Last raised 01
$520M extension / >$935M Series A [CO007, CV008] Diligence report
Apptronik
Industrial humanoid robotics platform with strong strategic backing but limited public operating proof
Apptronik is a well-capitalized industrial humanoid robotics company with credible partner validation, but public proof is still too thin to justify a buy at a $5B-plus mark.
Coverage and disclosure
Public disclosures and retained coverage through 2026-09-24 support the financing, partner, and product narrative, but audited financials, ARR, pricing, and governance remain undisclosed.
Cover facts
Company profile
Apptronik is a private Austin-based humanoid robotics company that develops Apollo for industrial work in factories, warehouses, logistics, and retail back-of-house environments. The public record shows strong strategic validation, but it still leaves pricing, customer economics, and governance only partially disclosed.
- Website
- apptronik.com
- Founders
- Jeff Cardenas, Nick Paine
- Founding location
- Austin, Texas, USA
- Headquarters
- Austin, Texas, USA
- Product
- Apollo humanoid robot platform for industrial and back-of-house work
- Customers
- Manufacturing, warehousing, logistics, and retail operations
- Business model
- Enterprise humanoid robot deployments, integration, and support; public pricing is not disclosed
- Stage
- Late-private / Series A-X
- Funding status
- Series A with a $520M extension; public disclosures put total Series A capital above $935M and total capital near $1B
Executive summary
Top strengths
- Strong industrial partner validation from Mercedes-Benz, GXO, and Jabil
- Large capital base and continued financing support execution
- Clear focus on industrial humanoid deployment rather than a vague consumer story
Top risks
- Public operating metrics, revenue, and deployment KPIs remain sparse
- Valuation already implies execution before durable proof
- Customer concentration, manufacturing ramp, and governance opacity could slow the thesis
Open gaps
- No audited revenue, ARR, cash balance, or runway disclosure
- No public customer-side throughput, uptime, or repeat-usage metrics
- Full board composition, control rights, and cap-table terms remain undisclosed
- Exact near-term SAM / SOM and pricing remain unproven
Contents
01Company Overview
1.1 Identity and product posture
Apptronik presents itself as a humanoid-robotics platform company rather than a single-product hardware vendor. Its own materials describe Apollo as a stack that combines advanced hardware, embodied AI, and fleet-level tools, with applications spanning manufacturing, warehousing, and retail. The public identity story is consistent across the company’s homepage, press materials, and investor-facing summaries: Austin headquarters, 2016 founding, and a University of Texas at Austin origin. What is still missing is the commercial detail that would let a buyer model the business cleanly, especially a public list price, published throughput numbers, or a stable revenue disclosure. [CO001, CO002, CO003, CO012, CO014, CO015]
| Metric | Value / status | Date | Confidence | Gap |
|---|---|---|---|---|
| Headquarters | Austin, Texas | 2026-06 | high | No contrary evidence in the retained sources |
| Founding | 2016 | 2016 | high | Exact incorporation filings not retained here |
| Product | Apollo humanoid robot platform | 2026-09-24 | high | No public list price or SKU-level catalog |
| Stage | Private; later-stage Series A / extension financing | 2026-02-11 | high | Exact equity terms are undisclosed |
| Total capital raised | Nearly $1B / reported range $431.38M to >$935M depending on source and date | 2026-02-11 | medium | Different public summaries use different cutoffs |
| Valuation | $5.5B reported by independent secondary-market summary | 2026-06 | medium | Secondary-source estimate, not company-confirmed |
| Employees | 150+ to ~300 publicly reported | 2025-02 to 2026-02 | medium | No official current headcount disclosed |
| Customers / deployments | Mercedes-Benz, GXO, Jabil, and other pilot / validation relationships | 2024-03 to 2026-02 | medium | No public throughput or conversion metrics |
| Pricing | No public Apollo list price; quote-based enterprise engagement only | 2026-07 | medium | Commercial terms not published |
| Governance | First outside board director named, but full board roster is not public | 2025-02 | medium | Control rights remain undisclosed |
Public summaries disagree on several scale metrics; values reflect the latest publicly stated or reported figure in the retained sources, and the gap column explains what remains unknown or contested.
[CO003, CO005, CO006, CO011, CO012, CO013, CO014, CO015]1.2 Leadership, founders, and governance
The named leadership bench is clear enough to establish the company’s technical and commercial center of gravity. Jeff Cardenas and Nick Paine are consistently presented as co-founders, with Cardenas in the CEO seat and Paine as CTO; later public materials add Kay Sheils as CFO and Animesh Garg as CSO. The same sources also point to Gordon Daugherty as the first outside board director, which is helpful but still far short of a full governance picture. That matters because a company this private can look more transparent than it is: public leadership names do not substitute for board composition, shareholder control rights, or any formal key-person risk schedule. [CO009, CO010, CO013, CO014]
| Person | Role | Background / coverage | Key-person or governance note | Diligence ask |
|---|---|---|---|---|
| Jeff Cardenas | Co-founder, CEO | Public face of the company and commercial lead | Central to strategy, fundraising, and product narrative | Confirm succession planning and board oversight |
| Nick Paine | Co-founder, CTO | Robotics and actuator lineage from UT Austin / NASA work | Core technical founder | Confirm IP ownership and technical bench depth |
| Kay Sheils | CFO | Finance leader added in the StartEngine summary | Supports scale and capital planning | Confirm controls and reporting cadence |
| Animesh Garg | CSO | AI / robotics research leadership | Shapes autonomy and scientific roadmap | Confirm execution ownership for model / data strategy |
| Gordon Daugherty | First outside board director (publicly named) | Capital Factory chairman; early investor link | Only explicitly named board-linked individual in retained sources | Confirm full board composition and voting rights |
The table is intentionally partial because the company does not publish a full board roster or governance schedule in the retained sources.
[CO009, CO010, CO013, CO014]1.3 Capital, valuation, and traction
Apptronik’s capital story is the clearest part of the public record. The company announced a $350 million Series A in February 2025, then a $520 million extension in February 2026 that took the Series A above $935 million and total capital to nearly $1 billion. The investor list expanded from B Capital, Capital Factory, and Google into a broader strategic syndicate that now includes Mercedes-Benz, PEAK6, AT&T Ventures, John Deere, and QIA. Independent summaries then pushed the valuation conversation to $5.5 billion, while the company itself stayed careful and only described the 2026 extension as a multiple of its prior valuation. That gap between what is disclosed and what is inferred is the core diligence issue here. [CO005, CO006, CO007, CO008, CO012, CO015]
| Stakeholder | Role | Why it matters | Diligence ask |
|---|---|---|---|
| B Capital | Lead / repeat investor | Anchors the financing story and validation of the market | Confirm post-money rights and any protective provisions |
| Capital Factory | Co-lead investor and governance-linked backer | Connects to the company’s board narrative | Confirm whether board influence extends beyond the named outside director |
| Google / DeepMind | Strategic investor and AI partner | Signals technical credibility in embodied AI | Confirm whether the collaboration creates commercial obligations or only research support |
| Mercedes-Benz | Strategic investor and pilot customer | The strongest public industrial validation | Confirm pilot-to-production criteria and scope |
| GXO Logistics | Pilot / proof-of-concept customer | Tests the warehouse use case | Confirm whether the relationship is still experimental or commercially ordered |
| Jabil / 2026 extension investors | Manufacturing partner and later-stage strategic capital | Relevant to scaling and supply chain | Confirm manufacturing commitments and order pipeline |
This is a stakeholder map, not a cap table; public sources reveal named relationships, but not the control economics behind them.
[CO005, CO006, CO007, CO008, CO012, CO015]1.4 Milestones and remaining diligence gaps
The milestone trail shows a company that is moving steadily from research lineage into commercialization, but not yet into a fully legible operating business. The public chronology runs from the 2016 spinout and Apollo’s robotic lineage, through the 2025 financing milestones, into the 2026 extension, production ramp, and the newer commercial-robot narrative. The same chronology also exposes what Apptronik does not yet publish: no public list price, no customer-site throughput metrics, no official board roster, and no clean, current headcount number. Those gaps are not minor polish items; they are the main blockers to turning a compelling robotics story into a fully underwritten operating case. [CO003, CO004, CO006, CO008, CO011, CO015, CO016]
Apptronik’s public story moves from research spinout to aggressive financing and 2026 commercialization signals, while the most important operating details remain private.
Timeline dates reflect public announcement dates or listing-update dates, not necessarily the underlying contract or execution date.
[CO003, CO005, CO006, CO007, CO012, CO013, CO014, CO016]02Market Analysis
2.1 Market boundary and substitutes
Apptronik's public materials define the market around physically demanding work in human-built environments, not consumer companionship or home service robotics. The company centers Apollo on manufacturing, warehouse, logistics, and retail back-of-house workflows, while the broader category still competes with manual labor and conventional automation. That matters because the market boundary is narrower than "all robots" and wider than a single factory pilot: the near-term spend is tied to repetitive tasks, structured facilities, and budgets that care about labor relief, uptime, and integration cost. The excluded set includes consumer/home robots and fixed automation that does the job more cheaply when humanoid form is not needed.[CM001, CM002, CM003, CM005, CM014]
| segment/category | included spend | excluded spend | buyer/payer | relevance |
|---|---|---|---|---|
| Industrial humanoid robots | Robots, deployment software, integration, fleet tooling, and support for repetitive physical work in structured facilities | Consumer/home robots and entertainment/toy robots | Ops, plant, warehouse, and supply-chain leaders paying from automation or labor budgets | Core near-term market |
| Adjacent automation | Humanoid deployments where the form factor adds value versus fixed automation | Conveyors, arms, AMRs, and other cheaper non-humanoid substitutes | Manufacturing engineering and operations | Useful adjacency but not pure humanoid TAM |
| Retail back-of-house | Inventory, replenishment, and back-room handling | Front-of-house service robots and consumer assistant devices | Store operations and retail labor budgets | Minor adjacency in the current public product set |
| Future healthcare / eldercare / home | Future service workflows beyond current industrial focus | Current industrial deployments | Hospitals, eldercare operators, or households | Downstream optionality, not the current core |
| Status quo manual labor | Labor spend tied to repetitive physical work | Robotics purchases | Operations budgets measured against productivity and safety | The main substitute and adoption benchmark |
Boundary is an analyst synthesis from public product/use-case statements; excluded rows are treated as substitutes or adjacencies rather than a source-defined taxonomy.
[CM001, CM002, CM003, CM005, CM014]2.2 Sizing lenses and valuation signals
The available market-sizing evidence is better treated as a stack of lenses than as one clean TAM. Two secondary pages cite very different long-horizon estimates for humanoid or robotics demand, and the private market pricing pages show that investors are willing to ascribe multi- billion-dollar value to the company even though the operating proof is still limited. That mix supports a high-conviction view that the category is large, but a low-conviction view on any exact near-term SAM or SOM. The figure below intentionally layers those heterogeneous signals instead of pretending they are directly comparable.[CM007, CM008, CM009, CM010, CM011, CM012]
| publisher | year | geography | value | CAGR | methodology | confidence | limitation |
|---|---|---|---|---|---|---|---|
| StartEngine | 2026 | global | $38B | n/a | Goldman Sachs humanoid-robot TAM cited on the page | medium | Secondary citation and broad category; not Apptronik-specific |
| TSG Invest | 2025 | global | $5T | n/a | Morgan Stanley long-horizon robotics estimate cited in the memo | medium | Extremely long-dated and very broad |
| Forge Global | 2026 | US/private market | $5.3B | n/a | Indicated private-market valuation from Forge Price | medium | Valuation signal, not a market-size estimate |
| The Information | 2026 | global/private market | $5B | n/a | Reported funding talks in the page title | high | Paywalled title snippet; not a closed financing |
These rows are deliberately non-comparable lenses: external TAM quotes, private-market marks, and a reported valuation talk. They bracket market appetite but do not produce a defensible Apptronik SAM/SOM.
[CM007, CM008, CM009, CM010, CM011]A layered view of the public market signals around Apptronik, from broad humanoid TAM claims down to current private-market pricing and the company's still-limited operating proof.
Layer widths indicate hierarchy, not quantitative proportions.
This is a layered evidence stack, not a numeric roll-up. The available sources do not isolate a defensible Apptronik SAM or SOM, so heterogeneous market and valuation signals are shown together rather than forced into a single arithmetic estimate.
[CM001, CM005, CM007, CM008, CM009, CM010, CM011, CM012, CM013, CM014]2.3 Buyer map, adoption triggers, and constraints
The buyer path looks operational rather than consumer-led. The primary buyer and budget owner are usually operations, plant, or warehouse leaders who need help with repetitive physical tasks, labor shortages, and throughput pressure. Apptronik's own materials point to a deployment model that starts in factories and warehouses, then expands into retail back-of-house and only later into healthcare, eldercare, or the home. The main constraints are not just technical; they are proof, cost, safety, and the need to show concrete throughput gains instead of partner logos. Until those metrics are public, adoption remains a pilot-to-production question rather than a fully proven category shift.[CM001, CM002, CM003, CM004, CM005, CM006, CM013, CM014]
| segment | buyer | user | payer | workflow | budget owner | adoption trigger |
|---|---|---|---|---|---|---|
| Factories | Operations or plant leadership | Line workers and technicians | Manufacturing capex or pilot budget | Material handling, line-side tasks, inspection, and repetitive workflows | Manufacturing ops or industrial engineering | Labor shortages and repetitive tasks without factory redesign |
| Warehouses and logistics sites | Warehouse or logistics operations | Warehouse associates | Automation or RaaS budget | Pick-pack-move, trailer unloading, and sorting | Warehouse operations | Throughput pressure and labor availability |
| Retail back-of-house | Store operations | Retail associates | Retail labor or ops budget | Inventory, replenishment, and back-room tasks | Store operations | Physical strain and staffing gaps |
| Early production partners | Strategic operations or engineering leadership | Robotics, manufacturing, and support teams | Strategic capex or partner budget | Integration, testing, and support for repeatable machines | Manufacturing engineering plus operations | Need for a production path and field proof |
Buyer and payer roles are inferred from the public deployment language and named customer contexts, not from disclosed procurement contracts.
[CM001, CM002, CM003, CM005, CM006, CM011, CM013]03Competitors
3.1 Competitive landscape
Apptronik's real competition is not just other humanoids. A buyer can choose a pilot-only humanoid, a more mature warehouse robot, fixed automation, internal build, or simply manual labor. That means the purchase decision blends technical capability with deployment friction, serviceability, and whether the customer wants a general-purpose platform or a narrower, more immediately purchasable tool. Apptronik's public position is strongest where the task is repetitive industrial work, but the company still lacks the sort of customer-published operating numbers that would make its lead look durable. In practice, the category looks crowded on logos and thin on transparent KPI reporting, which makes status quo and internal automation viable substitutes, not afterthoughts.[CP001, CP003, CP004, CP007, CP011, CP012]
| Competitor | Category | Public scale / funding | Target segment | Differentiation | Limitation |
|---|---|---|---|---|---|
| Apptronik Apollo | Direct humanoid peer | Series A / A-X scale capital; no public list price | Manufacturing and logistics first | Jabil manufacturing path and Google DeepMind support | Public scoreboard is still partner-heavy and metric-light |
| Tesla Optimus | Incumbent entrant | No mass-production channel yet in the pool sources | Tesla internal use and future industrial work | Brand, capital, and manufacturing optionality | Not yet a purchasable or mass-market product |
| Figure 03 | Direct humanoid peer | Well-funded; 350+ robots built and BMW logistics work starting | Automotive and industrial operations | Clearer public deployment receipts than Apptronik | No sales channel or public order path |
| Agility Digit | Adjacent warehouse robot | RaaS available; public warehouse work | Warehouse and logistics | Commercially acquirable today | Narrower task envelope than a general-purpose humanoid |
| Boston Dynamics Atlas | Premium incumbent | Production slots committed in the pool sources | Industrial and plant work | Production product with strong brand trust | Limited availability and first-year output commitments |
| Manual labor | Status quo substitute | No capex / no integration | Any repetitive physical work | Immediate availability and flexible task absorption | Labor shortages, injury risk, and turnover remain costs |
| Internal build / fixed automation | Internal substitute | Project-specific capex | Highly stable workflows | Can be tailored to a single facility or line | Less flexible than a humanoid platform |
Comparative synthesis from the assigned source pool; scale and limitation fields reflect public evidence only, and 'no public' / 'unknown' means no disclosure found in the pool rather than proof of absence.
[CP001, CP004, CP005, CP006, CP007, CP008, CP011, CP012, CP013]3.2 Public proof versus promise
The peer comparison here is less about headline funding and more about what a buyer can verify. Figure and Agility appear ahead on public proof because their advocates publish operating numbers, while Apptronik's public record is still mostly partner names, manufacturing intent, and future plans. Tesla and Atlas matter as strategic pressure, but their commercial availability is still limited enough that they function more like long-dated threats than current procurement options. The practical takeaway is that Apptronik is competing in a proof race, not a demo race, and every additional public KPI from a peer raises the bar for Apollo.[CP005, CP006, CP008, CP013]
| Buying criterion | Apptronik Apollo | Tesla Optimus | Figure 03 | Agility Digit | Boston Dynamics Atlas |
|---|---|---|---|---|---|
| Public deployment metrics | No published customer KPI scoreboard | No public deployment scoreboard in the pool sources | BMW-linked operating numbers and deployment reporting | Published warehouse milestones and RaaS work | Production launch, but no comparable customer KPI set |
| Purchase / contract access | Quote-based enterprise pilots only | No public order path | No sales channel disclosed | RaaS and quote-based access | Production slots committed rather than open inventory |
| Industrial fit | Factories, logistics, and repetitive handling | Future industrial use | Automotive and industrial logistics | Warehouse and logistics | Industrial and plant work |
| Manufacturing readiness | Jabil partnership is a strategic asset | Manufacturing ambitions, but not public commercial volume | BotQ-style ramp narrative | Third-party production path | Production product with committed output |
| Trust / regulatory posture | Enterprise pilots with safety-zone language | High uncertainty | Private and still proving operating safety | Known warehouse deployment path | More mature industrial posture |
| Moat signal | AI stack plus partner breadth | Brand and capital | Public proof scoreboard | Commercial accessibility | Production status and reputation |
Matrix uses public evidence only; unsupported cells are deliberately phrased as 'No public' or similar so the reader can distinguish missing disclosure from negative proof.
[CP004, CP006, CP007, CP009, CP010, CP012, CP013]Higher scores indicate more public proof and easier procurement access.
| Item | X (1–5) | Y (1–4) | Context |
|---|---|---|---|
| 1. Apptronik Apollo | 2 | 3 | |
| 2. Figure 03 | 2 | 4 | |
| 3. Agility Digit | 4 | 4 | |
| 4. Tesla Optimus | 1 | 1 | |
| 5. Boston Dynamics Atlas | 3 | 4 | |
| 6. Internal build / fixed automation | 5 | 3 |
Ordinal coordinates from public evidence, not measured market data.
[CP013, CP014]3.3 Distribution, pricing, and moat durability
Apptronik's best wedge is not a unique humanoid body plan; it is the combination of AI leverage, a manufacturing path, and enterprise partners that can turn pilots into field learning. Jabil makes the production story more credible, and Google DeepMind gives the software stack real technical depth, but neither is a moat until it produces measurable cost or uptime advantages. The risk is that hardware form factors and general-purpose autonomy could commoditize faster than deployment relationships harden. In that world, the winners are the vendors that can turn pilots into repeatable operations and quote-based deals into standardized buying channels.[CP009, CP010, CP012, CP013, CP014]
| Package / channel | Apptronik Apollo | Key competitor analog | Implication |
|---|---|---|---|
| Public price | No public list price; quote-based only | Agility Digit has RaaS terms by quote | Procurement is relationship-driven, not self-serve |
| Access path | Enterprise pilots with customers | Figure 03 lacks a sales channel | Apptronik is closer to pilot-led enterprise software than consumer hardware |
| Deployment model | Pilot, test, and manufacturer learning loop | Atlas production slots are committed | Availability can matter as much as technical quality |
| Industrial economics | Return depends on task repeatability and service burden | Manual labor has no capex but high operating friction | The value proposition must beat labor plus integration costs |
| Scale path | Jabil manufacturing partner plus field learning | Tesla and Figure rely on internal scale narratives | Manufacturing execution can become a real moat if it compresses cost and turnaround |
Packaging rows reflect public channel models, not realized economics or negotiated discounts; where a price is not public, the cell is intentionally 'No public' rather than estimated.
[CP004, CP007, CP008, CP009, CP011, CP014]04Financials
4.1 Revenue model and monetization
Apptronik presents Apollo as an industrial robot platform for manufacturing, warehouse, and retail workflows, so the most plausible operating revenue is tied to deployments, support, and integration rather than pure software licensing. The reviewed sources do not disclose a public list price, realized contract value, or revenue mix, which means the revenue bridge still has to be inferred from product positioning, strategic customer logos, and a small amount of third-party pricing commentary. The clearest public monetization clue is the secondary-market estimate that Apollo may be priced around $80,000 per unit, but that figure is not company-published and should be treated as directional only. The revenue streams table and pricing table below separate company-described activity from market inference so the reader can see what is known, what is implied, and what is still absent.[CI001, CI004, CI005, CI010]
| stream | mechanism | unit | current value/status | quality | diligence ask |
|---|---|---|---|---|---|
| Apollo pilot deployment revenue | time-limited proof-of-value pilots and early deployments | site or pilot | announced but not monetized publicly | medium | Are pilots paid and what portion converts? |
| Apollo production deployments | robot units or fleet contracts at customer sites | unit or site | future or early-stage; no public active-robot count | low | How many robots are on recurring contract? |
| Service and support | installation training maintenance and spare parts | site per year | implied by field robotics model; margin undisclosed | low | What is the attach rate and service margin? |
| Fleet software and monitoring tools | telemetry updates and fleet-level management | site per month | described on the homepage but not priced separately | low | Is software bundled or billed separately? |
Public materials support the deployment and support model, but none of the reviewed sources disclose a revenue mix or realized operating revenue by stream.
[CI001, CI004, CI010, CI012]| price/unit/contract | list vs realized pricing | discounts/unknowns | source |
|---|---|---|---|
| $80,000 per Apollo unit | implied secondary estimate | not a published list price; realized pricing unknown | Forge cites B Capital / Howard Morgan |
| $25 per security | secondary investment price | not an operating price; no revenue relevance | StartEngine |
| $5.3B to $5.5B valuation band | capital-market valuation not product pricing | total capital and cap table still inconsistent across sources | Forge / Tracxn / New Market Pitch |
| Commercial agreement terms | undisclosed | no public unit economics or discounting disclosed | Apptronik and Mercedes-Benz / GXO references |
This table separates product monetization from investor-market pricing because the public record only exposes an implied robot price and private-market share pricing, not a disclosed list price.
[CI005, CI006, CI008, CI009]Apollo appears to move from industrial pilot demand to deployment fees, support revenue, and eventual fleet-scale economics, but the public record still hides the pricing and conversion step.
| Node / Connection | Node / from | To | Context |
|---|---|---|---|
| Node 1 | Industrial demand [demand] | Manufacturing and warehouse labor pain points | |
| Node 2 | Pilots and proof-of-value [pilots] | Mercedes-Benz, GXO, and Jabil references | |
| Node 3 | Commercial deployments [deployments] | Unit or fleet rollouts, if pilots convert | |
| Node 4 | Services and support [support] | Installation, training, maintenance, spares | |
| Node 5 | Fleet software [software] | Telemetry and management tools | |
| Node 6 | Private capital [capital] | Funding required before public revenue disclosure | |
| Connection 1 | Industrial demand [demand] | Pilots and proof-of-value [pilots] | |
| Connection 2 | Pilots and proof-of-value [pilots] | Commercial deployments [deployments] | |
| Connection 3 | Commercial deployments [deployments] | Services and support [support] | |
| Connection 4 | Commercial deployments [deployments] | Fleet software [software] | |
| Connection 5 | Services and support [support] | Private capital [capital] |
The bridge is conceptual because the reviewed sources do not disclose a public pricing sheet, revenue mix, or cash-flow statement.
[CI001, CI002, CI003, CI004]4.2 Capital profile and valuation
Apptronik has already raised a very large amount of private capital for a company that still does not publish public operating metrics. The official 2025 press release says the company closed a $350 million Series A and then a $403 million total round in March 2025; later market-data sources move the estimate closer to $956 million raised and a $5.5 billion valuation, while Forge and New Market Pitch both put the valuation in the $5.3 billion range. The point is not that one source is correct and the others are wrong. It is that the public capital picture is now large enough to require execution-level proof, but the exact numerator remains fuzzy enough that underwriting should treat the numbers as estimates rather than audited facts. That makes financing dependency, future dilution, and the absence of cash/runway disclosure central diligence issues.[CI002, CI003, CI006, CI008, CI009]
4.3 Cost structure, unit economics, and diligence gaps
The cost side is also under-disclosed. Apptronik's public materials point to hardware, field deployment, fleet tools, services, and manufacturing support, which implies a capital-intensive operating model with meaningful service-delivery, inventory, and support costs. But no reviewed source gives gross margin, cash balance, burn, runway, or capex detail, so the company cannot be underwritten as a conventional software business and should not be treated like one. Public headcount signals are similarly inconsistent: the company itself said it had over 150 employees in 2025, StartEngine cited 195 employees, and Tracxn later listed 504 employees, which is a useful reminder that even basic operating-scale metrics remain fluid. The unit economics table below makes the missing inputs explicit and ties each gap to a specific diligence ask.[CI007, CI011, CI012]
| metric | value or null | confidence | why it matters | diligence ask |
|---|---|---|---|---|
| gross margin | none | Determines whether Apollo can scale profitably once deployments start | Disclose product and service gross margin by program | |
| cash balance | none | The core indicator of short-term financing dependency | Provide latest balance sheet cash | |
| burn rate | none | Needed to estimate runway and next-round timing | Provide monthly burn and forecast | |
| runway | none | Tells us how much time remains before another raise is needed | Provide runway under base and downside cases | |
| headcount | 150+ to 504 across public sources | low to medium | Proxy for payroll scale and operating burn | Reconcile HR and payroll numbers |
| customer count | at least 3 named strategic customers | low | Concentration and conversion risk remain opaque | Disclose paying customer count and active robots |
Values are either unavailable or inconsistent across public sources; where the table shows a range, it reflects public-source disagreement rather than a management disclosure.
[CI006, CI007, CI009, CI011, CI012]05Product & Technology
5.1 What Apollo is and where it fits
Apptronik presents Apollo as a human-centered humanoid robot built first for manufacturing and logistics, with later use cases in healthcare, the home, retail, and other physically demanding settings. The public product story is broader than a single task robot: Apollo is framed as a platform for collaborative work in human-centered spaces, not as a lab demo. That matters because the near-term diligence question is not whether Apptronik can describe a compelling robot, but whether the company can show that the same platform is useful, repeatable, and supportable in real factory and warehouse environments. The company has strong partner names, but the public record still leaves deployment maturity and measurable task performance only partially answered.[CE001, CE004, CE005, CE006]
| module / asset | primary user | status / maturity | differentiation | diligence gap |
|---|---|---|---|---|
| Apollo humanoid platform | Manufacturing and logistics operators | Pilot / early deployment | Human-centered humanoid platform with modular mobility and embodied AI | Need partner-side operating metrics |
| Manufacturing workflow package | Factory and lineside teams | Pilot / validation | Built for physically demanding, repetitive, or hazardous work | Need cycle-time and quality data |
| Warehouse workflow package | Fulfillment and 3PL teams | Pilot / validation | Designed to pick, pack, move goods, and reduce strain | Need uptime and intervention data |
| Motion-data / control stack | Internal robotics team | Active development | Motion capture, teleoperation, synthetic data, and whole-body RL | Need technical benchmarks and release notes |
Status labels are inferred from public wording, not measured deployment grades; gap fields name the missing diligence item.
[CE001, CE002, CE003, CE005, CE010, CE011]| user job | current workflow | Apptronik solution | measurable benefit | limitation |
|---|---|---|---|---|
| Repetitive factory tending | Human labor or fixed automation | Apollo in designated factory areas | Potentially lower strain and broader task coverage | No public cycle-time or intervention-rate data |
| Warehouse picking and moving | Manual handling or conventional warehouse automation | Apollo for warehouse/logistics work | Potentially supports pick, pack, move, and fulfillment tasks | No public throughput or uptime numbers |
| Robot learning and adaptation | Manual teleoperation and offline tuning | Motion-data pipelines plus whole-body RL | Should improve skill acquisition and retargeting | No public sim-to-real benchmark set |
Benefits are inferred from public descriptions; null-like gaps are not missing rows, they are unresolved public evidence.
[CE001, CE006, CE007, CE010, CE012]5.2 How the stack works
The most useful technical breadcrumb is Apptronik's own hiring language. It points to motion-capture, teleoperation, synthetic data generation, retargeting, and whole-body reinforcement learning pipelines, which suggests a sim-to-real development loop rather than a fixed-function machine. Apptronik also says Apollo combines advanced hardware, embodied AI, and fleet-level tools, which implies the company is trying to operate a deployed robot fleet rather than only sell hardware. The result looks like a vertically integrated robotics stack: body, control software, data pipelines, and support tooling. That is a credible architecture for a humanoid program, but the public sources do not yet reveal enough technical detail to judge repeatability, benchmark performance, or how much of the stack is actually field-proven.[CE002, CE003, CE010, CE011]
| layer / component | role | dependency | risk |
|---|---|---|---|
| Body hardware and actuation | Mobility and manipulation platform | Motors, batteries, sensors, and manufacturing quality | Cost, reliability, and field repair pressure |
| Motion-data and control stack | Train and deploy robot behavior | Mocap, teleoperation, synthetic generation, retargeting | Data quality and sim-to-real gap |
| Deployment / safety layer | Rollout and human coexistence | External sensors, light curtains, service support | Certification, incident, and privacy gaps |
This is a synthesized operating view from public descriptions, not a complete internal architecture diagram.
[CE002, CE003, CE006, CE010, CE011, CE012]Public signals suggest a layered Apollo stack spanning customer workflow fit, robot hardware, motion-data control, AI partnership, deployment guardrails, and unresolved operating proof.
- Workflow fit
- Manufacturing, logistics, and retail use cases
- Modules
- factory tending
- warehouse work
- future-facing applications
- Outputs
- human-centered task coverage
- Robot body
- Mobility and manipulation platform
- Modules
- bipedal mobility
- wheeled mobility
- dexterous manipulation
- Outputs
- Apollo platform
- Motion-data loop
- Mocap, teleoperation, synthetic generation, RL
- Modules
- mocap
- teleoperation
- retargeting
- whole-body RL
- Outputs
- skills and policies
- AI partner layer
- Google DeepMind and Gemini Robotics
- Modules
- multi-embodiment reasoning
- embodied AI
- Outputs
- better action selection
- Deployment guardrails
- Sensors, light curtains, designated areas
- Modules
- external sensors
- light curtains
- boundary control
- Outputs
- safer initial rollout
- Open diligence gaps
- Uptime, certification, privacy, support
- Modules
- metrics
- certification
- incident data
- support
- Outputs
- unknown maturity
Layer order is synthesized from public descriptions, not an internal architecture diagram.
[CE001, CE002, CE003, CE006, CE007, CE009, CE010, CE012]5.3 Deployment, integration, and trust gaps
Public reporting shows Apollo in designated areas at factories and warehouses with Mercedes-Benz, GXO, and Jabil, and CNBC says those areas use external sensors and light curtains so the robot pauses if a person crosses the boundary. That is a cautious rollout model, not a fully open-field autonomy story. Independent commentary is more skeptical: the public evidence is still partner-heavy and metric-light, with no visible Apollo scoreboard for uptime, throughput, intervention rate, or cost per task. The trust and safety picture is therefore incomplete. Apptronik looks serious about industrial deployment, but the public record still leaves certification, incident, recovery, and privacy documentation open.[CE007, CE008, CE009, CE012]
06Customers
6.1 Customer base and use-case segmentation
Apptronik’s public customer story is concentrated in industrial settings. The company’s own product page frames Apollo around manufacturing, warehouse, and retail workflows, while recent coverage narrows the near term focus further to factories and warehouses first. That matters because the buyer is usually an operations or automation leader, the user is a frontline site team, and the value proposition is labor relief, repetitive task support, and safer material handling rather than a broad consumer or home use case. The key diligence issue is that Apptronik can clearly name the industrial environments it wants, but not yet the public operating metrics that show how many deployments have crossed from trial into durable repeat use.[CU001, CU002, CU011]
| segment | buyer/user/payer | use case | scale | revenue/strategic value | gap |
|---|---|---|---|---|---|
| manufacturing operators | operations or automation leaders and line teams | repetitive material handling and line-side support | industrial beachhead | proves factory-fit positioning | no public site-level KPI or conversion data |
| warehouse and 3PL operators | warehouse ops leaders and fulfillment teams | pick/pack/move goods and trailer-adjacent work | growth wedge | validates logistics demand | no public throughput or uptime metrics |
| automotive factories | plant engineering and production managers | pilot/commercial agreement in factory settings | marquee reference | gives credibility with large industrial buyers | pilot-to-rollout status is not disclosed |
| manufacturing production partners | manufacturing and supply-chain teams | build and scale Apollo units | production path | may lower unit-cost and service friction | contract-manufacturing scope is not public |
Partial public mapping based on the assigned evidence set; "scale" and "revenue/strategic value" are inferred from public positioning rather than disclosed customer economics.
[CU001, CU002, CU005, CU011]Apollo’s public customer journey runs from industrial discovery to pilots and commercial agreements, with a production path emerging but public KPI disclosure still missing.
[CU001, CU004, CU007, CU008, CU010, CU013]6.2 Named deployments and adoption trajectory
The strongest public proof is still a small set of named enterprise relationships. Apptronik has publicly tied Apollo to Mercedes-Benz and GXO Logistics, and later coverage added Jabil as a production-path signal. That combination is meaningful: Mercedes-Benz shows automotive-floor validation, GXO shows logistics exposure, and Jabil suggests that Apptronik is trying to move from pilots toward a repeatable manufacturing pathway. Still, the record remains partner-heavy and metric-light. The company has not published the sort of customer scoreboard that would answer how many robots are active, how often they work, or how often a pilot becomes a recurring deployment.[CU003, CU004, CU005, CU006, CU007, CU008]
| metric | value | date | source | confidence | implication | missing denominator |
|---|---|---|---|---|---|---|
| announced commercial relationships | 2 named industrial relationships | 2025-02-13 | Apptronik press release | high | shows early enterprise traction | public rollout counts |
| capital raised in latest public round | $520M Series A-X and >$935M total Series A capital | 2026-02-12 | Trending Topics coverage | medium | supports continued scaling | customer conversion rate |
| public customer focus | factories and warehouses first | 2026-06-29 | New Market Pitch | medium | clarifies go-to-market | active account count |
| public operating KPI disclosure | not disclosed | 2026-09-24 | assigned source set | medium | indicates evidence gap not traction | customer-level throughput and renewals |
Mixed quantitative and qualitative trajectory table; the last row is an explicit gap so the reader does not mistake disclosure silence for weak demand.
[CU003, CU004, CU006, CU008]| customer | segment | deployment/use case | production vs pilot | outcome | limitation |
|---|---|---|---|---|---|
| Mercedes-Benz | automotive | factory workflow validation | pilot/commercial agreement | first publicly announced commercial deployment | no disclosed unit count or utilization |
| GXO Logistics | logistics/3PL | warehouse and logistics work | pilot/partnership | confirms logistics exposure | no public throughput or renewal data |
| Jabil | manufacturing/contract manufacturing | Apollo production path | production collaboration | strengthens repeatable manufacturing story | public customer-site KPI not disclosed |
Public named relationships are treated as proof of market access, not proof of scaled recurring revenue; the table is intentionally limited to the relationships visible in the assigned evidence set.
[CU004, CU007, CU012]6.3 Retention, expansion, and concentration risk
The durability question is where the public record gets thin. Apptronik does not disclose renewal rates, NRR, GRR, churn cohorts, or customer-level revenue mix, so the company’s customer quality has to be inferred from a handful of marquee relationships and the scale of the funding behind them. That creates two risks at once. First, the customer base may be more concentrated than the headline relationships suggest, because the public set of named relationships is still small. Second, expansion may be real but unproven, since the company has not yet shown whether pilots turn into repeatable production or multi-site rollouts. Until Apptronik publishes harder operating proof, the customer story remains promising but not yet fully durable.[CU009, CU010, CU012, CU013]
07Risks
7.1 Risk stack and thesis breakpoints
Apptronik's headline risk is that the market is now pricing the company for execution while public proof remains pre-scale. The strongest public signals are Robot Park and Apollo 3, but those same sources still describe Apollo 2 as a prototype for scaled pilots and data collection. That makes safety, regulatory friction, and the missing KPI scoreboard the near-term thesis breakpoints: if Apollo 3 slips again or the next public reveal still lacks throughput, uptime, and intervention data, the company will look well-funded but not yet de-risked. We did not surface public litigation or recall evidence in the reviewed material, but that remains an open diligence item rather than a cleared risk.[CR003, CR004, CR005, CR007, CR009, CR014, CR015]
| Risk | Jurisdiction / surface | Status | Likelihood | Severity | Mitigation | Residual exposure | Diligence path |
|---|---|---|---|---|---|---|---|
| Bipedal fall / proximity safety | U.S. factory and warehouse sites | Public materials emphasize safety controls, but no incident data is disclosed | Medium | High | Wheeled base, configurable safety zones, safe perception, staged pilots | Medium-high | Request site-safety package, incident logs, and insurance details |
| Regulatory compliance / mobility standards | Industrial mobile-robot rules and local site approvals | Wheeled configuration is designed around existing standards, while bipedal work still carries friction | Medium | High | Use wheeled deployments first and align with current standards | Medium | Confirm certification path, workcell design, and local approvals |
| Human-robot workplace liability | Customer premises and labor-safety regimes | Current deployments still appear to require engineered workcells or barriers | Medium | High | Constrain initial deployments, training, and site validation | Medium-high | Ask for deployment SOPs and liability coverage |
Risk severity and likelihood are analyst judgments based on public evidence; the table is partial because no docket or regulator sweep was performed here.
[CR004, CR009, CR014]Apptronik's public risk stack is dominated by execution and proof risk, with safety/regulatory and concentration concerns next, and valuation/liquidity a close third.
[CR004, CR005, CR006, CR007, CR013, CR014]7.2 Operational, quality, and security risks
Operationally, Apptronik is no longer a lab with a few engineers; it needs manufacturing, service, IT, and security functions that look like a real industrial hardware business. The job posting and press releases imply growing on-prem infrastructure, backups, and high-availability expectations, while Jabil and Robot Park show how much the company depends on repeatable physical execution. This is why the largest residual exposure here is not one isolated bug but the possibility that Apollo 3 arrives without durable unit economics, serviceability, or field reliability. The clearest diligence ask is still public or customer-side evidence of uptime, intervention rate, mean time to recover, and safety incidents.[CR001, CR002, CR008, CR010, CR011, CR012]
| Failure mode | Likelihood | Severity | Mitigation maturity | Residual exposure | Unresolved gap |
|---|---|---|---|---|---|
| Apollo 2 remains a prototype for scaled pilots and data collection rather than a standard product | High | High | Medium | High | Need Apollo 3 delivery plus customer metrics |
| Mass-production ramp depends on Jabil and other manufacturing execution | Medium-high | High | Medium | High | Need yield, serviceability, and ramp data |
| Public throughput, uptime, intervention-rate, and cost-per-task metrics remain sparse | High | High | Low-medium | High | Need customer-side KPI disclosure |
| Internal IT, service, and security infrastructure must scale with headcount | Medium | Medium-high | Medium | Medium | Need service org and security controls evidence |
The table combines product-readiness and operating-model risks; severities are relative to the public evidence available in this run, not internal company data.
[CR003, CR005, CR008, CR010, CR011, CR012]7.3 Partner, concentration, and financing risks
The company also carries concentration risk. The public narrative depends on a short list of named counterparties - Mercedes-Benz, GXO, Jabil, and Google DeepMind - so any one relationship shifting could slow both customer proof and product learning. On top of that, Apptronik is now being discussed at a roughly $5B valuation, which means private-market liquidity and follow-on capital discipline matter almost as much as product milestones. If the next financing or secondary pricing compresses, or if partner access to data or model support weakens, the thesis should be repriced quickly. The right mitigants are milestone-based spend, broader customer diversification, and explicit data/model rights.[CR006, CR007, CR011, CR012, CR013]
| Dependency | Counterparty | Role | Concentration | Failure scenario | Severity | Mitigation | Residual exposure |
|---|---|---|---|---|---|---|---|
| Customer proof concentration | Mercedes-Benz / GXO / Jabil | Reference customers and deployment venues | High | A pilot slips, stalls, or never scales into repeatable orders | High | Broaden customer base and publish a KPI scoreboard | High |
| Manufacturing path concentration | Jabil | Apollo production partner | Medium-high | Quality or capacity issues slow unit ramp | High | Dual-source critical components and validate serviceability | High |
| AI / model dependence | Google DeepMind | Embodied-AI collaboration and Gemini Robotics support | Medium | Model access or roadmap shifts dilute differentiation | High | Retain internal actuation and data flywheel; lock in rights | Medium-high |
| Capital / valuation dependence | Follow-on investors and the secondary market | Financing and price support | High | Down-round or illiquidity compresses returns | High | Tie future spend to deployment milestones and cash runway | High |
Dependency risk here includes both operating partners and the capital stack; the table uses public counterparties only and does not assume undisclosed contract terms.
[CR006, CR007, CR011, CR012, CR013]08Valuation
8.1 Recommendation and price context
Apptronik now sits in a classic late-private valuation gap: the company has enough capital to keep scaling, but not enough public operating proof to justify a precise intrinsic valuation. The public record shows a 2025 Series A that was already unusually large, a 2026 extension that took total capital above $1B, and a reported mark above $5.5B. That combination supports a cautious track call rather than a buy. The current price already assumes that Apollo can move from strategic interest to repeatable deployment economics, and the public sources do not yet show audited financials, ARR, or a disclosed cap-table stack that would let us underwrite the downside with confidence. [CV001, CV004, CV008, CV009, CV011, CV013]
| Decision state | Recommendation | Confidence | Risk rating | Valuation stance | Decision implication |
|---|---|---|---|---|---|
| Current evidence | track | medium | high | stretched | Public funding marks support monitoring but not a buy at this price |
| If operating proof improves | buy | medium | medium | fairer | Audited financials, repeat deployments, and governance clarity would justify upgrading |
| If another raise arrives before proof | avoid | high | high | overheated | More dilution without KPI disclosure would argue for a lower risk budget |
Qualitative decision states are anchored to public disclosures through 2026-09-24; valuation stance is directional because no audited financials, ARR, or cap-table terms are public.
[CV008, CV009, CV011, CV013, CV014]Financing strength and platform depth support a premium story, but missing operating proof and governance disclosure keep the recommendation at track.
| Node / Connection | Node / from | To | Context |
|---|---|---|---|
| Node 1 | $1B+ capital base and $5.5B reported mark [n1] | ||
| Node 2 | Apollo, DeepMind, Mercedes-Benz, and GXO signals [n2] | ||
| Node 3 | Missing audited economics and cap-table terms [n3] | ||
| Node 4 | Need repeatable deployments and KPIs [n4] | ||
| Node 5 | Need public financing clarity [n5] | ||
| Node 6 | Track, not buy [n6] | ||
| Connection 1 | $1B+ capital base and $5.5B reported mark [n1] | Need repeatable deployments and KPIs [n4] | supports scale |
| Connection 2 | Apollo, DeepMind, Mercedes-Benz, and GXO signals [n2] | Need repeatable deployments and KPIs [n4] | supports platform premium |
| Connection 3 | Missing audited economics and cap-table terms [n3] | Need public financing clarity [n5] | constrains conviction |
| Connection 4 | Need public financing clarity [n5] | Need repeatable deployments and KPIs [n4] | keeps diligence open |
| Connection 5 | Need repeatable deployments and KPIs [n4] | Track, not buy [n6] | leads to current call |
Qualitative flow chart only; it compresses the valuation logic into a decision path rather than a numeric model.
[CV003, CV006, CV007, CV008, CV009, CV011, CV014]8.2 What supports the premium and what does not
The strongest thesis is that Apptronik is not a one-dimensional robotics prototype. The company points to a decade of work out of UT Austin, 15 robotic systems before Apollo, a DeepMind partnership, and named commercial relationships that suggest a serious platform effort rather than a science project. The anti-thesis is that these signals still stop short of hard operating proof. The company page describes fleet-level deployment, but the current public narrative still leans on manufacturing scale, future use cases, and strategic validation instead of customer-by-customer deployment economics. That leaves the valuation dependent on whether the next phase produces repeatable robots-in-operation metrics instead of more headline financing. [CV002, CV003, CV005, CV006, CV007, CV010, CV012, CV014]
| Argument | What would change the view |
|---|---|
| Apptronik has enough technical depth to deserve a platform premium, but the market still has to see repeatable deployments | If Apollo produces recurring deployments and customer expansion, the premium becomes more defensible |
| Named partnerships and commercial relationships reduce the chance that this is just a demo story | If those relationships remain non-binding pilots or do not convert into repeat business, the thesis weakens |
| The company has already accumulated a large capital base, which helps execution | If the next financing is mostly rescue capital or comes at weaker terms, dilution risk rises |
| The public record still lacks audited economics and cap-table detail | If management discloses those terms along with unit-level metrics, the valuation gap narrows |
Each row pairs a thesis or anti-thesis with the single fact that would most likely move the recommendation.
[CV002, CV003, CV005, CV006, CV007, CV008, CV009, CV011, CV012, CV013, CV014]8.3 Why the valuation stays stretched
The downside case is not that Apptronik lacks technical credibility; it is that the public evidence still does not clear the bar for a premium mark. StartEngine's retail offering language explicitly warns that valuation is not static and that investors should not assume the stake will rise in value. New Market Pitch goes further, arguing that the company is priced into execution mode and needs hard proof such as customer expansion, robot counts, hours worked, and failure rates. That framing matters because the company has already raised enough capital to make dilution a real issue, while the cap-table and preference stack remain undisclosed. If the next round arrives before clear operating proof, the premium can compress quickly. [CV008, CV009, CV011, CV013, CV014]
8.4 Scenario frame and diligence gate
The valuation logic is best thought of as a scenario problem rather than a point estimate. In the bull case, Apptronik starts producing repeatable deployments, discloses stronger operating KPIs, and earns a rerating on the back of clearer economics and lower perceived execution risk. In the base case, the company keeps attracting capital and partner attention, but the public evidence remains too thin to justify more than a monitoring stance. In the bear case, deployment proof lags, additional capital is required, and the market reprices the company as a promising but still pre-commercial robotics platform. The diligence gate is straightforward: I would want audited financials, a current revenue bridge, a cap-table and preference schedule, and customer-level deployment metrics before moving this from track to buy. [CV008, CV009, CV010, CV011, CV012, CV013, CV014]
| Case | Assumptions | Valuation / return logic | Key risks | Probability signal |
|---|---|---|---|---|
| Bull | Repeat deployments appear in public KPIs and the company shows cleaner operating disclosure | The mark can hold a premium range around 6.5B-8.0B or higher if growth converts into repeat revenue | Hardware reliability and manufacturing ramp remain the main failure modes | Low-to-moderate because the proof burden is still high |
| Base | Apptronik keeps raising capital and winning attention but disclosure stays thin | The current 5.0B-6.0B zone looks plausible as a holding pattern rather than a discount | Slow pilot conversion and future dilution | Highest because the public evidence mostly supports patience |
| Bear | Deployment proof stalls and the company must raise again before hard KPI disclosure | Down-round risk pushes the valuation toward 3.0B-4.0B or lower | Preference overhang, customer concentration, and commercialization failure | Meaningful if repeat usage does not materialize |
Scenario values are qualitative ranges inferred from public financing marks and operating evidence; they are not a discounted-cash-flow model or an assertion of formal fair value.
[CV008, CV009, CV011, CV012, CV013, CV014]Disclaimer
This report is a public-evidence diligence snapshot, not investment advice. Important financial, legal, technical, and contractual facts remain non-public and should be verified directly with management and primary documents before any investment decision.
Evidence index
| ID | Statement | Confidence | Sources |
|---|---|---|---|
| CO001 | Apptronik describes Apollo as a platform that combines advanced hardware, embodied AI, and fleet-level tools. | Medium | SO008 |
| CO002 | Apptronik says Apollo is intended for manufacturing, warehouse, and retail workflows. | Medium | SO008 |
| CO003 | Apptronik says it was founded in 2016 at the University of Texas at Austin Human Centered Robotics Lab and had over 150 employees in the February 2025 release. | High | SO007, SO003 |
| CO004 | Apptronik says it had developed 15 robotic systems before Apollo, including NASA Valkyrie. | Medium | SO007 |
| CO005 | Apptronik announced a $350 million Series A in February 2025 led by B Capital and Capital Factory with Google participation. | High | SO007, SO002 |
| CO006 | Apptronik’s official February 2025 release says it has commercial agreements with Mercedes-Benz and GXO and that the capital was intended to meet customer demand. | Medium | SO007 |
| CO007 | Apptronik announced a $520 million Series A-X extension on February 11, 2026, taking the Series A above $935 million and total capital raised to nearly $1 billion. | Medium | SO001 |
| CO008 | The February 2026 release says the new capital will ramp production, expand pilot and commercial deployments, and support a new robot slated to debut in 2026. | Medium | SO001 |
| CO009 | StartEngine identifies Jeff Cardenas as co-founder and CEO and Nick Paine as co-founder and CTO. | Medium | SO003 |
| CO010 | StartEngine identifies Kay Sheils as CFO and Animesh Garg as CSO. | Medium | SO003 |
| CO011 | StartEngine lists Apptronik at 195 employees and $431.38 million total raised. | Medium | SO003 |
| CO012 | IPO CLUB’s June 2026 page lists Apptronik as private, Austin-based, founded in 2016, led by Jeff Cardenas, valued at $5.5 billion, and backed by roughly $1 billion in cumulative funding. | Medium | SO006 |
| CO013 | The February 2025 release describes Gordon Daugherty as Apptronik’s first outside board director. | Medium | SO007 |
| CO014 | RoboZaps says Apollo has no public list price and is only available through enterprise pilots or quote-based engagements. | Medium | SO005 |
| CO015 | RoboZaps describes Apollo 2 as a prototype for scaled pilots and says Apollo 3 is the commercial product Apptronik is waiting to ship. | Medium | SO005 |
| CO016 | Apptronik’s newsroom lists March 2024 Mercedes-Benz, June 2024 GXO, and 2026 Robot Park / executive-hire milestones, showing the company’s public commercialization cadence. | Medium | SO002 |
| CM001 | Apptronik frames Apollo as a platform for scalable humanoid deployment in real operations, with both bipedal and wheeled mobility options. | High | SM001, SM002 |
| CM002 | Apptronik's public product pages center Apollo on manufacturing, warehouse, and retail workflows that reduce repetitive physical work. | High | SM001, SM002 |
| CM003 | Apptronik says it is scaling Apollo manufacturing to meet customer demand in industrial verticals such as automotive, logistics, and manufacturing. | High | SM001, SM002 |
| CM004 | Apptronik says it was founded in 2016 at the University of Texas at Austin's Human Centered Robotics Lab and had developed 15 robotic systems. | High | SM002, SM005 |
| CM005 | Public sources put Apptronik's near-term focus on factories and warehouses first, with retail back-of-house as a secondary adjacency and consumer/home use cases downstream. | High | SM001, SM003, SM005 |
| CM006 | Apptronik's public evidence is still partner-heavy and metric-light, so the company has not yet published operating metrics comparable to some humanoid peers. | Medium | SM003 |
| CM007 | Two independent market-data pages place Apptronik's private-market valuation around $5.3 billion and its headcount around 300 employees. | Medium | SM005, SM006 |
| CM008 | Forge Global shows a $36.97 Apptronik share price and a $5.3 billion Forge Price valuation as of 2026-09-23. | Medium | SM006 |
| CM009 | Secondary market pages cite Goldman Sachs projecting a $38 billion humanoid-robot market by 2035 and Morgan Stanley projecting a $5 trillion robotics market by 2050. | Medium | SM004, SM007 |
| CM010 | The Information page title says Apptronik was in talks to raise funding at a $5 billion valuation. | Medium | SM008 |
| CM011 | New Market Pitch describes Apptronik as being in the proof phase rather than the promise phase and names Mercedes-Benz, GXO Logistics, and Jabil as industrial exposure. | Medium | SM003 |
| CM012 | New Market Pitch says Apptronik still lacks public operating metrics like the throughput numbers or deployment counts peers have published. | Medium | SM003 |
| CM013 | Apptronik's public use-case language points to repeatable industrial tasks such as material handling, line-side work, picking, packing, moving goods, and back-of-house retail work. | High | SM001, SM002 |
| CM014 | Apptronik says future applications include healthcare, eldercare, and the home, but those uses are later-stage adjacencies rather than the current industrial core. | Medium | SM001, SM005 |
| CP001 | Apptronik positions Apollo as a general-purpose humanoid for manufacturing, logistics, and other industrial work, with bipedal and wheeled deployment options. | High | SP001, SP003 |
| CP002 | Apptronik's February 2025 announcement said it closed a $350 million Series A and had only $28 million of previous funding. | Medium | SP002, SP009 |
| CP003 | Apptronik's public product focus is factories and warehouses first, with retail and other future uses positioned as later extensions. | High | SP001, SP003 |
| CP004 | Apollo has no public list price and no self-serve purchase path in the assigned pool sources; the public channel is quote-based enterprise engagement or pilot work. | Medium | SP007, SP005 |
| CP005 | Independent coverage describes Apptronik as being in the proof phase, with partner-heavy and metric-light public evidence. | Medium | SP004 |
| CP006 | Figure and Agility look stronger on public operating proof than Apptronik because the pool sources say Figure has published BMW deployment numbers and Agility has published GXO tote milestones. | Medium | SP004 |
| CP007 | The pool sources place Apptronik in a pilot-only position, Tesla Optimus without mass production, Figure 03 without a sales channel, Digit as a RaaS product, and Atlas with committed production slots. | Medium | SP006, SP007 |
| CP008 | StartEngine's market snapshot places Apptronik at 195 employees and $431.38 million raised as of March 2025, which is larger than a lab-only team but still far from a scaled hardware platform. | Medium | SP005 |
| CP009 | Apptronik's Jabil relationship is strategically important because the assigned sources describe Jabil as both a production partner and a validation environment for Apollo. | Medium | SP003, SP004, SP002 |
| CP010 | Google DeepMind gives Apptronik real technical depth, but the assigned sources do not show that partnership converting into a durable customer moat or public field KPI advantage yet. | Medium | SP001, SP003, SP004 |
| CP011 | The effective substitute set includes status quo manual labor and internal or fixed automation, because Apptronik's target jobs are repetitive industrial tasks that can still be solved without a general-purpose humanoid. | Medium | SP001, SP003, SP006 |
| CP012 | Robotics competition is intense and new entrants remain credible because the assigned sources frame the category as capital-heavy, fast-moving, and still far from settled. | Medium | SP006, SP004 |
| CP013 | The public evidence still favors peers with explicit operating numbers over peers with only partnerships, so Apptronik's competitive edge remains more strategic than measurable. | Medium | SP004, SP006 |
| CP014 | The Information page in the pool is effectively gated behind subscription access, illustrating that some high-signal category coverage is not fully transparent in public form. | Medium | SP008 |
| CI001 | Apptronik publicly frames Apollo as an industrial robot platform for manufacturing, warehouse, and retail workflows, with fleet-level tools rather than a one-off demo. | High | SI001, SI002 |
| CI002 | Apptronik announced a $350 million Series A in February 2025 and said the round totaled $403 million after the March 2025 extension. | High | SI002, SI008 |
| CI003 | Public market-data sources place Apptronik's valuation in a narrow band around $5.3 billion to $5.5 billion, but they disagree materially on the total capital raised. | Medium | SI003, SI004, SI006 |
| CI004 | Forge says Apptronik has not released revenue data, and its IPO or market-value path still depends on commercial deployment rather than disclosed operating scale. | Medium | SI004 |
| CI005 | Forge cites an implied Apollo price of about $80,000 per unit, but that figure is a secondary estimate rather than a public company list price. | Medium | SI004 |
| CI006 | Tracxn lists Apptronik at $956 million of total funding, a $5.5 billion valuation, and 504 employees as of late August 2026. | Medium | SI003 |
| CI007 | Apptronik's 2025 press release said the company had over 150 employees and was scaling manufacturing to meet orders across automotive, electronics manufacturing, 3PL, beverage bottling, and CPG. | High | SI002, SI001 |
| CI008 | StartEngine's 2026 offering page listed Apptronik at $25 per security and $431.38 million raised to date, but the company itself was not participating in the offering. | Medium | SI005, SI008 |
| CI009 | New Market Pitch described Apptronik as still in pilot phases with no public deployment KPIs, despite a reported $5.3 billion valuation and nearly $1 billion raised. | Medium | SI006 |
| CI010 | Apptronik's homepage says Apollo is designed for real operations with advanced hardware, embodied AI, and fleet-level tools, which implies monetization will depend on deployment scale and support rather than software-only usage. | High | SI001, SI002 |
| CI011 | The reviewed secondary sources still describe Apptronik as pre-commercial or pilot-heavy, so the public evidence for sustained operating revenue remains weak. | Medium | SI004, SI006, SI007, SI008 |
| CI012 | Across the reviewed sources, Apptronik does not publish audited revenue, gross margin, cash balance, or runway figures, so the company cannot yet be underwritten from public financial statements. | Medium | SI001, SI002, SI004, SI006 |
| CE001 | Apptronik positions Apollo as its flagship humanoid robot platform for manufacturing and logistics first, with future applications in healthcare, the home, and retail. | High | SE001, SE002, SE007 |
| CE002 | Apollo is presented as a modular humanoid platform with both bipedal and wheeled mobility options designed for human-centered spaces and workflows. | High | SE001, SE006 |
| CE003 | Apptronik says Apollo combines advanced hardware, embodied AI, and fleet-level tools and that the company is tackling safety, commercialization, and mass production. | High | SE001, SE007 |
| CE004 | The official product copy frames Apollo as a platform for manufacturing, warehouse, and retail use cases rather than a narrow single-task robot. | Medium | SE001 |
| CE005 | Apptronik's 2025 Series A announcement says Apollo is being scaled for customer demand across automotive, electronics manufacturing, third-party logistics, beverage bottling, and consumer packaged goods. | Medium | SE002 |
| CE006 | CNBC reports that Apollo units are being tested in factories and warehouses with Mercedes-Benz, GXO, and Jabil, and that designated areas use sensors and light curtains so Apollo pauses if a person crosses the boundary. | Medium | SE003 |
| CE007 | New Market Pitch says Apptronik is past the lab-story phase but still partner-heavy and metric-light, with no public Apollo scoreboard for uptime, throughput, intervention rate, or cost per task. | Medium | SE004 |
| CE008 | The Jabil relationship is the clearest production-path signal because the public narrative links Apollo validation with inspection, sorting, kitting, lineside delivery, fixture placement, and sub-assembly. | Medium | SE004, SE006 |
| CE009 | Google DeepMind and Gemini Robotics are presented as a technical advantage for Apollo, but the public record still does not show a durable field-performance or cost-per-task moat. | Medium | SE003, SE004, SE008 |
| CE010 | The human-motion-data job posting shows active work on motion capture, teleoperation, synthetic generation, kinematic retargeting, and whole-body reinforcement-learning pipelines for humanoid control. | Medium | SE007 |
| CE011 | Apptronik's recent hiring language points to product safety, simulation, manufacturing, services inventory, and hardware testing as deployment priorities. | Medium | SE007, SE004 |
| CE012 | Public sources still do not disclose Apollo's uptime, recovery, incident, certification, or compliance record, so the current trust and safety posture remains a diligence gap. | Medium | SE004, SE006, SE003 |
| CU001 | Apptronik positions Apollo for manufacturing, warehouse, and retail workflows and says the robot can use either bipedal or wheeled mobility. | High | SU001, SU004 |
| CU002 | Apptronik says Apollo is intended to support physically demanding human work and be deployed across real operations rather than as a pure lab demo. | High | SU001, SU002 |
| CU003 | Apptronik said its 2025 funding round would help it scale manufacturing to meet demand across automotive, electronics manufacturing, 3PL, beverage bottling, fulfillment, and consumer packaged goods. | High | SU002, SU004 |
| CU004 | Apptronik publicly linked Apollo to commercial relationships with Mercedes-Benz and GXO Logistics. | High | SU002, SU004 |
| CU005 | Recent 2026 coverage says Apptronik’s customer focus is factories and warehouses first, with recurring use cases including trailer unloading, case picking, palletization, machine tending, kitting, sorting, line-side delivery, and sub-assembly. | Medium | SU005, SU006 |
| CU006 | Public coverage describes Apptronik’s customer evidence as partner-heavy and metric-light, with no Apollo scoreboard comparable to the strongest public peer disclosures. | Medium | SU005, SU008 |
| CU007 | Recent coverage treats Jabil as a production-path signal for Apollo, which suggests Apptronik is trying to move from pilots toward repeatable manufacturing support. | Medium | SU005, SU008 |
| CU008 | Apptronik’s 2026 capital raise pushed reported funding to more than $935 million and reported valuation to more than $5 billion, increasing pressure to convert the customer narrative into hard operating proof. | Medium | SU003, SU006 |
| CU009 | The public named customer and partner set is concentrated around Mercedes-Benz, GXO Logistics, and Jabil rather than a broad disclosed base. | Medium | SU002, SU005, SU008 |
| CU010 | Apptronik does not publicly disclose NRR, GRR, churn, renewal cohorts, or customer-level retention metrics in the assigned evidence set. | Medium | SU001, SU005, SU006 |
| CU011 | The evidence supports an industrial beachhead in manufacturing and logistics rather than near-term consumer or home adoption. | Medium | SU001, SU002, SU003 |
| CU012 | The main concentration risk is that the publicly visible relationships are pilots, commercial agreements, or production collaborations rather than fully disclosed recurring deployments. | Medium | SU002, SU005, SU008 |
| CU013 | The assigned evidence set does not show a public customer complaint, failed pilot, or churn event tied to Apollo, only a lack of disclosed operating proof. | Medium | SU005, SU006, SU008 |
| CR001 | Apptronik's public site positions Apollo as a scalable humanoid deployment platform with bipedal and wheeled mobility options for manufacturing, warehouse, and retail use cases. | High | SR001, SR002 |
| CR002 | Apptronik's February 2025 press release says it raised $350 million, had over 150 employees, and was scaling manufacturing to meet demand across automotive, electronics, logistics, bottling, and CPG. | High | SR002, SR004 |
| CR003 | Forbes reported in June 2026 that Apptronik announced Robot Park, a 90,000-square-foot physical AI data factory, and described Apollo 2 as a prototype for scaled pilots and data collection while Apollo 3 is the product intended to scale to market. | High | SR003, SR008 |
| CR004 | Forbes said Apollo 2's wheeled configuration is designed to align with existing safety standards for industrial mobile robots, which reduces some regulatory friction versus a pure bipedal deployment. | High | SR003, SR008 |
| CR005 | The reviewed evidence still does not show Apptronik publishing Apollo throughput, uptime, intervention-rate, or cost-per-task metrics at the level of Figure or Agility. | Medium | SR006, SR008 |
| CR006 | StartEngine's offering page listed Apptronik at 195 employees and $431.38 million raised, while warning that the security is speculative, illiquid, and may lose the entire investment. | Medium | SR007 |
| CR007 | New Market Pitch said Apptronik had raised close to $1 billion, was reportedly around a $5 billion valuation, and now had to prove execution rather than remain in promising-pilot language. | Medium | SR006 |
| CR008 | Apptronik's IT Infrastructure Engineer posting required on-prem networking, server administration, backups, virtualization, security practices, and high-availability work, which signals a scaling internal infrastructure burden. | Medium | SR005 |
| CR009 | Anton Robots said Apollo 2 is better for strategic pilots and co-development, while Digit is better for deployment today, which implies Apptronik lags a peer on public commercial proof even if its modularity is attractive. | Medium | SR008 |
| CR010 | Yahoo's February 2025 article said Apptronik was scaling production, accelerating deployment, and aiming to fulfill growing orders across multiple industrial verticals. | Medium | SR004 |
| CR011 | Apptronik's official release said it would scale manufacturing to meet customer demand and named Mercedes-Benz, GXO, and Google DeepMind as part of the public partner stack. | High | SR002, SR003 |
| CR012 | Forbes said Apptronik's Robot Park data-collection workflows extend across Google DeepMind, Mercedes-Benz, and GXO, and that Apollo 2 is being used for scaled pilots and data collection while Apollo 3 is expected to scale to market. | High | SR003, SR008 |
| CR013 | The public evidence remains partner-heavy because the named industrial exposures are Mercedes-Benz, GXO, and Jabil, with Google DeepMind acting as a strategic AI dependency rather than a closed Apptronik-only moat. | Medium | SR002, SR003, SR008 |
| CR014 | The reviewed safety sources point to controlled deployment mechanisms such as wheeled mobility, configurable safety zones, and engineered workcells or barriers rather than unrestricted humanoid operation. | Medium | SR003, SR008 |
| CR015 | The reviewed sources do not confirm any active litigation, enforcement action, or recall exposure for Apptronik, so legal-regulatory status remains unverified. | Low | |
| CV001 | Apptronik closed a $350 million Series A in February 2025 with B Capital, Capital Factory, and Google participation. | Medium | SV001 |
| CV002 | The same 2025 press release said Apptronik had over 150 employees at the time. | Medium | SV001 |
| CV003 | The 2025 press release said Apptronik had developed 15 robotic systems, including NASA Valkyrie, before Apollo. | Medium | SV001 |
| CV004 | Apptronik disclosed a 2025 financing sequence that moved from a $350 million Series A to an oversubscribed $403 million round with an extra $53 million. | High | SV001, SV002 |
| CV005 | The March 2025 release said the capital would scale manufacturing and meet customer demand across automotive, electronics manufacturing, 3PL, beverage bottling, fulfillment, and CPG. | Medium | SV002 |
| CV006 | The March 2025 release said Apptronik had a strategic partnership with the Google DeepMind robotics team and commercial agreements with Mercedes-Benz and GXO Logistics. | Medium | SV001, SV002 |
| CV007 | Apptronik's home page says it combines advanced hardware, embodied AI, and fleet-level tools for robots that can be managed, improved, and deployed across real operations. | Medium | SV003 |
| CV008 | Sacra says Apptronik closed a $520 million Series A extension on February 11, 2026, taking total Series A financing above $935 million and total capital above $1 billion. | Medium | SV004 |
| CV009 | Yahoo Finance and Crunchbase both reported a $520 million 2026 extension and a valuation above $5.5 billion. | High | SV005, SV006 |
| CV010 | Crunchbase says the $520 million extension was intended to boost production of Apollo. | Medium | SV006 |
| CV011 | StartEngine's offering page warns investors not to assume the investment will increase in value because valuation is not static and can fluctuate. | Medium | SV007 |
| CV012 | New Market Pitch says Apptronik is focused on factories and warehouses first, with use cases such as trailer unloading, case picking, palletization, machine tending, kitting, sorting, and sub-assembly. | Medium | SV008 |
| CV013 | New Market Pitch says the valuation is high because the company has raised close to $1 billion and is reportedly around a $5 billion valuation. | Medium | SV008 |
| CV014 | New Market Pitch says Apptronik is priced into execution mode and needs hard operating proof such as customer expansion, robot counts, hours worked, failure rates, or cost-per-task improvements. | Medium | SV008 |
| ID | Publisher | Title | Quote |
|---|---|---|---|
| SO001 | Apptronik | Apptronik Closes Over $935 Million Series A with New $520 Million Extension Round | bringing Apptronik’s total Series A to more than $935 million and total capital raised to nearly $1 billion |
| SO002 | Apptronik | Apptronik - Press Releases | March 18, 2024 ... Apptronik and Mercedes-Benz Enter Commercial Agreement |
| SO003 | StartEngine | Invest in Series Apptronik (2026 Round) | StartEngine | Jeff Cardenas | Co-Founder, CEO |
| SO004 | TSG Invest | Apptronik Stock: $5.5B Valuation — Is It a Buy? | meaningful revenue generation is still 1-2 years away according to company leadership |
| SO005 | RoboZaps | Apptronik Apollo Review 2026: Price, Apollo 2 & Deployments | Apptronik has never published a price for Apollo |
| SO006 | IPO CLUB | Apptronik Stock Price, Valuation & IPO Outlook 2026 - IPO CLUB | Valuation: $5.5B |
| SO007 | Apptronik | Apptronik Raises $350 Million in Series A Funding | AUSTIN, TEXAS, February 13, 2025 – Today, Apptronik ... announced the successful closing of a $350 million Series A funding round |
| SO008 | Apptronik | Apptronik - Home | Apptronik brings together advanced hardware, embodied AI, and fleet-level tools |
| SM001 | Apptronik | Apptronik - Home | Apollo is more than a robot - it’s a platform for scalable humanoid deployment. |
| SM002 | Apptronik | Apptronik Raises $350 Million in Series A Funding | Meet skyrocketing customer demand. Apptronik is scaling manufacturing of Apollo units to fulfill growing orders across priority verticals. |
| SM003 | New Market Pitch | How's Apptronik doing these days? | Apptronik looks like a serious top-tier humanoid robotics contender, but it is now in the proof phase rather than the promise phase. |
| SM004 | StartEngine | Invest in Series Apptronik (2026 Round) | StartEngine | Apollo's Potential in a $38B Market (By 2035) |
| SM005 | Silicon Valley Invest Club | Apptronik — Company profile | The company’s valuation has reached approximately $5.3 billion—roughly 3x the initial Series A valuation. |
| SM006 | Forge Global | Buy and Sell Apptronik Stock, $36.97 Forge Price - Forge Global | Forge Price $36.97 |
| SM007 | TSG Invest | Apptronik Stock: $5.5B Valuation — Is It a Buy? | TSG Invest | The humanoid robotics market presents extraordinary growth potential, with Goldman Sachs projecting the market to reach $38 billion by 2035 and Morgan Stanley estimating it could reach $5 trillion by 2050. |
| SM008 | The Information | Google-Backed Apptronik in Talks to Raise Funding at $5 Billion Valuation | Google-Backed Apptronik in Talks to Raise Funding at $5 Billion Valuation |
| SP001 | Apptronik | Apptronik - Home | Apptronik brings together advanced hardware, embodied AI, and fleet-level tools to support robots that can be managed, improved, and deployed across real operations. |
| SP002 | Apptronik | Apptronik Raises $350 Million in Series A Funding | Today, Apptronik, the AI-powered humanoid robotics company, announced the successful closing of a $350 million Series A funding round. |
| SP003 | KÜRE Encyclopedia | Apptronik | KÜRE Encyclopedia | Apollo is a general-purpose humanoid robot ... designed to support a wide range of future industrial applications. |
| SP004 | New Market Pitch | How's Apptronik doing these days? | The company is no longer just a lab story. The gap is that Apptronik’s public evidence is still partner-heavy and metric-light. |
| SP005 | StartEngine | Invest in Series Apptronik (2026 Round) | StartEngine | Total Raised to Date: $431.38M |
| SP006 | TSG Invest | “The Robots are coming“ | The company faces significant challenges including intense competition from well-funded rivals like Tesla and Figure AI. |
| SP007 | RoboZaps | Apptronik Apollo Review 2026: Price, Apollo 2 & Deployments - Blog | Apptronik has never published a price for Apollo, and you cannot buy one today. |
| SP008 | The Information | Google-Backed Apptronik in Talks to Raise Funding at $5 Billion Valuation | |
| SP009 | Pulse 2.0 | Apptronik: $350 Million Raised For Scaling AI-Based Humanoid Robots | Apptronik is scaling manufacturing of Apollo units to fulfill growing orders across priority verticals. |
| SI001 | Apptronik | Apptronik - Home | Apptronik brings together advanced hardware, embodied AI, and fleet-level tools to support robots that can be managed, improved, and deployed across real operations. |
| SI002 | Apptronik | Apptronik Raises $350 Million in Series A Funding | Apptronik announced the successful closing of a $350 million Series A funding round... Apptronik is scaling manufacturing of Apollo units to fulfill growing orders. |
| SI003 | Tracxn | Apptronik | Apptronik has raised $956M in funding... with a current valuation of $5.5B. |
| SI004 | Forge | Insights: How To Invest In Apptronik Stock Pre-IPO | The company has not released revenue data... investors should not assume that a listing will occur on any particular timeline. |
| SI005 | StartEngine | Invest in Series Apptronik (2026 Round) | StartEngine | Price Per Security: $25.00 |
| SI006 | New Market Pitch | How's Apptronik doing these days? | The valuation is high, but the bigger issue is that the company has now priced itself into execution mode. |
| SI007 | The Business Journals | What startup founders should consider from day one | Corporate giants are throwing cash at a startup that's already among the leaders in the global robotics race. |
| SI008 | StartEngine | Invest in Series Apptronik (2026 Round) | StartEngine | Apptronik is looking to capitalize on a pivotal moment for humanoid robots... as well as $400M+ in VC funding. |
| SE001 | Apptronik | Apptronik - Home | Apollo is designed to bring AI into the physical world. |
| SE002 | Apptronik | Apptronik Raises $350 Million in Series A Funding | Apptronik is scaling manufacturing of Apollo units to fulfill growing orders across priority verticals. |
| SE003 | CNBC | Apptronik raises $520 million at $5 billion valuation for Apollo robot | The designated areas are defined by external sensors and so-called light curtains. |
| SE004 | New Market Pitch | How's Apptronik doing these days? - New Market Pitch | Apptronik's public evidence is still partner-heavy and metric-light. |
| SE005 | StartEngine | Invest in Series Apptronik (2026 Round) | StartEngine | Apollo's modular hardware, AI-driven autonomy. |
| SE006 | TSG Invest | Apptronik Stock: $5.5B Valuation — Is It a Buy? | TSG Invest | Apollo is a 5'8" tall robot that can lift 55 pounds. |
| SE007 | Vaia Talents | Software Engineer - Human Motion Data in Austin at Apptronik | Apply now! – Vaia – Talents | Design and build motion data pipelines for cutting-edge humanoid robots. |
| SE008 | The Information | Google-Backed Apptronik in Talks to Raise Funding at $5 Billion Valuation | Google-Backed Apptronik in Talks to Raise Funding at $5 Billion Valuation. |
| SU001 | Apptronik | Apptronik - Home | Apollo for Manufacturing |
| SU002 | Apptronik | Apptronik Raises $350 Million in Series A Funding | Meet skyrocketing customer demand. |
| SU003 | Trending Topics | Apptronik raises $520 million for humanoid robots, valuation climbs to around $5 billion | Apptronik has now raised nearly a billion dollars. |
| SU004 | Robotics247 | Apptronik closes $350M funding from Google, others to scale AI-powered humanoid production | Meet customer demand. |
| SU005 | New Market Pitch | How's Apptronik doing these days? | The gap is that Apptronik’s public evidence is still partner-heavy and metric-light. |
| SU006 | StartEngine | Invest in Series Apptronik (2026 Round) | StartEngine | The company’s progress has attracted partnerships with Google, Mercedes-Benz, and NASA. |
| SU007 | Rapid Innovation | Apptronik's Humanoid Robot Revolution 2025 | Industry | Apptronik stands out in this field due to its innovative approach and commitment to research and development. |
| SU008 | The Robot Report | Apptronik Archives - The Robot Report | Apptronik unveils Apollo 2 and a flagship data collection and training facility |
| SR001 | Apptronik | Apptronik - Home | Apptronik brings together advanced hardware, embodied AI, and fleet-level tools to support robots that can be managed, improved, and deployed across real operations. |
| SR002 | Apptronik | Apptronik Raises $350 Million to Scale Production of AI-Powered Humanoid Robots and Meet Significant Customer Demand | Apptronik announced the successful closing of a $350 million Series A funding round. |
| SR003 | Forbes | Apptronik Announces Robot Park, A 90,000 Square Foot Humanoid Data Factory, Teases New Robot | Apollo 2 as really a prototype for scaled pilots and data collection, and the next version of Apollo will really be the product that will scale to the market. |
| SR004 | Yahoo News | Apptronik to scale up production of humanoid robots that can work alongside humans | Apptronik aims to scale up operations, accelerate innovation, and grow its world-class team to meet the demand for next-generation, AI-powered humanoid robots. |
| SR005 | Capital Factory | IT Infrastructure Engineer @ Apptronik | Implement security best practices to protect against cyber threats. |
| SR006 | New Market Pitch | How's Apptronik doing these days? | The gap is that Apptronik’s public evidence is still partner-heavy and metric-light. |
| SR007 | StartEngine | Invest in Series Apptronik (2026 Round) | StartEngine | This investment is speculative, illiquid, and involves a high degree of risk, including the possible loss of your entire investment. |
| SR008 | Anton Robots | Apptronik Apollo 2 vs Agility Digit (2026): Full Comparison | Agility Digit is the better choice for organisations that need the strongest evidence of commercial deployment today. |
| SV001 | Apptronik | Apptronik Raises $350 Million in Series A Funding | Today, Apptronik, the AI-powered humanoid robotics company, announced the successful closing of a $350 million Series A funding round. |
| SV002 | Apptronik | Apptronik Closes Additional Series A Funding | Apptronik announced the successful close of an oversubscribed $403M Series A funding round, adding an extra $53 million to the previously... |
| SV003 | Apptronik | Apptronik - Home | Apptronik brings together advanced hardware, embodied AI, and fleet-level tools to support robots that can be managed, improved, and deployed across real ... |
| SV004 | Sacra | Apptronik valuation, funding & news | Sacra | On February 11, 2026, Apptronik closed a $520M Series A extension, bringing total Series A financing to more than $935M and total capital ... |
| SV005 | Yahoo Finance | Apptronik Raises $520 Million at $5.5 Billion Valuation | Apptronik has secured roughly $520 million in a new funding extension that values the company at more than $5.5 billion... |
| SV006 | Crunchbase News | Amid Record Robotics Funding, Apptronik Raises $520M Series A Extension To Boost Production Of Humanoid Robot Apollo | AI-powered robotics company Apptronik announced Wednesday that it has raised $520 million in an extension of its $415 million Series A raise... |
| SV007 | StartEngine | Invest in Series Apptronik (2026 Round) | StartEngine | investors should not assume that investments in Series Apptronik will increase in value. Valuation is not static and can fluctuate based on various factors. |
| SV008 | New Market Pitch | How's Apptronik doing these days? | The valuation is high because the company has raised close to $1 billion and is reportedly around a $5 billion valuation. |