Self Inspection Raises $10M to Turn Vehicle Inspections into Enterprise AI Infrastructure

Self Inspection raised a $10M funding round led by Sandberg Bernthal Venture Partners, with participation from U.S. AutoForce, Westlake Financial, Costanoa Ventures, Rebellion Ventures, BrightCap Ventures, DVx Ventures, and Karim Bousta, former VP of Worldwide Service at Tesla. Headquartered in San Diego, California, the company develops AI-powered Vehicle Condition Intelligence software that enables dealerships, fleet operators, lenders, insurers, rental companies, and logistics providers to perform standardized smartphone-based vehicle inspections.

Founded in 2021 by CEO Constantine Yaremtso and Co-Founder Evgeny Shevelev, Self Inspection's Vehicle Condition Intelligence platform uses guided mobile capture, computer vision, and AI to produce consistent vehicle condition records. The company says it has completed more than 1M inspections, generated more than $80M in customer savings, and returned more than 300K operational hours to customers by replacing one of the automotive industry's most manual workflows.

What Happened

Some industries spend decades optimizing around inefficient processes instead of asking why those processes exist in the first place. Vehicle inspections have lived comfortably inside that category: clipboards, subjective notes, inconsistent photos, repeated inspections for the same vehicle, and endless arguments over scratches, dents, and responsibility.

Self Inspection decided that was not a documentation problem. It was a data infrastructure problem, and the company is treating vehicle condition as a shared enterprise record rather than a one-off operational task.

The new $10M financing will support further development of the company's Vehicle Condition Intelligence platform, deeper AI capabilities, enterprise customer growth, and continued expansion across North America and Europe. The funding follows a 2025 seed round co-led by Costanoa Ventures and DVx Ventures, bringing disclosed funding to at least $13M.

Funding rounds often emphasize the size of the investment, but the more interesting story is usually what investors believe the company is becoming.

Why This Matters

Enterprise AI has matured beyond novelty, and buyers are increasingly asking a more practical question: can artificial intelligence become part of the operating system of the business? Self Inspection's answer is to turn ordinary smartphones into standardized inspection tools capable of producing consistent vehicle condition records across lenders, insurers, dealers, fleets, rental companies, auctions, marketplaces, and service organizations.

Every used vehicle transaction, lease return, insurance claim, fleet audit, rental handoff, repossession, and wholesale auction begins with confidence in vehicle condition. That confidence shapes financing, residual values, insurance exposure, repair costs, operational efficiency, and trust between counterparties.

When every participant creates a different version of reality, disputes become inevitable. When every participant can reference the same trusted inspection record, operational friction starts to disappear.

The company's reported metrics suggest the product is moving beyond experimental AI. More than 1M completed inspections, more than $80M in customer savings, and more than 300K operational hours returned are the kinds of business outcomes that matter to enterprise buyers.

Enterprise customers rarely purchase AI because it sounds impressive. They purchase lower costs, faster workflows, more predictable operations, cleaner data, and better decisions. AI simply happens to be the engine making those outcomes possible.

Market Context

Automotive technology has entered a strange but familiar phase. Much of the industry's attention sits on electric vehicles, autonomy, connected cars, and software-defined transportation, yet all of those markets still depend on operational infrastructure built long before AI entered the conversation.

Vehicle inspections are one of those overlooked layers. Every dealership, fleet operator, rental company, logistics provider, lender, insurer, auction house, and service organization depends on knowing the condition of an asset before money, risk, or responsibility changes hands.

The inspection itself is not the business. Confidence is the business, which shifts Self Inspection from being viewed as inspection software toward becoming a provider of enterprise condition intelligence.

Those are different categories. One sells workflow software, while the other creates standardized data infrastructure that multiple organizations can trust, reuse, and build decisions around.

The platform combines computer vision and artificial intelligence to standardize vehicle condition assessment using ordinary smartphones. That positioning gives Self Inspection exposure to several overlapping markets: automotive AI, fleet technology, dealership software, insurance technology, automotive finance, remarketing technology, and enterprise AI infrastructure.

Competitive Landscape

The inspection technology market is changing as computer vision becomes more accessible within enterprise software. The hard part is no longer proving AI can recognize physical damage. The hard part is earning enough trust for organizations to rely on that analysis during high-value commercial transactions.

That is where execution matters more than product demonstrations. The investor syndicate reflects that view, with Sandberg Bernthal Venture Partners leading the round and strategic investors such as U.S. AutoForce and Westlake Financial participating because inspection quality directly affects their operating environments.

Participation from existing backers and venture firms, including Costanoa Ventures, Rebellion Ventures, BrightCap Ventures, and DVx Ventures, suggests continued confidence in both the technology and the management team's execution. Karim Bousta's participation also brings automotive service experience from his previous leadership role at Tesla Worldwide Service.

Sophisticated investors increasingly look for companies solving expensive operational problems instead of companies simply adding another AI feature to existing software. Self Inspection appears to fit that thesis because the value lies in trusted records, measurable workflow savings, and repeatable enterprise adoption.

What This Signals

Every funding round sends two messages. The first is obvious: capital has been raised. The second is usually more important: capital has chosen a direction.

This investment reflects growing confidence that enterprise AI will be embedded inside operational workflows where accuracy, consistency, and trust influence financial outcomes. Inspection data affects downstream decisions worth billions of dollars annually across automotive ecosystems, and reducing uncertainty within those workflows creates value beyond the inspection itself.

That is why infrastructure companies often compound quietly. Consumers may never recognize their brands, but enterprise customers build processes on top of them, and those businesses become indispensable because they eliminate friction instead of generating attention.

The Bigger Industry Shift

The AI conversation is gradually becoming less about intelligence and more about infrastructure. The winners will not necessarily be the loudest companies. They will be the organizations creating trusted data layers that entire industries depend on.

Self Inspection's vision aligns with that transition. Instead of asking whether AI can inspect a vehicle, the company is asking whether every inspection can become part of a persistent, trusted record that follows an asset throughout its lifecycle.

If the answer continues to be yes, inspections stop being isolated events and become institutional knowledge. That pattern extends beyond automotive into industrial operations, logistics, infrastructure, insurance, financial services, manufacturing, and enterprise asset management.

The next generation of AI companies will not simply automate work. They will become the systems organizations rely on when decisions carry financial consequences, which is a much larger opportunity than digitizing a clipboard.