Founded 01
2016 [CO001] Diligence report
Overhaul
Austin supply-chain visibility platform with real enterprise traction, but still too much public opacity for a clean valuation call
Overhaul is strategically relevant and commercially credible, but the public record still supports research-more rather than a confident buy.
Coverage and disclosure
Public evidence supports Overhaul's 2016 Austin origin, enterprise traction, named customers, and a sizable 2025 funding event, but the company remains opaque on current valuation, ARR, gross margin, retention, and concentration. Public funding totals also vary by database, so the fair reading is a research-more stance rather than a precise buy/sell call.
Cover facts
Company profile
Overhaul is an Austin-based supply-chain software and services company founded in 2016 that combines shipment visibility, cargo-risk management, compliance monitoring, and human control-tower operations. Public materials position the company as more than a tracking tool: it sells a response-oriented workflow for high-consequence freight, with insurance brokerage and adjacent monitoring services layered on top. The public record supports enterprise adoption and a meaningful 2025 funding event, but the company still does not disclose enough operating detail to underwrite a clean valuation.
- Website
- www.over-haul.com
- Founded
- 2016-01-01
- Founders
- Barry Conlon
- Founding location
- Austin, Texas, United States
- Headquarters
- Austin, Texas, United States
- Product
- Shipment visibility, cargo risk management, compliance monitoring, and human-in-the-loop control tower operations.
- Customers
- Enterprise shippers, 3PLs, automotive manufacturers, and regulated freight operators.
- Business model
- B2B software subscriptions, insurance brokerage, and monitoring / control-tower services.
- Stage
- late-stage private
- Funding status
- Public sources support a $105 million Series C in August 2025 with MidCap debt and conflicting total-funding estimates ranging from roughly $215 million to $271 million.
Executive summary
Top strengths
- Named enterprise customers and FreightVerify expansion support real commercial traction.
- The product combines visibility, intervention, and insurance in a harder-to-copy workflow.
- The company remains well-capitalized enough to keep investing in adjacent services.
Top risks
- ARR, gross margin, retention, and customer concentration remain undisclosed.
- Regulatory, security, and insurance-related exposure raises operating and diligence complexity.
- Public funding totals conflict across databases, which weakens valuation precision.
Open gaps
- Current operating metrics and revenue mix are still not public.
- Customer concentration and renewal durability remain unproven.
- Security and privacy documentation is still not visible at enterprise-ready depth.
- A current valuation or secondary mark is still absent from the public record.
Contents
01Company Overview
1.1 Identity, origin, and leadership
Overhaul is best understood as an Austin-based supply-chain software and services company that started in 2016 and has since broadened from tracking shipments to managing security, compliance, and risk intervention. Public company pages consistently present Barry Conlon as the CEO, while third-party databases describe the business as founder-led and highlight the same Austin base. The company’s public materials also emphasize that it is not a generic visibility vendor: it markets a control-tower workflow designed for high-consequence cargo rather than commodity parcel tracking. That positioning matters because it explains why the platform can sell into regulated, high-value verticals even without a disclosed public valuation.[CO001, CO002, CO003, CO004]
| Metric | Value / status | Date | Confidence | Gap |
|---|---|---|---|---|
| Founded | 2016 | 2016 | medium | |
| Headquarters | Austin, Texas, United States | current | medium | |
| Latest funding | $105M Series C + MidCap debt | Aug 2025 | medium | Valuation not disclosed |
| Total funding | $215M to $271M depending on source | 2025-2026 sources | medium | Database disagreement |
| Current valuation | Not publicly disclosed | 2026 | medium | No public mark |
| Named customers | Microsoft, Bristol Myers Squibb, CEVA, Arvato | current | medium | No customer concentration data |
Values are public-source snapshots; funding totals conflict across databases and the valuation field remains undisclosed.
[CO001, CO002, CO005, CO006, CO011, CO012]| Person | Role | Background | Founder / fit | Key-person note |
|---|---|---|---|---|
| Barry Conlon | CEO and founder | Publicly cited by PRNewswire and Tracxn as the company leader. | Commercial and operating fit | Central to public identity |
| Springcoast Partners | Lead growth investor | Led 2025 financing and joined the board through its principals. | Capital sponsor fit | Adds board influence |
| Edison Partners | Investor across multiple rounds | Participated in both the 2021 and 2025 financings. | Long-running capital support | Signals continuity |
| MidCap Financial | Debt provider | Added debt to the 2025 capital stack. | Structured-finance fit | Introduces leverage risk |
| Macquarie Capital | 2021 Series B lead investor | Named in the 2021 financing announcement. | Historical capital sponsor fit | Helps anchor the pre-2025 capital stack |
Leadership information is public but incomplete; board composition is only partially disclosed.
[CO004, CO006, CO007]| Person | Role | Background | Founder / fit | Key-person note |
|---|---|---|---|---|
| Barry Conlon | CEO and founder | Publicly cited by PRNewswire and Tracxn as the company leader. | Commercial and operating fit | Central to public identity |
| Unknown cofounder set | Not publicly disclosed | Current public sources do not disclose a full founding roster. | Gap | Requires confirmation |
| Springcoast Partners | Lead growth investor | Led 2025 financing and joined the board through its principals. | Capital sponsor fit | Adds board influence |
| Edison Partners | Investor across multiple rounds | Participated in both the 2021 and 2025 financings. | Long-running capital support | Signals continuity |
| Macquarie Capital | 2021 Series B lead investor | Named in the 2021 financing announcement. | Historical capital sponsor fit | Helps anchor the pre-2025 capital stack |
Leadership information is public but incomplete; board composition is only partially disclosed.
[CO004, CO006, CO007]A compact chronology of founding, funding, and expansion events.
[CO001, CO006, CO010]1.2 Funding, scale, and capital structure
The public funding trail is more informative than the current valuation. Overhaul secured a $35 million Series B in 2021, followed by a 2025 growth round and then the August 2025 $105 million Series C that included MidCap Financial debt. Sacra and Tracxn disagree on total funding, which is common when private rounds, debt, and undisclosed tranches are mixed together, but both point to a heavily capitalized business. The important takeaway is not the exact top-line total; it is that the company has continued to raise capital while layering in adjacent services, suggesting a strategy of financing product breadth rather than starving the platform.[CO005, CO006, CO007, CO009]
1.3 Milestones and unresolved questions
The most meaningful milestone in the current refresh is the FreightVerify acquisition, because it materially expands the product’s footprint into automotive manufacturing and part-level visibility. The evidence also points to a broader issue: despite multiple public funding events, Overhaul still does not disclose a current valuation, and public databases disagree on total funding. That means the capital story is clearer than the ownership story. For diligence, the open questions are whether the founder / CEO ownership structure is stable, how debt sits behind the August 2025 round, and whether any valuation reset occurred off the public record.[CO010, CO011, CO012]
02Market Analysis
2.1 Market boundary and status quo
Overhaul should not be sized as generic transportation management software. The more useful boundary is the wedge where visibility, intervention, and risk transfer overlap: high-value freight, time-sensitive freight, and regulated freight that creates a measurable cost when it goes wrong. That framing is consistent with public language around cargo theft, freight fraud, and compliance monitoring. The status quo is still a stack of telematics, spreadsheets, carrier calls, and insurance workarounds, so the real market is the spend that shifts from reactive processes to a monitored control plane.[CM001, CM005, CM009]
| Segment / boundary | Included spend | Excluded spend | Buyer / payer | Relevance |
|---|---|---|---|---|
| Supply-chain visibility | Shipment tracking and alerting | Commodity TMS basics | Shippers / 3PLs | Core software wedge |
| Cargo risk management | Loss prevention, recovery, compliance | Manual exception handling only | Operations / risk owners | Most differentiated budget |
| Insurance adjacency | Premium optimization and brokerage | Generic insurance unrelated to cargo | Risk / finance owners | Expands spend per account |
| Status quo substitute | Telematics, email, spreadsheets | None | Operations teams | Baseline alternative |
Boundary is deliberately narrower than total logistics software; this table preserves the included/excluded spend logic.
[CM001, CM004, CM005, CM009]| Segment | Buyer | User | Payer | Adoption trigger |
|---|---|---|---|---|
| Enterprise shipper | VP supply chain / risk | Control tower team | Operations or finance | Loss event or audit pressure |
| 3PL / logistics provider | COO / account lead | Dispatch or exception managers | Client-funded or shared | Customer SLA and visibility demands |
| Automotive / manufacturing | Plant logistics | Planners and suppliers | Plant or procurement | Production-critical part delays |
| Regulated cargo | Compliance / legal | Risk analysts | Compliance budget | Regulatory traceability or claims issues |
Buyer roles vary by use case; the practical buying motion is operations-led but finance-validated.
[CM002, CM006, CM011]The market is buyer-fragmented, but the trigger is usually a real loss or compliance event.
[CM002, CM011]2.2 Demand drivers and adoption constraints
The strongest demand driver is loss prevention: when theft or damage is expensive enough, buyers can justify a dedicated system that reduces incidents and improves recovery. A second driver is insurance economics, because premium savings and better claims discipline turn risk management into a financial conversation. The constraints are just as real: the product must prove ROI lane by lane, integrate into existing operations, and satisfy compliance or legal review. That is why the market is expanding, but still selective and operationally intensive rather than mass-market SaaS.[CM003, CM004, CM006, CM010, CM012]
| Driver / constraint | Direction | Timing | Implication | Diligence ask |
|---|---|---|---|---|
| Cargo theft and fraud | Positive | Current | Raises urgency and ROI | Loss-reduction proof by lane |
| Insurance savings | Positive | Near-term | Supports premium pricing | Documented premium delta |
| Switching cost | Negative | Ongoing | Slows adoption | Migration / integration cost |
| Compliance burden | Mixed | Ongoing | Can create budget but slow procurement | Legal review path |
Directional table; it is intentionally descriptive rather than numerically precise.
[CM003, CM005, CM006, CM012]2.3 Sizing logic and uncertainty
Public evidence supports a range-based sizing approach rather than a single TAM number. The relevant budget mix includes software subscriptions, services, and an insurance adjacency, but the spend is spread across shippers, 3PLs, and regulated end markets. That means the right diligence question is not whether the market is “large”; it is how much of the budget actually moves from manual monitoring to premium monitoring when ROI is proven. The most useful output is a bounded range with assumptions preserved, not a false-precision headline. The implication for diligence is that market size should be read as an operating range tied to proof of loss reduction, claims discipline, and premium spend conversion, not as a venture-style TAM claim detached from buyer behavior. This keeps the sizing honest.[CM007, CM008, CM011]
03Competitors
3.1 Peer landscape and substitutes
Overhaul’s competitive set is broader than the usual visibility market shortlist. The direct peers are software-led platforms such as project44 and FourKites, but the practical substitutes also include telematics companies, fraud-detection tools, and manual workflows inside the shipper’s own operation. That matters because buyers often start with a narrow problem and then decide whether they need a broader control plane. Overhaul’s position is strongest when the customer wants not only to know where freight is, but also what to do next, who is accountable, and how insurance fits into the response path.[CP001, CP002, CP003, CP004]
| Competitor | Category | Scale / funding | Target segment | Differentiation | Limitation |
|---|---|---|---|---|---|
| project44 | Direct visibility peer | Large private company / heavy funding | Enterprise shippers | Broad multi-modal visibility | Less insurance / response integration |
| FourKites | Direct visibility peer | Large private company / heavy funding | Enterprise shippers | Deep visibility and orchestration | Less cargo-security specialization |
| Tive | Adjacent sensor competitor | Series C-backed | Cold chain and high-value freight | Hardware-led telemetry | Less workflow integration |
| Samsara | Adjacent fleet competitor | Public-scale platform | Carrier-side fleet operations | Telematics and asset data | Not a cargo-response specialist |
| Descartes MacroPoint / Highway | Substitute | Incumbent software players | Fraud and broker risk | Narrower fraud detection tools | Lacks end-to-end control plane |
Profiles are purposefully directional; funding figures are omitted where the public data in this bundle is not the focus of the current refresh.
[CP001, CP002, CP003, CP004, CP005]| Buying criterion | Overhaul | Visibility peers | Telematics peers | Substitutes |
|---|---|---|---|---|
| Tracking / visibility | Strong | Strong | Moderate | Moderate |
| Cargo-response workflow | Strong | Moderate | Weak | Weak |
| Insurance adjacency | Strong | Weak | Weak | Weak |
| Hardware dependency | Device-agnostic | Low | High | Varies |
Capability scoring is relative and evidence-based, not a benchmark study.
[CP006, CP008, CP009]3.2 Differentiation and pricing logic
The company’s differentiator is not raw tracking coverage; it is the blend of intervention, insurance, and cargo-security workflow. That blend can support premium pricing because the buyer is buying avoided loss, not just a dashboard. FreightVerify adds another layer: item-level and manufacturing use cases that broaden the competitive wedge into auto and healthcare workflows. The key question is whether competitors can replicate enough of this stack with software alone. If they can, the moat narrows. If they cannot, Overhaul’s integrated operating model keeps the platform above point-solutions.[CP005, CP006, CP007, CP008]
| Moat claim | Threat | Severity | Mitigation / diligence ask |
|---|---|---|---|
| Integrated response stack | Visibility peers add adjacent features | High | Ask for win/loss evidence |
| Insurance economics | Premium pressure or regulatory change | Medium | Review brokerage terms and licensing |
| FreightVerify expansion | Integration complexity | Medium | Confirm product roadmap and adoption metrics |
| Control-tower service | Human-intensive scaling | High | Check service margins and staffing model |
This table separates moat claims from the risks that can erode them.
[CP006, CP007, CP008, CP011]3.3 Moat durability and risk
The main competitive risk is commoditization by larger platforms. Visibility players can add exception management, while telematics vendors can climb the stack from the carrier side. Overhaul’s defense is that its human-in-the-loop response and insurance economics are harder to copy than software features alone. But that defense is only durable if customers keep paying for intervention and not just tracking. The most useful diligence question is therefore simple: where does Overhaul win because of its operating model, and where would a buyer be just as well served by a cheaper visibility tool or in-house process? The answer determines whether the moat is structural or merely packaging. That is the competitive test. Buyers will pay only where service quality is visibly superior.[CP009, CP010, CP011, CP012]
04Financials
4.1 Revenue model and monetization
Overhaul appears to monetize in three distinct ways: software subscription, insurance brokerage, and monitoring services. That is attractive because it creates multiple revenue levers around the same freight event, but it also makes margin analysis harder. The public record suggests the platform is sold against shipment volume and feature set rather than a simple per-seat license. That means public valuation should not be forced into a pure SaaS template. The right financial question is whether the services layer is a durable margin enhancer or a labor-intensive drag that only looks attractive while growth is strong.[CI001, CI002, CI008, CI010]
| Stream | Mechanism | Unit | Current value / status | Quality | Diligence ask |
|---|---|---|---|---|---|
| Subscription software | Platform access and features | Shipment / account | Core revenue stream | Likely highest margin | Confirm pricing and mix |
| Insurance brokerage | Cargo insurance placement | Policy / premium | Adjacent revenue stream | Margin uncertain | Ask for brokerage economics |
| Monitoring services | 24/7 control-tower support | Account / lane | Value-added service | Potentially labor-intensive | Separate labor cost from software |
This is a revenue-mechanism table, not a disclosed financial statement.
[CI001, CI002, CI008]| Capital item | Status | Why it matters | Open question |
|---|---|---|---|
| Cash / runway | Not public | Determines follow-on risk | How long until next raise? |
| Debt | MidCap debt included in 2025 round | Adds leverage and covenant risk | What are the terms? |
| Use of funds | Growth and acquisition | Explains burn rate | How much is organic vs M&A? |
| Customer concentration | Not public | Affects downside risk | Are the top accounts diversified? |
All values are public or explicitly unavailable; no attempt is made to estimate hidden cash balance.
[CI003, CI004, CI009, CI010]A simple bridge showing how one freight event can produce multiple revenue streams.
| Node / Connection | Node / from | To | Context |
|---|---|---|---|
| Node 1 | High-consequence freight | ||
| Node 2 | Subscription software | ||
| Node 3 | Insurance brokerage | ||
| Node 4 | Monitoring services | ||
| Node 5 | Revenue / gross profit | ||
| Connection 1 | High-consequence freight | Subscription software | |
| Connection 2 | High-consequence freight | Insurance brokerage | |
| Connection 3 | High-consequence freight | Monitoring services | |
| Connection 4 | Subscription software | Revenue / gross profit | |
| Connection 5 | Insurance brokerage | Revenue / gross profit | |
| Connection 6 | Monitoring services | Revenue / gross profit |
4.2 Capital structure and financing cadence
The financing cadence is the clearest public financial signal. Overhaul raised a Series B in 2021, a growth round in early 2025, and a Series C plus debt stack in August 2025. That pattern says the company is still capital-intensive even after years in market. Debt adds a real hurdle because it introduces repayment and covenant risk that pure-equity investors do not face. The absence of a disclosed valuation in the August 2025 round means the market cannot tell whether investors paid up, held flat, or reset lower. That uncertainty is central to any underwriting view.[CI003, CI004, CI005, CI007, CI011]
| Date | Round | Disclosed amount | Investor / debt | Interpretation |
|---|---|---|---|---|
| Jun 2021 | Series B | $35M | Macquarie / Edison / Avanta | Early scale capital |
| Jan 2025 | Growth financing | $55M | Springcoast / Edison / Americo | Pre-Series C support |
| Aug 2025 | Series C | $105M | Springcoast / Edison / MidCap debt | Latest public capital event |
| 2025-2026 | Total raised | $215M to $271M | Sacra / Tracxn | Public databases disagree |
This chronology preserves the public funding record without resolving the database discrepancy.
[CI003, CI005]4.3 Missing metrics and underwriting blockers
The open record still does not reveal ARR, gross margin, NRR, burn, runway, or customer concentration. Those are not minor missing pieces; they are the variables that determine whether the business can support its capital stack and what kind of valuation multiple is reasonable. The best interpretation is to treat public financial data as directionally informative, not definitive. Until management shares an operating package, all valuation work should stay in scenario form rather than pretending that the public record supports exact numbers. That same gap also blocks a credible cash-flow bridge and makes any margin bridge speculative. Investors would therefore insist on tighter reporting covenants. Full diligence still required.[CI006, CI009, CI012]
05Product & Technology
5.1 Workflow and modules
Overhaul’s product story is built around a simple promise: move from observing freight to actively controlling freight. The public material is unusually consistent on that point. The platform combines visibility, predictive risk intelligence, and compliance monitoring in a control-tower workflow that lets operators see shipment status, triage exceptions, and escalate when the risk engine flags a problem. FreightVerify makes the story more specific by extending the workflow into item-level and manufacturing use cases, which means the product is no longer just a freight alerting system; it is a broader operational layer tied to inventory and production outcomes.[CE001, CE002, CE007, CE009]
| Module / product line | User | Status / maturity | Differentiation | Diligence gap |
|---|---|---|---|---|
| Visibility + control tower | Shippers and operators | Core product | Combines alerts with human response | Margin and staffing model |
| RiskGPT | Exception managers | Recent AI layer | Plain-language recommendations | Model accuracy / hallucination controls |
| Vision module | Origin teams | Recent AI/computer vision | Validates photo documentation | Error rate / audit trail |
| FreightVerify | Manufacturing and auto teams | Acquired capability | Item-level and VIN/SKU sequencing | Integration roadmap |
A concise module map anchored in public product pages and acquisition coverage.
[CE001, CE004, CE005, CE007]| Layer / component | Role | Dependency | Risk |
|---|---|---|---|
| Telemetry ingestion | Collect data from sensors and systems | External devices and feeds | Data quality and device compatibility |
| Risk scoring engine | Detect anomalies and rank issues | Historical events and rules | False positives / negatives |
| Control tower | Human escalation and recovery | 24/7 staffing | Labor intensity |
| Insurance / compliance layer | Convert data into coverage and savings | Licensing and regulatory compliance | Regulatory and legal exposure |
Architecture is described at a functional level because the company does not disclose a formal public system diagram.
[CE003, CE006, CE010, CE012]The product is a detect–triage–recover loop, not just a passive dashboard.
| Node / Connection | Node / from | To | Context |
|---|---|---|---|
| Node 1 | Freight event | ||
| Node 2 | Telemetry ingestion | ||
| Node 3 | Risk scoring | ||
| Node 4 | Control tower | ||
| Node 5 | Recovery / customer impact | ||
| Node 6 | Manual escalation | ||
| Connection 1 | Freight event | Telemetry ingestion | |
| Connection 2 | Telemetry ingestion | Risk scoring | |
| Connection 3 | Risk scoring | Control tower | |
| Connection 4 | Control tower | Recovery / customer impact | |
| Connection 5 | Control tower | Manual escalation | |
| Connection 6 | Manual escalation | Recovery / customer impact |
5.2 Architecture, telemetry, and AI
The architecture is data-heavy and device-agnostic. Public descriptions reference GPS, electronic logging devices, temperature, shock and tilt sensors, door events, route context, weather, traffic, and crime heat maps. That makes the technical edge less about one sensor and more about the combination of ingestion, scoring, and intervention. RiskGPT and the Vision module add an AI layer, but they are still bounded by the quality of the incoming telemetry and the operating discipline of the human control tower. If those inputs are noisy, the AI layer can only be as good as the underlying event pipeline.[CE003, CE004, CE005, CE006]
5.3 Trust, compliance, and differentiation
The moat is not just technical; it is operational and trust-based. Overhaul is asking customers to share sensitive shipment information and rely on the company for exception handling, recovery, and in some cases insurance-related decisions. That means the public lack of SOC 2 or equivalent detail is a real diligence question, not a footnote. The company’s differentiation is strongest where it can show end-to-end workflow plus item-level data plus response. The weakest point, based on public evidence, is the depth of external trust and developer proof beyond the company’s own marketing surface. The practical question is whether these controls scale cleanly as freight volume and customer expectations rise.[CE010, CE011, CE012]
| Control / certification / quality metric | Status | Scope | Gap |
|---|---|---|---|
| SOC 2 / formal security certification | Not publicly confirmed | Enterprise data trust | Need evidence |
| Privacy / DPA documentation | Not publicly confirmed | Sensitive shipment data | Need evidence |
| Device-agnostic integration | Publicly claimed | Multi-modal monitoring | Need implementation proof |
| AI output validation | Publicly claimed | RiskGPT / Vision | Need error-rate evidence |
The table separates public claims from missing trust documentation.
[CE011, CE012, CE006]06Customers
6.1 Named customer proof
Customer proof is strongest when it combines a named logo with a concrete outcome. Overhaul has that for Microsoft, and it has repeated named references for Bristol Myers Squibb, CEVA, and Arvato across official and third-party sources. The vertical mix is also coherent: automotive, life sciences, healthcare, logistics, and high tech all face expensive freight exceptions and a premium on reliability. That is a better proof set than a generic logo wall because it shows the platform is already being used in workflows where failure is expensive.[CU001, CU002, CU003, CU009]
| Segment | Buyer / user / payer | Use case | Scale | Revenue / strategic value | Gap |
|---|---|---|---|---|---|
| Enterprise shipper | Operations / risk / finance | Exception management and loss prevention | High | Core enterprise ARR | Concentration unknown |
| Automotive manufacturer | Plant logistics / procurement | Part-level tracking | High after FreightVerify | Strategic expansion | Adoption depth unclear |
| Life sciences / healthcare | Supply chain / compliance | Cold-chain and traceability | High | Premium vertical | Retention not public |
| 3PL / logistics provider | Operations | Shipment monitoring | Medium | Channel / footprint | No contract data |
The segmentation is driven by the public customer list and FreightVerify expansion.
[CU001, CU002, CU008, CU011]| Customer | Segment | Deployment / use case | Production vs pilot | Outcome | Limitation |
|---|---|---|---|---|---|
| Microsoft | High tech | Supply-chain control and ROI | Production | 4x return claim | Single quote only |
| Bristol Myers Squibb | Life sciences | High-consequence cargo | Production | Named logo proof | No quantified ROI |
| CEVA | Logistics | Enterprise freight monitoring | Production | Named logo proof | No retention data |
| Arvato | Logistics / services | Supply-chain visibility | Production | Named logo proof | No contract length |
Named proof is strongest when accompanied by a customer quote or outcome metric.
[CU001, CU003, CU004]A high-consequence customer usually starts in a single lane and expands after proving ROI.
[CU003, CU004, CU005, CU007]6.2 Adoption trajectory and scale
FreightVerify materially improves the customer narrative because it adds scale metrics rather than just logos. The acquisition brought in six of the top ten automotive manufacturers, around 70,000 monthly users, and about 280,000 shipping locations. That is enough to say the platform is not just being tested; it is being used in a meaningful operational footprint. The 100 million tracked shipment figure is especially useful because it shows activity depth, not just account count. Even so, the public record still does not show how much of that activity is recurring versus one-off integration work. The distinction matters because recurring usage is what turns scale into durable revenue.[CU004, CU005, CU006]
6.3 Durability, retention, and concentration
The missing piece is durability. We do not see public churn, renewal, contract-length, or top-customer concentration data, which means the durability story remains inferential. The buying motion is likely operations-led but finance-validated, especially in regulated verticals where compliance and data handling matter. That makes the customer story real but not complete. In diligence, the most useful next step is a customer roster that shows production status, ARR share, renewal timing, and whether FreightVerify customers are additive or simply re-labeled proof points. These details separate real expansion from headline-only proof. They also show whether the platform is sticky enough to defend pricing. That is the underwriting core.[CU007, CU008, CU010, CU011, CU012]
| Expansion driver | Concentration risk | Impact | Diligence path |
|---|---|---|---|
| FreightVerify automotive expansion | Customer concentration remains unknown | Positive growth, but possible OEM concentration | Ask for top-customer mix |
| Monthly users / locations | Use is broad but not audited | Adds scale evidence | Ask for active-user definition |
| Production deployments | Pilot vs production not always clear | Affects ARR confidence | Request deployment list |
| Regulated verticals | Compliance sensitivity | Can slow renewals | Request renewal and procurement history |
This is the table most likely to turn into a recurring diligence ask at refresh time.
[CU004, CU005, CU006, CU010]07Risks
7.1 External threats: demand, regulation, and competition
Overhaul’s risk profile starts with the fact that its market is built around expensive problems. Cargo theft can increase the need for the product, but it also means the company lives in an environment where buyer urgency is tied to external loss trends. The second risk is regulatory: as soon as the company touches insurance, compliance, and sensitive freight data, it inherits supervision and privacy obligations that are harder to hide from than ordinary software risk. Competition is the third threat, because larger visibility vendors can add adjacent capabilities and erode differentiation. These risks also shape procurement cycles and partner diligence.[CR001, CR002, CR010, CR011]
| Rule / license / case | Jurisdiction | Status | Likelihood | Severity | Mitigation | Residual exposure | Diligence path |
|---|---|---|---|---|---|---|---|
| Insurance brokerage supervision | US state multi-jurisdiction | Ongoing | Medium | High | Compliance controls | Residual licensing risk | Request broker license list |
| Privacy and data handling | US / EU | Ongoing | Medium | High | Security documentation | Sensitive-data exposure | Request DPA / GDPR docs |
| Consumer / customer-service enforcement analogs | Regulatory environment | Contextual | Medium | Medium | Policy discipline | Operational oversight risk | Ask for complaints / incident log |
Ordered by severity; the table is intentionally a diligence register, not a legal opinion.
[CR002, CR011, CR012]The highest residual severity sits in security, scaling, and capital-structure risk.
[CR003, CR004, CR006, CR010, CR012]7.2 Operational and security risk
The operational model is not purely software. It depends on data feeds, integrations, sensors, and a human control tower, which means a failure in any one layer can create a customer-visible incident. AI adds another failure mode: false positives can disrupt operations while false negatives can miss real threats. The fact that the public record does not clearly spell out SOC 2 or privacy posture keeps the company in a higher-risk bucket for enterprise procurement. In short, the platform is useful, but it is also exposed at the exact point where customers are most sensitive. Small failures can cascade into larger account-level trust problems.[CR003, CR006, CR007, CR008, CR012]
| Failure mode | Likelihood | Severity | Mitigation maturity | Residual exposure | Unresolved gap |
|---|---|---|---|---|---|
| Bad telemetry / missing feeds | Medium | High | Moderate | Monitoring blind spots | Sensor / integration reliability |
| AI false positives / negatives | Medium | High | Early | Operational disruption | Model validation |
| Control-tower staffing strain | High | High | Moderate | Scaling friction | Headcount / margin |
| Security or privacy incident | Low / Medium | High | Unknown | Enterprise trust damage | SOC 2 / DPA proof |
The risks are ordered qualitatively by residual exposure rather than by exact probability math.
[CR003, CR006, CR007, CR012]7.3 Financial risk and kill criteria
The financial risk is that the company still needs outside capital while public metrics remain incomplete. Debt in the August 2025 round adds another layer of discipline, and the absence of public retention, margin, or concentration data makes it impossible to prove the capital stack is comfortable. The most useful kill criteria are straightforward: if security documentation remains unavailable, if customer concentration is extreme, or if margins are too thin to support the service layer, then the thesis weakens materially. Those are the exact issues to monitor in the next refresh. Capital providers will care about the same stress points.[CR004, CR005, CR009, CR012]
| Risk | Monitorable trigger | Threshold / event | Action implication |
|---|---|---|---|
| Security posture | Security docs remain unavailable | No SOC 2 / DPA / privacy packet | Pause conviction |
| Customer concentration | Top customer share remains hidden | No visibility into concentration | Discount valuation |
| Margin quality | Services layer too labor-intensive | Gross margin not supportable | Question the model |
| Debt burden | Covenant or interest pressure | Debt terms tighten | Reassess capital risk |
This table turns vague concerns into monitorable diligence triggers.
[CR004, CR005, CR006, CR012]08Valuation
8.1 Thesis and anti-thesis
The thesis is straightforward: Overhaul operates in a real, painful market, has named enterprise customers, and combines software with response and insurance in a way that is difficult for pure visibility vendors to copy quickly. The anti-thesis is just as straightforward: the company has not published the financial inputs needed to underwrite a clean valuation. No public ARR, no public gross margin, and no public retention data means the market can tell a story, but it cannot yet prove the math. That pushes the valuation stance toward caution.[CV001, CV002, CV006]
| Field | Value | Rationale | Decision implication |
|---|---|---|---|
| Recommendation | research-more | Public evidence is incomplete | Do not price as a buy yet |
| Confidence | medium | Direction is clear, numbers are not | Use scenario analysis |
| Risk rating | high | Regulatory, security, and financial opacity | Require more diligence |
| Valuation stance | fair / unknown | No public valuation and no ARR | Avoid false precision |
This is the summary judgment table that underwrites the report card.
[CV002, CV003, CV006, CV011]| Argument | What would change the view |
|---|---|
| Differentiated control plane | Evidence that pure visibility peers can replicate the stack quickly |
| Enterprise customer proof | Customer concentration or weak retention |
| Insurance adjacency | Regulatory limits or poor brokerage economics |
| FreightVerify expansion | Low adoption outside the initial use cases |
This table is intentionally concise because the key issue is evidence quality, not narrative density.
[CV001, CV002, CV009, CV010]Range framing only; the figure is illustrative because public ARR is not disclosed.
[CV007, CV008, CV009]8.2 Capital context and comparable anchors
The public capital context is helpful but incomplete. The company has raised multiple rounds, yet the August 2025 Series C did not disclose a post-money valuation. That forces valuation work to rely on comp logic rather than headline price. The most relevant anchors are private-market visibility peers and broader supply-chain software marks, but those comps are imperfect because Overhaul layers in insurance and human response. The right reading is not that the company is cheap or expensive in absolute terms; it is that the public record is not sufficient to say with confidence which side of the range it belongs on. That matters because even a small variance in ARR or margin could move the conclusion materially.[CV003, CV004, CV005, CV011]
8.3 Scenario framing and decision
A sensible valuation frame is scenario-based. A bear case assumes weak margin, limited retention proof, and a lower multiple; a base case assumes a reasonable ARR multiple with no heroic assumptions; a bull case requires proof that FreightVerify expands the customer base and that margins remain healthy enough to support the service layer. Those assumptions are not visible in the public record today. That is why the right recommendation is research-more: the business is interesting enough to keep on the list, but not yet transparent enough to price confidently. Price is a check, not the thesis.[CV007, CV008, CV009, CV010, CV012]
| Comparable | Metric | Multiple / valuation / status | Relevance | Limitation |
|---|---|---|---|---|
| project44 | Private visibility peer | Large-scale private mark | Closest operational peer | Capital-heavy and more visibility-centric |
| FourKites | Private visibility peer | Publicly discussed market mark | Direct competition | Different product mix |
| Samsara | Public market peer | High public ARR multiple | Shows what public liquidity can support | Not directly comparable on business model |
| Private-markets commentary | Secondary pricing | Valuation uncertainty persists | Useful context for pricing discipline | Not a company-specific mark |
The comp set is directional only because the business model mixes software, services, and insurance.
[CV005, CV011]Disclaimer
This report is based on public sources and research-grade synthesis, not investment advice.
Evidence index
| ID | Statement | Confidence | Sources |
|---|---|---|---|
| CO001 | Overhaul was founded in 2016. | Medium | SO001, SO002, SO005 |
| CO002 | Overhaul is headquartered in Austin, Texas, United States. | Medium | SO002, SO005, SO006 |
| CO003 | Public company pages describe Overhaul as a supply-chain visibility, integrity, and security platform. | Medium | SO001, SO002 |
| CO004 | PRNewswire and Tracxn both identify Barry Conlon as CEO and founder. | Medium | SO003, SO005 |
| CO005 | Sacra reports total funding of $215 million while Tracxn reports $271 million over 10 rounds. | Medium | SO004, SO005 |
| CO006 | The August 2025 round was a $105 million Series C led by Springcoast Partners and Edison Partners with MidCap Financial debt. | Medium | SO010, SO005 |
| CO007 | Earlier public funding included a $35 million Series B in 2021 led by Macquarie Capital. | Medium | SO003 |
| CO008 | The company says it combines shipment visibility with risk intelligence, compliance monitoring, and control-tower operations. | Medium | SO001, SO002 |
| CO009 | Overhaul has expanded into tech-embedded cargo insurance brokerage and 24/7 monitoring services. | Medium | SO001, SO002 |
| CO010 | The FreightVerify acquisition added six of the top ten automotive manufacturers, 70,000 monthly users, and roughly 280,000 shipping locations. | Medium | SO004, SO010 |
| CO011 | Named customers repeatedly cited in public sources include Microsoft, Bristol Myers Squibb, CEVA, and Arvato. | Medium | SO001, SO002 |
| CO012 | Public sources still do not disclose a current valuation for Overhaul. | Medium | SO004, SO007, SO009 |
| CM001 | The addressable market should be defined as supply-chain visibility plus in-transit risk management plus cargo-security response, not generic logistics software. | Medium | SM001, SM002, SM008 |
| CM002 | The most relevant buyers are enterprise shippers and 3PLs moving high-consequence cargo in automotive, life sciences, healthcare, and high tech. | Medium | SM001, SM002 |
| CM003 | Cargo theft and freight fraud are central demand drivers because they convert visibility into a measurable loss-avoidance budget. | Medium | SM001, SM002 |
| CM004 | The insurance brokerage angle expands the addressable spend beyond software subscriptions into a higher-value risk-transfer budget. | Medium | SM008, SM007 |
| CM005 | The main constraints are switching cost, operational trust, and the buyer’s need to prove ROI before replacing basic tracking tools. | Medium | SM003, SM004, SM007 |
| CM006 | Regulatory pressure in insurance, privacy, and transport compliance can accelerate adoption while also slowing procurement. | Medium | SM003, SM004 |
| CM007 | Public market commentary still treats the broader logistics and private-markets context as active rather than saturated. | Medium | SM005, SM006 |
| CM008 | Public sources do not support a single clean TAM figure, so any sizing should be presented as a bounded range with the underlying assumptions preserved. | Medium | SM008, SM009 |
| CM009 | The practical substitute is still a mix of telematics, spreadsheets, email, and ad hoc carrier management rather than a single integrated control plane. | Medium | SM001, SM002 |
| CM010 | Growth is tied to the economics of loss prevention: theft, damage, and missed production windows are easier to budget for than generic visibility. | Medium | SM001, SM007 |
| CM011 | The adoption path typically starts with a single high-value lane or plant and expands once the buyer sees operational and insurance benefits. | Medium | SM001, SM002, SM008 |
| CM012 | Cargo-security vendors can justify premium pricing when they show measurable recovery, loss avoidance, or premium-savings outcomes. | Medium | SM001, SM008, SM007 |
| CP001 | Tracxn lists Overhaul among a competitor set that includes Risk Ledger, Nulogy, HICX, Aravo, Achilles, and other supply-chain risk and compliance vendors. | Medium | SP001 |
| CP002 | The closest software-only alternatives are project44 and FourKites, which emphasize visibility and orchestration rather than insurance and response. | Medium | SP003, SP004 |
| CP003 | Tive competes on sensor-driven cold-chain and high-value cargo tracking, making it a more hardware-forward alternative. | Medium | SP001, SP003 |
| CP004 | Samsara overlaps on fleet and carrier-side asset tracking, but it is not a cargo-response specialist. | Medium | SP003 |
| CP005 | Descartes MacroPoint and Highway represent fraud and broker-risk substitutes that address a narrower slice of the problem. | Medium | SP003 |
| CP006 | Overhaul differentiates through an integrated stack that includes control-tower operations, risk intelligence, insurance brokerage, and law-enforcement coordination. | Medium | SP004, SP005, SP006 |
| CP007 | FreightVerify expands Overhaul into item-level and manufacturing workflows that pure visibility vendors do not cover as deeply. | Medium | SP006 |
| CP008 | The integrated model creates switching costs because it links shipment data, response workflows, and insurance economics in one operating loop. | Medium | SP004, SP005, SP006 |
| CP009 | The main commoditization threat is that larger visibility platforms can add adjacent exception-management features without carrying the same service burden. | Medium | SP002, SP003, SP009 |
| CP010 | Public competitive evidence still favors Overhaul where buyers want intervention and accountability, not just tracking. | Medium | SP004, SP006 |
| CP011 | The company’s acquisition strategy suggests it is trying to deepen, not narrow, the competitive wedge. | Medium | SP006, SP009 |
| CP012 | Open-source and community signals around the Over-haul GitHub org are too thin to count as meaningful product defensibility evidence. | Medium | SP007, SP008 |
| CI001 | Overhaul monetizes through a B2B subscription platform, insurance brokerage, and monitoring services. | Medium | SI001, SI004 |
| CI002 | The core platform is priced around shipment volume and feature requirements, not consumer-style per-seat licensing. | Medium | SI001, SI004 |
| CI003 | The 2021 Series B, 2025 growth financing, and 2025 Series C show continued capital dependence and investor willingness to fund expansion. | Medium | SI001, SI002, SI003 |
| CI004 | The August 2025 round included MidCap Financial debt, which adds leverage and covenant considerations to the stack. | Medium | SI003 |
| CI005 | Sacra and Tracxn disagree on the total capital raised, which means the public record is not clean enough for precision underwriting. | Medium | SI004, SI005 |
| CI006 | Neither ARR nor gross margin is publicly disclosed, so revenue quality cannot be measured directly from the open record. | Medium | SI004, SI007, SI008 |
| CI007 | The August 2025 round disclosed no valuation, so it is impossible to confirm whether the round was flat, up, or down versus the prior peak. | Medium | SI003, SI007, SI008 |
| CI008 | The services layer likely supports revenue diversification but also lowers pure software gross margin relative to a seat-based SaaS model. | Medium | SI004, SI008 |
| CI009 | Public sources do not reveal burn, runway, or customer concentration, which means the next-round trigger cannot be modeled cleanly. | Medium | SI006, SI007, SI008 |
| CI010 | A debt-augmented financing structure implies there is now a stack behind equity that should be modeled explicitly in returns work. | Medium | SI003, SI007 |
| CI011 | The most credible public signal is continued investor support rather than a fully transparent operating profile. | Medium | SI001, SI002, SI003, SI006 |
| CI012 | Private Funds CFO’s coverage of valuation disclosure risk, alongside Nasdaq Private Market’s secondary-market page, is a useful reminder that public data here is not enough for precision pricing. | Medium | SI008, SI009, SI010 |
| CE001 | The platform is designed around SKU-level visibility, predictive risk intelligence, and proactive compliance monitoring. | Medium | SE001, SE004 |
| CE002 | Overhaul presents live shipments through a control-tower style interface with alerts for cargo theft, fraud, and cold-chain issues. | Medium | SE004, SE001 |
| CE003 | Telemetry inputs include GPS, ELD feeds, temperature, shock and tilt sensors, door events, driver hours, weather, traffic, and crime heat maps. | Medium | SE004 |
| CE004 | RiskGPT is a generative AI tool that turns incident history into plain-language recommendations. | Medium | SE001, SE004 |
| CE005 | The Vision module uses computer vision to validate photo documentation at cargo origins. | Medium | SE001, SE004 |
| CE006 | The product is device-agnostic and supports multimodal tracking across trucks, containers, planes, railcars, and vessels. | Medium | SE001, SE004 |
| CE007 | FreightVerify extends the stack into item-level, SKU, and VIN-sequenced workflows that matter in manufacturing. | Medium | SE003 |
| CE008 | FreightVerify claims over 100 million tracked shipments, 70,000 monthly users, and roughly 280,000 shipping locations. | Medium | SE003 |
| CE009 | The integrated product story links visibility to inventory outcomes and customer impact rather than stopping at shipment location. | Medium | SE003, SE004 |
| CE010 | Overhaul markets insurance savings and risk reduction as part of the product value proposition, which broadens the technical-commercial stack. | Medium | SE001, SE004 |
| CE011 | GitHub activity and other practitioner signals are too thin to prove a large developer ecosystem around the product. | Medium | SE005, SE009 |
| CE012 | Security and compliance posture is not publicly documented at the depth investors would want for a sensitive freight-data platform. | Medium | SE006, SE007 |
| CU001 | Named customers repeatedly cited in public sources include Microsoft, Bristol Myers Squibb, CEVA, and Arvato. | Medium | SU001, SU003 |
| CU002 | The same public sources position those customers in pharmaceutical, healthcare, logistics, and technology verticals. | Medium | SU001, SU003 |
| CU003 | Microsoft provides the clearest public customer proof because Overhaul’s site includes a return-on-investment testimonial. | Medium | SU001 |
| CU004 | FreightVerify’s acquisition adds six of the top ten automotive manufacturers to the customer story. | Medium | SU002 |
| CU005 | FreightVerify also adds roughly 70,000 monthly users and about 280,000 shipping locations. | Medium | SU002 |
| CU006 | FreightVerify says it has tracked more than 100 million shipments, which is the strongest adoption scale signal in the public record. | Medium | SU002 |
| CU007 | The public record still does not disclose renewal rates, churn, or contract duration, so retention quality is not directly measurable. | Medium | SU005, SU006 |
| CU008 | The likely buyer-user-payer split is operations-led with finance and risk validating the purchase. | Medium | SU001, SU003, SU005 |
| CU009 | The customer story is strongest where there is a named logo plus a quoted outcome, not just a list of logos. | Medium | SU001, SU002 |
| CU010 | Public concentration risk remains unknown because top-customer revenue share is not disclosed. | Medium | SU005, SU006 |
| CU011 | Procurement and compliance friction likely matter most in regulated verticals because the product handles sensitive shipment data. | Medium | SU008, SU007 |
| CU012 | A useful diligence packet would include a customer list with production status, usage depth, and expansion history. | Medium | SU001, SU005, SU006 |
| CR001 | Cargo theft is both a market driver and a risk because demand rises when losses rise. | Medium | SR002 |
| CR002 | The insurance brokerage component exposes Overhaul to licensing, compliance, and multi-jurisdiction supervision risk. | Medium | SR001, SR002 |
| CR003 | Sensitive freight data and control-tower operations create cybersecurity and privacy exposure. | Medium | SR003, SR004 |
| CR004 | The August 2025 financing stack adds debt-related covenant and interest risk on top of equity dilution. | Medium | SR005, SR006 |
| CR005 | Customer concentration and contract duration remain undisclosed, which keeps downside risk elevated. | Medium | SR005, SR007 |
| CR006 | The most important operational risk is that human-in-the-loop control towers are labor intensive and hard to scale perfectly. | Medium | SR003, SR007 |
| CR007 | AI output quality risk exists because false positives and false negatives can both create operational losses. | Medium | SR003, SR008 |
| CR008 | The main partner and dependency risks are external data feeds, sensor ecosystems, and logistics integrations. | Medium | SR004, SR010 |
| CR009 | Public financing coverage shows a company still dependent on outside capital to keep expanding. | Medium | SR005, SR008 |
| CR010 | Competitors can narrow the product gap by adding adjacent features, which makes commoditization a genuine threat. | Medium | SR001, SR008, SR009 |
| CR011 | Regulatory and enforcement articles across other industries show that control and documentation burdens are rising, not falling. | Medium | SR001, SR002, SR004 |
| CR012 | A lack of public SOC 2, GDPR, and DPA detail remains a real diligence gap for a company handling sensitive freight data. | Medium | SR003, SR004, SR007 |
| CV001 | The strongest thesis is that Overhaul sells a differentiated control plane for high-consequence freight where losses are expensive. | Medium | SV003, SV006, SV007 |
| CV002 | The anti-thesis is that the company is still opaque on ARR, gross margin, retention, and customer concentration. | Medium | SV001, SV002, SV003 |
| CV003 | Current valuation cannot be pinned down because the August 2025 round disclosed no post-money value. | Medium | SV001, SV002 |
| CV004 | Sacra and Tracxn disagree on total funding, which makes even the capital base somewhat uncertain in public data. | Medium | SV003, SV004 |
| CV005 | The most useful comp anchors are project44, FourKites, Samsara, and the market commentary around private-markets pricing. | Medium | SV002, SV008, SV009 |
| CV006 | The right valuation stance is research-more, not buy, because public evidence is not enough to support precision pricing. | Medium | SV001, SV002, SV003 |
| CV007 | A base-case valuation should be range-based and depend mostly on ARR and margin assumptions, both of which are missing. | Medium | SV001, SV002, SV003 |
| CV008 | A bear case is easy to imagine if services margins stay thin or if customer concentration turns out to be high. | Medium | SV001, SV003, SV009 |
| CV009 | A bull case requires proof of durable retention plus stronger evidence that FreightVerify expands the addressable customer base. | Medium | SV006, SV007, SV014 |
| CV010 | Strategic interest is plausible because the platform sits at the intersection of freight visibility, risk, and insurance. | Medium | SV003, SV006, SV009 |
| CV011 | Private-markets commentary still points to valuation uncertainty rather than a clean public mark. | Medium | SV001, SV002, SV008 |
| CV012 | The most important diligence asks are ARR, gross margin, NRR, debt terms, and customer concentration. | Medium | SV001, SV003, SV005 |