SHAREBOT

1.1 Identity and operating model

SHAREBOT is identified in the retained reporting as Qingtian Rent and as a Chinese robot-leasing platform. The available evidence describes a transition from rental activity toward a broader Robotics-as-a-Service model, with commercial deployment across service and industrial settings rather than a single robot type. Reporting on the surrounding ecosystem indicates that leasing addresses a practical adoption problem: customers may prefer short-term access while robot products continue to iterate. That context supports the business-model direction, but it does not establish SHAREBOT's own utilization, gross margin, contract duration, renewal, or customer concentration. The company profile should therefore distinguish the reported product direction from an independently verified operating scale.[CO001, CO002, CO003, CO004]

1.2 Financing, valuation, and disclosure

A RobotToday briefing, explicitly crediting an original PanDaily report, says SHAREBOT completed Series A and A+ rounds, raised hundreds of millions of RMB, and was valued at 7 billion RMB. Crunchbase separately lists Botshare, described as a robot leasing and rental platform based in Pudong, as a new unicorn valued at $1 billion; the retained text does not independently prove that Botshare and SHAREBOT are the same legal entity, so the linkage remains a diligence question rather than a consolidated metric. The public record retained here does not disclose audited revenue, cash burn, runway, gross margin, total raised, or a verified employee count. These gaps materially limit confidence in valuation and financing conclusions.[CO005, CO006, CO007, CO008, CO009]

1.3 Milestones, leadership, and open diligence

The evidence records a sequence from robot rental toward RaaS, a reported 2026 financing milestone, and a September 2026 ecosystem event associated with seven commercial RaaS products in the assigned search result. It also places the company within a Chinese robotics market where policy and deployment are expanding, while independent reporting cautions that many humanoid capabilities remain demonstrators or pilots. The retained source set does not identify founders, named executives, board members, or material leadership changes with sufficient corroboration. Governance, key-person dependence, related-party controls, safety audits, and legal or regulatory history therefore remain open diligence items rather than established negative findings.[CO010, CO011, CO012, CO013]

1.4 Exhibits

2.1 Market boundary and demand context

The relevant market is robot access delivered as a service: customers rent or subscribe to humanoid, service, and other robots for defined deployments, with the provider coordinating availability, delivery, setup, maintenance, and recovery. This boundary includes event, hospitality, retail, healthcare, logistics, property, and emerging industrial use cases when the buyer pays for access or an operated outcome rather than purchasing the asset outright. It excludes robot manufacturing revenue, one-time equipment sales, general industrial automation capex, and financing that does not include operating service. The boundary matters because broad robotics statistics describe hardware deployment and technology investment, while a leasing platform monetizes utilization, service density, and workflow reliability. The evidence indicates a demand bridge from demonstrations and short events toward recurring commercial operations, but does not establish SHAREBOT's recurring revenue, utilization, or retention.[CM001, CM002, CM003]

2.2 Multiple sizing lenses, not a single TAM

Available sizing is directional and uses different populations, geographies, and definitions. Market Research Future estimates the Asia-Pacific robotics market at USD 37.53 billion in 2024 and USD 42.33 billion in 2025, with a projected 12.8% CAGR through 2035; that is a broad robotics market, not RaaS revenue. IFR reports that China had an operational stock of around two million industrial robots and represented 54% of annual global installations in the World Robotics 2025 period. Statista's account of World Robotics 2026 reports 354,000 installations in China during 2025, equal to 59% of global installations. These lenses support a large underlying installed-base and adoption opportunity, but they cannot be arithmetically converted into SHAREBOT's SAM or SOM without rental penetration, service pricing, utilization, geography, and asset-mix assumptions. The most defensible current sizing conclusion is an evidence-constrained opportunity with a broad robotics ceiling and an unquantified serviceable slice.[CM005, CM006, CM007, CM008, CM009]

2.3 Buyers, adoption path, and constraints

Public evidence identifies event, retail, hospitality, property, healthcare, logistics, and light-industrial settings, but it does not name the contracting party or budget owner for SHAREBOT deployments. Sohu reports that short activity duration can make rental more attractive than purchasing, while also describing delivery, setup, repair, insurance, recovery, and cross-city dispatch as part of the operating burden. China policy and manufacturing scale are tailwinds: IFR says robotics is central to the 2026–2030 industrial strategy, while Global Times reports planned deployments and commercialization efforts. Constraints are equally material: IFR says humanoid capabilities in real production remain limited to demonstrators or pilots and that industrial robots are generally faster and more reliable for specialized tasks. Falling daily rental prices reported by Sohu increase trial affordability but compress platform spread, making service execution and asset utilization central to valuation. Specific buyer and payer roles in the table are therefore marked as inferred or undisclosed rather than presented as observed facts.[CM010, CM011, CM012, CM013, CM014]

2.4 What must be proven before sizing can support valuation

The evidence supports market pull, but not a company-specific adoption or valuation conclusion. The next diligence pass should reconcile SHAREBOT's claimed fleet availability, city coverage, fulfillment standard, and funding profile with signed customer contracts, repeat-booking cohorts, utilization by robot type, realized price per deployed day, repair and logistics cost, insurance losses, and contribution margin. It should also separate event rentals from recurring site operations and test whether each segment has a clear budget owner. Public market forecasts should be retained as context rather than treated as company revenue proxies. A defensible SOM requires a stated service geography, eligible fleet capacity, achievable utilization, price realization, and a penetration assumption supported by customer evidence; none of those company-specific inputs is sufficiently public in this pool.[CM015, CM016, CM017]

2.5 Exhibits

3.1 Landscape and direct alternatives

SHAREBOT's direct competitive set is a platform layer that aggregates robot manufacturers, service providers, and customer demand. SHAREBOT says it has moved from display, entertainment, events, and marketing toward industrial manufacturing, campus operations, warehouse logistics, and commercial services, and reports a fleet assembled from multiple brands. Preqin describes the same model as robot equipment leasing, service coordination, and digital platform usage for B2B and B2C contracts. That creates a direct comparison with Qingtian Rent, Wanjiyi Rental, and JD.com's self-operated rental service, not only with robot OEMs. Yicai attributed Qingtian Rent to AgiBot, while Pandaily identified SHAREBOT with the same name. The platform was reported as operating in 50 cities with more than 600 service providers and over 1,000 robots, while SHAREBOT's reporting cites deployment in more than 50 cities and over 1 million cumulative operating hours. These figures are issuer- or media-reported and are not a like-for-like measure of active utilization.[CP001, CP002, CP003, CP004, CP005, CP016]

3.2 Buyer choice, capability, and distribution

Buyers can solve the same job through several routes: a multi-brand rental marketplace, a manufacturer-led or OEM-linked platform, a large commerce channel, or direct purchase and internal operation. SHAREBOT's cited capabilities include partner SaaS, a global app, intelligent task dispatch, a skills store, robot selection, customized scenario solutions, scheduling, and maintenance support. Wanjiyi presents a similar ecosystem proposition, combining AI matching, standardized operation and maintenance, and an alliance of manufacturers, solution providers, finance, insurance, parks, and end users. JD.com has distribution power and a lower-friction rental offer through JD MALL, while Qingtian Rent emphasizes scenario packages and an expanding provider network. The evidence does not disclose comparable contract terms, uptime, take rates, renewal, or service-level performance, so the matrix marks those cells unknown rather than inferring a winner.[CP004, CP006, CP007, CP008, CP009, CP010, CP016]

3.3 Pricing pressure and moat durability

Price is a visible competitive pressure. Independent coverage reports that robot rental prices fell from roughly CNY10,000 per day to just over CNY100 for some offerings, while another report gives mainstream rates of roughly CNY3,000-CNY5,000 and records a Qingtian Rent package as high as CNY99,800 per day. These are different models, scenarios, and periods, so they should not be treated as one price curve. The same Yicai report identifies unstable pricing, seasonal demand, and incompatible interfaces as sector challenges. SHAREBOT's multi-brand scheduling and service network could reduce customer search and coordination costs, but those advantages may be copied by commerce platforms, OEMs, and ecosystem alliances. The strongest adverse conclusion is therefore not that SHAREBOT lacks a product; it is that commoditization and channel disintermediation could limit pricing power before switching costs and repeat utilization are demonstrated.[CP011, CP012, CP013, CP014, CP015]

3.4 Exhibits

4.1 Revenue model and monetization

SHAREBOT's public model is a multi-sided robot-rental and service platform rather than a disclosed subscription business. The platform connects robot manufacturers, service partners, content or solution providers, and customers, with booking, dispatch, delivery, and on-site support forming the commercial workflow. Public reporting places early demand in events, exhibitions, retail, tourism, and other short-duration deployments, while later financing communications emphasize industrial manufacturing, park operations, warehousing, logistics, and commercial services. This is a plausible path from one-off rentals toward recurring operational contracts, but the available sources do not disclose revenue by stream, contract duration, renewal, take rate, or realized gross margin. List or quoted daily prices should therefore be treated as market observations, not SHAREBOT revenue.[CI001, CI002, CI003, CI004]

4.2 Unit economics and cost drivers

The economics appear operationally intensive. A robot deployment may require logistics, configuration, choreography or task preparation, technical support, maintenance, insurance, and recovery after damage or downtime. Public reporting describes a market in which daily rental prices have fallen sharply from earlier peaks, including low-priced basic robots and materially higher prices for advanced models or technician-supported packages. Falling prices can widen trial access, but they also compress the revenue available to cover asset depreciation, idle time, repairs, field labor, and partner economics. No source in this assigned pool provides SHAREBOT's CAC, payback, contribution margin, utilization, service cost per order, churn, or customer concentration. Those missing fields prevent a conventional SaaS-style underwriting case.[CI005, CI006, CI007, CI008]

4.3 Capital adequacy and financial verdict

Public financing coverage indicates substantial investor support and a stated use of proceeds: building the RaaS system, expanding into industrial and other real-world scenarios, and improving standardized fulfillment, asset, dispatch, and supply-chain capabilities. That capital is not equivalent to cash available today, and the sources do not disclose cash on hand, burn, runway, debt, capex commitments, working capital, or the timing of the next financing trigger. The operating transition itself may require more field infrastructure and service capacity before higher-frequency contracts are proven. The financial verdict is therefore conditional: financing access appears supportive, but revenue quality, margin path, and capital sufficiency remain unverified until management supplies cohort-level operating and cash data.[CI009, CI010, CI011, CI012, CI013, CI014]

4.4 Exhibits

5.1 Product and customer workflow

SHAREBOT's disclosed product is a robot-leasing service rather than a single robot model. Public descriptions place it between hardware suppliers and customers that need temporary or recurring robot deployments for events, retail, service operations, education, tourism, and light industry. The platform manages more than 4,000 robots across more than 100 cities according to a company-data report, while an earlier launch account described a smaller fleet and provider network; these are time- and scope-dependent disclosures rather than a reconciled installed-base series. The operating workflow appears to include selection, delivery, local operation or training, maintenance, and asset disposition. That workflow can lower upfront acquisition barriers, but the public record does not establish utilization, uptime, repeat deployment, or customer-level outcomes. The product therefore has a credible access proposition, with execution quality dependent on standardization across suppliers and local service providers.[CE001, CE002, CE003, CE004]

5.2 Operating architecture and maturity

The evidence supports an operating architecture with four practical layers: a hardware and asset layer, a platform and transaction layer, a local deployment and after-sales layer, and a partner ecosystem layer. SHAREBOT says it intends to connect leasing, deployment, maintenance, upgrades, secondary trading, and cross-region scheduling, while a reported JD.com relationship for the similarly described RoboNow platform illustrates the kinds of logistics, maintenance, insurance, recycling, and data-collection capabilities required by this model. These descriptions are ecosystem claims, not proof that every capability is already owned or integrated by SHAREBOT. The company's stated expansion to 13 countries and partnerships for mobile retail and sale-plus-rental products indicate roadmap breadth, but no public API, architecture diagram, service-level agreement, failure statistics, or deployment acceptance criteria was found in the assigned evidence. Maturity is therefore strongest at the marketplace and orchestration concept level and unproven at technical-system level.[CE005, CE006, CE007, CE008]

5.3 Differentiation and dependencies

SHAREBOT's potential differentiation is operational rather than a demonstrated proprietary robot breakthrough. The reported model emphasizes a standardized delivery network, geographic coverage, scenario-specific solutions, and partner coordination. Partnerships with Shanpu and Digit Robotics are described as extending mobile retail and sale-plus-rental offerings, with Digit responsible for research and production while SHAREBOT contributes platform, channels, and venue resources. This division suggests a capital-light ecosystem position, but it also creates dependence on supplier quality, partner economics, local operators, logistics, and the availability of suitable robots. China's 2026 national policy environment is pushing real-scene validation, data governance, reliability, safety functions, and lifecycle controls for embodied robots. That raises the bar for measurable deployment evidence: marketing claims about access or coverage should not be treated as evidence of safety certification, algorithmic advantage, or durable intellectual property.[CE009, CE010, CE011, CE012]

5.4 Trust, safety, and diligence priorities

The assigned sources do not provide SHAREBOT-specific security documentation, privacy controls, incident history, insurance terms, safety certification, or quality-control records. Government guidance for embodied-robot deployments calls for real-scene testing, success-rate and efficiency evaluation, safety and reliability assessment, data-security and privacy safeguards, collision detection, force limits, emergency braking, and black-box capabilities. Those requirements are relevant diligence benchmarks, not evidence that SHAREBOT has implemented them. The key product risk is a gap between a broad network promise and the evidence needed to show repeatable, safe, and economically viable deployments across heterogeneous robot types and countries. Before underwriting product maturity, an investor should obtain the asset inventory by model, acceptance and uptime records, incident and insurance logs, partner service-level terms, data-flow and access-control diagrams, and evidence that customer deployments meet applicable local requirements.[CE013, CE014]

5.5 Exhibits

6.1 Customer segments and demand surfaces

Publicly described demand is concentrated in business-to-business and event-led use cases rather than a disclosed recurring enterprise subscription base. People’s Daily reports that more than 54 percent of Botshare orders during the Spring Festival were for New Year greetings, temple fairs, and shopping malls, while marriage proposals and parent-child activities were rising. Pandaily similarly describes demand from festive events, corporate annual meetings, and cultural-tourism activities, with orders increasing approximately 30 percent week over week during February 1–7, 2026. The AWE account adds exhibitions, malls, tourism, brand marketing, celebrations, and education as target contexts, and says customers asked how robots could support store traffic, event dissemination, brand interaction, and reception. These signals identify a broad buyer set—brands, event organizers, malls, tourism operators, and education providers—but do not disclose payer mix, contract value, or repeat behavior.[CU001, CU002, CU003, CU004]

6.2 Adoption trajectory and named-use proof

The strongest public adoption evidence is transactional or operational rather than retention-based. People’s Daily cites more than 1,000 Botshare orders received by February 12 for the February 15–23 holiday period, with an expectation of more than 5,000 by the holiday’s end; Pandaily reports that seasonal bookings were essentially sold out a month in advance and that popular models were scheduled through mid-March. The AWE article describes jointly deployed robots listed in the platform mini-program and customer inquiries at the exhibition. These records support demand, availability pressure, and platform-mediated deployment, but they do not identify customer names, production-versus-pilot status, outcomes, renewal, or unit economics.[CU005, CU006, CU007, CU008]

6.3 Durability, expansion, and concentration unknowns

Public reporting does not provide SHAREBOT’s churn, renewal, GRR, NRR, cohort retention, contract duration, or top-customer revenue share. The available evidence instead shows a seasonal demand pattern and an operating model that must coordinate equipment, local service, on-site operators, safety personnel, and customization. IT Home reports a network of more than 600 service providers across 50 core cities and a price range from 200 yuan to more than 10,000 yuan, while the AWE account describes selection, solution design, deployment, content planning, and operational support. This can lower experimentation friction for customers, but it also leaves open whether activity converts into durable recurring usage and whether platform economics depend on a small number of seasonal channels or partners.[CU009, CU010, CU011, CU012]

6.4 Exhibits

7.1 Risk posture and evidence boundary

SHAREBOT operates in a market where robots move through public, high-traffic, and varied environments rather than remaining in controlled facilities. A Chinese financial publication describes rental as lowering adoption barriers while increasing exposure to equipment damage, third-party liability, and data security. It also reports that robot leasing combines equipment lending with on-site technical operations and human interaction, making responsibility span the owner, operator, software, and venue. This is a structurally higher-control burden than a simple marketplace transaction. Public reporting further indicates that demand is expanding, but the evidence does not disclose SHAREBOT-specific incident frequency, loss ratios, insurance exclusions, uptime, or customer concentration. The risk conclusion is therefore based on operating-model exposure and sector evidence, not a claim that SHAREBOT has suffered an unreported incident.[CR001, CR002, CR003]

7.2 Regulatory, legal, and data exposure

The most material legal and regulatory uncertainty concerns safety, responsibility, and data governance across jurisdictions and use cases. A Yicai report says embodied-intelligence products lack unified international or industry standards and identifies compatibility, security, data compliance, and cross-border data-flow risks. The same report records that insurers are adding third-party liability and cybersecurity coverage, which is a mitigation signal but not proof that a platform's controls or policy limits are adequate. The available evidence does not confirm SHAREBOT's licenses, privacy notices, customer consent flows, incident response plan, product-safety certifications, or contract allocation of liability. These gaps should be treated as diligence blockers before assuming that insurance transfers legal or reputational exposure.[CR004, CR005, CR006]

7.3 Operational and dependency risks

Reliability is a core economic risk because a rental asset that is late, damaged, or unavailable can lose the event and require replacement service. Shanghai government reporting describes engineers checking state, adjusting parameters, confirming interaction logic, monitoring operation, and responding to unexpected interaction in crowded holiday settings. It also reports that robots may run for more than eight hours in dense public environments. Separate reporting describes repair, battery, testing, logistics, insurance, and recovery as interlocking capabilities, and notes that rental prices have fallen while service quality becomes a competitive threshold. SHAREBOT's public evidence does not establish its own service levels, spare-parts availability, partner exclusivity, or economics after field support. The operating model therefore has both uptime risk and dependency risk even when demand is present.[CR007, CR008, CR009, CR010]

7.4 Monitoring, mitigations, and thesis-break triggers

Available mitigations are developing at the ecosystem level: insurance products combine body-loss and third-party liability, repair networks are expanding, and platforms are described as using operations data to improve dispatch and risk control. These measures reduce exposure only if SHAREBOT can demonstrate coverage scope, claims handling, preventive maintenance, event-site controls, and auditable data permissions. The investment thesis should break if a material injury or property loss is uninsured or cannot be assigned promptly; if repeat failures cause cancellations or refunds; if insurance exclusions leave the company bearing replacement cost; if supplier or repair dependencies interrupt peak-season availability; or if regulators or customers restrict data collection. The next diligence step is a loss-run and incident ledger reconciled to contracts, insurance schedules, uptime records, and repair tickets.[CR011, CR012, CR013, CR014]

7.5 Exhibits

8.1 Recommendation and entry discipline

SHAREBOT should remain in research-more status. Crunchbase's May 2026 unicorn review reports that a less-than-one-year-old Pudong robot-leasing platform called Botshare raised a Series A and was valued at $1 billion, but the assigned pool does not establish that this English label maps to SHAREBOT's legal entity or that the mark remains current. The report also supplies no revenue run-rate, gross margin, utilization, cash burn, capitalization, or preference data. Entry discipline therefore matters more than the headline valuation: an investor should require legal-entity confirmation, financing documents, audited or management accounts, cohort utilization and renewal data, and a contribution-margin bridge after logistics, service, insurance, downtime, and depreciation. Conditional on entity confirmation, the $1 billion reference looks stretched rather than supported by public fundamentals; this is not evidence that demand is absent.[CV001, CV002, CV003, CV004, CV010, CV011]

8.2 Investment thesis and anti-thesis

The positive thesis is that robotics adoption is expanding in Asia-Pacific, Chinese policy and industrial scale can create a large operating environment, and rental can reduce the upfront commitment for customers that need robots for short events or pilots. Market Research Future projects the Asia-Pacific robotics market from $42.33 billion in 2025 to $141.21 billion in 2035 at a 12.8% CAGR, while IFR and Chinese government reporting put China's 2024 industrial-robot stock at about or above two million units. The anti-thesis is that these are market-level indicators, not SHAREBOT cash flows. Bain and IFR describe humanoid deployments as largely pilot-stage or demonstration-led; Sohu describes falling daily rental prices and the operational burden of dispatch, tuning, repair, insurance, and recovery. CCTV's 2026 standards coverage also reports high costs, fragmented scenarios, imported-component dependence, and model-generalization constraints. The thesis changes only when SHAREBOT demonstrates durable utilization and positive contribution economics after those costs.[CV005, CV006, CV007, CV008, CV009, CV015, CV016]

8.3 Scenarios, comparables, and diligence

Scenario analysis should be expressed as underwriting gates rather than fabricated valuation points. In the bull case, repeat customers, multi-city service density, high utilization, and paid data or workflow services could support a premium to a simple equipment-rental multiple. In the base case, event-led demand grows but price competition and service costs keep margins modest, supporting a disciplined entry only after verified unit economics. In the bear case, falling day rates, hardware downtime, safety or compliance failures, and working-capital needs force a down-round or additional dilution. Comparable marks show the danger of false precision: Crunchbase reports Botshare at $1 billion after a Series A, while CompaniesMarketCap reported Serve Robotics at $0.24 billion on October 23, 2026 and down 68.08% during 2026. Richtech's indexed 10-K and 10-Q cadence also illustrates the disclosure gap between public comparables and this private-company evidence pool. None is an interchangeable benchmark, so SHAREBOT needs contract, asset, financing, and exit data before a valuation range or target return can be assigned.[CV010, CV011, CV012, CV013, CV014]

8.4 Exhibits