SAN DIEGO, CA — Sheryl Sandberg, the former Chief Operating Officer of Meta, has led a $10 million investment round into Self Inspection, a San Diego-based startup seeking to modernize the automotive inspection market through computer vision and artificial intelligence.
The funding round, executed through Sandberg’s family office, Sandberg Bernthal Venture Partners, marks a significant validation for the young software-as-a-service (SaaS) company. The round also drew strategic participation from key automotive industry players, including tire distributor U.S. AutoForce and prominent automotive lender Westlake Financial, alongside early-stage venture funds Costanoa Ventures, Rebellion Ventures, and BrightCap Ventures. Self Inspection was previously backed by DVx Ventures, the investment firm founded by former Tesla President Jon McNeill.
Main Facts: Democratizing Vehicle Inspections with Smartphone AI
Founded in 2021, Self Inspection has developed a proprietary software platform that allows anyone with a smartphone to conduct a professional-grade vehicle damage assessment. The technology is designed to eliminate the need for expensive, specialized hardware, physical inspection centers, or manual appraisals by certified mechanics.
By utilizing the advanced cameras already built into modern smartphones, Self Inspection’s platform guides users through a structured photo-capture process to ensure complete visual coverage of a vehicle. The software then analyzes these images against a massive database of damaged vehicles to identify physical imperfections, calculate repair costs, and generate detailed, body-shop-grade PDF reports.
The startup’s business model targets enterprise clients that manage large volumes of vehicles, including:
- Car rental fleets: Accelerating check-in and check-out processes while accurately documenting new damage.
- Automotive finance companies: Assessing the value and condition of collateral.
- Online vehicle marketplaces and auctions: Standardizing condition reports to build buyer trust.
- Automotive manufacturers (OEMs): Streamlining corporate fleet management and lease-end returns.
A notable early success for the company is its partnership with Stellantis’ financial services division, which currently uses the Self Inspection platform to manage inspections for its corporate-owned vehicles and to process lease-end vehicle returns.
Chronology: From Concept to One Million Inspections
The 2021 Genesis and Early Product Development
Self Inspection was founded in 2021 by CEO Constantine Yaremtso with a clear thesis: the physical infrastructure of the automotive inspection industry was a bottleneck in an increasingly digital economy. Traditional inspections required vehicles to be driven to specific yards, evaluated by human inspectors whose assessments could be highly subjective, or driven through multi-million-dollar imaging gantries.
Between 2021 and 2023, the startup focused heavily on training its machine learning models. The primary engineering challenge was ensuring that unstructured, user-submitted smartphone photos—often taken under varying lighting conditions, angles, and background environments—could yield highly accurate, millimeter-level damage assessments.
Commercial Launch and Enterprise Traction
By late 2023, Self Inspection transitioned from product development to commercial deployment. The company began pitching its API-driven software to rental agencies and automotive remarketing firms. The core selling point was simplicity: instead of forcing users to download a dedicated app, enterprise clients could simply text or email a web link to a customer or field agent. Clicking the link opened a guided web application that used the phone’s native camera, ensuring low friction and high completion rates.
Achieving Scale and Institutional Backing
By early 2025, the platform had achieved critical mass, crossing the threshold of 1 million completed vehicle inspections. This rapid scaling caught the attention of institutional investors and strategic automotive partners. The culmination of this growth was the securing of the $10 million funding round led by Sandberg Bernthal Venture Partners, announced in early 2026, which is earmarked for product expansion and international growth.
Supporting Data: Operational Metrics and Market Landscape
Quantifying the Efficiency Gains
Self Inspection has provided concrete data demonstrating the economic viability of its AI-driven model. According to company disclosures:
- Total Inspections Completed: Over 1,000,000.
- Customer Cost Savings: Exceeding $80 million, driven by the reduction of manual labor, transport costs, and administrative overhead.
- Operational Time Saved: Over 300,000 hours, resulting from the near-instantaneous generation of inspection reports compared to the multi-day turnaround times typical of traditional body shops.
Self Inspection Performance Metrics:
┌──────────────────────────────────────┬─────────────────┐
│ Metric │ Value │
├──────────────────────────────────────┼─────────────────┤
│ Total Inspections Completed │ 1,000,000+ │
│ Estimated Customer Savings │ $80,000,000+ │
│ Operational Hours Reclaimed │ 300,000+ │
└──────────────────────────────────────┴─────────────────┘The Automotive AI Funding Landscape
Self Inspection is part of a broader wave of startups leveraging artificial intelligence to modernize the legacy automotive ecosystem. However, these startups approach the market from distinct angles:
- Conversational and Dealership AI: Companies like Toma and Flai have raised venture capital to deploy AI voice agents and digital assistants designed to improve customer communication and appointment scheduling at dealerships.
- C2B Dealership Bidding: Startups like BidBus are transforming the acquisition process by allowing dealerships to bid competitively in real-time on privately owned used cars.
- Hardware-Intensive Inspections: In the inspection sub-sector, companies like UVeye have raised substantial capital (including a $191 million round) to build drive-through inspection gantries equipped with high-definition cameras and thermal imaging to scan vehicle undercarriages, tires, and bodies.
While UVeye represents an "infrastructure-heavy" approach suitable for fixed locations like dealership service bays and assembly lines, Self Inspection’s asset-light, software-only model positions it to capture the decentralized, consumer-facing segments of the market.
Official Responses: Investor and Executive Perspectives
The investment has drawn strong statements of support from both the lead investor and the startup’s executive leadership, highlighting the perceived market opportunity.
Sheryl Sandberg, speaking on behalf of Sandberg Bernthal Venture Partners, emphasized the transformative potential of establishing a digital "system of record" for vehicle conditions:
“The biggest technology companies are built by transforming industries that are massive, essential, and ready for change. Vehicle condition touches billions of dollars in automotive decisions every year, yet the data remains fragmented. That is changing. We believe Self Inspection will build the system of record that the automotive industry needs.”
Constantine Yaremtso, CEO of Self Inspection, highlighted the democratic and accessible nature of the technology, noting that the ubiquity of high-quality smartphone hardware has made their software-driven approach viable:
“Everyone has a good camera and knows how to capture photos. What we deliver is actually a fully detailed PDF report that you would normally only get from a body shop, which will tell you what labor needs to be done on the damage, how much it costs to repair, how many parts do you need, and so on.”
Yaremtso also noted that for enterprise clients requiring deeper technical diagnostics, the software can ingest data directly from a vehicle’s OBD2 (On-Board Diagnostics) port, marrying external visual data with internal mechanical health metrics.
Implications: The Future of Vehicle Remarketing and Insurance
The successful capitalization and scaling of Self Inspection carry broad implications for several sectors of the automotive and financial services industries.
1. Acceleration of Lease-End and Remarketing Workflows
Historically, the lease-end process has been a major point of friction between consumers, dealerships, and automotive finance companies. Disagreements over what constitutes "normal wear and tear" versus chargeable damage often lead to lengthy arbitration and customer dissatisfaction. By providing an objective, AI-driven baseline that generates a standardized repair estimate instantly, Self Inspection can significantly reduce the dispute rate, lowering administrative costs for lenders like Stellantis Financial Services and Westlake Financial.
2. Disruption of the Insurance Claims Process
While Self Inspection is currently focused on commercial fleets, marketplaces, and finance companies, its technology has clear applications for the auto insurance sector. Traditional claims processing requires field adjusters to physically inspect damaged vehicles, a process that can take days or weeks. Transitioning to a guided, smartphone-based self-inspection model could allow insurers to triage claims, estimate repair costs, and issue payouts within hours of an accident, drastically reducing cycle times and car rental expenses during repairs.
3. Geographical Expansion and International Standards
With the fresh $10 million in capital, Self Inspection has announced plans to expand its operations into Europe. The European automotive market features distinct regulatory environments, vehicle profiles, and consumer habits compared to North America. Establishing a footprint in Europe will require the startup to adapt its machine learning models to localized vehicle models, regional labor rates, and European privacy regulations (such as GDPR) regarding the collection of images that may contain license plates or personal property.
If successful, Self Inspection could establish itself as a global standard for automated vehicle valuation and condition reporting, transforming a fragmented, paper-and-pencil industry into a streamlined, digital-first ecosystem.
