# Dearborn Labs > AI transformation for insurance carriers, MGAs, and distributors. Built by the team behind Clearcover. ## About Dearborn Labs builds and deploys production AI systems for insurance companies. Founded by Kyle Nakatsuji, CEO of Clearcover, with 8+ years operating AI in insurance at scale. Based in Chicago, IL. Dearborn Labs is not a consulting firm. We are operators and builders who embed with carrier teams to ship AI into production. Our approach: discover your systems and data, build alongside your team, and run the last mile from prototype to production. ## What We Do - AI Claims Intake and Triage: automate first notice of loss and route claims with AI agents - Claims AI Co-Pilot: real-time AI assistant for claims adjusters surfacing policy details and recommendations - AI-Powered Customer Service: resolve policyholder inquiries instantly via AI chat and voice - Automated Policy Administration: handle endorsements, renewals, and policy changes without human intervention - AI-Enabled Digital Distribution: automated quoting, binding, and agent tools powered by AI - Machine Learning Risk Scoring: predictive underwriting and pricing models built on insurance data - AI-Powered Agent Tools: portal automation and producer support tools for independent agents - Insurance Customer Retention: churn prediction and renewal optimization using machine learning - Digital Vehicle Inspection: AI-powered photo damage assessment and claims estimation - Modern Insurance Mobile Applications: digital-first policyholder and agent experiences - Custom Policy Administration Systems: flexible rating engines and modern PAS architecture ## Proof Points These results are from production AI systems at Clearcover: - 91% of claims intake processed through AI agents - 100% of claims employees using AI co-pilots daily - 56% of customer contacts resolved instantly by AI - 3x more efficient claims handling with AI augmentation - 88% of policy changes completed with no human assistance - 93% of policies bound without human intervention ## Launchpad: an AI Insurance Accelerator Launchpad is an AI Insurance Accelerator from Dearborn Labs. We partner with a small cohort of the best MGAs, any line of business, to build the AI infrastructure and workflows they own. The partner pays nothing for the build; Dearborn Labs earns only on measured outcomes such as submissions triaged and claims closed. Inaugural cohort limited to up to 5 MGAs, application-only. Apply at https://dearbornlabs.com/launchpad/intake ## How We Work 1. DISCOVER: Map your systems, data, and operations. Build a transformation roadmap. 2. BUILD: Embed with your team. Connect AI to your data. Deploy to production. 3. TRANSFORM: Launch new workflows. Measure results. Run the last mile. ## Contact - Website: https://dearbornlabs.com - Email: hello@dearbornlabs.com - Location: Chicago, IL ## Key Pages - https://dearbornlabs.com - Homepage - https://dearbornlabs.com/launchpad - Launchpad: an AI Insurance Accelerator for MGAs - https://dearbornlabs.com/launchpad/intake - Apply to Launchpad - https://dearbornlabs.com/origins - Company story - https://dearbornlabs.com/insights - Insights index - https://dearbornlabs.com/insights/read-your-own-workflow-one-verb-at-a-time - Read Your Own Workflow, One Verb at a Time - https://dearbornlabs.com/insights/why-launchpad - Why Launchpad - https://dearbornlabs.com/insights/insurance-ai-last-mile-problem - Insurance Has an AI Last Mile Problem ## Latest Insights ### Read Your Own Workflow, One Verb at a Time (August 2026) Most carrier AI conversations start with the wrong question. "Where should we use AI?" gets answered at the altitude of departments and product categories, where nothing operational ever happens. The useful question is smaller: what are the verbs? Any piece of work is a chain of verbs — a commercial submission breaks into read, check, score, summarize, decide and sign — and each verb points at exactly one capability: a rule, a model trained on your own loss history, a language model, or a person. Naming which link is which is the part orchestration diagrams never did, and it tells you where to spend and where to stop. The method has two honest limits: some "rules" only live in a senior underwriter's head (so the first job is writing them down), and some work ladders all the way to done with no judgment step at all. The verbs that point at a person — decide, negotiate, refer — are the half of the map a rented system can't touch, and usually the more valuable half to have found. Any VP or CIO can run the exercise on one workflow in a single meeting, without a vendor in the room; DL Discovery runs it across an operation over six weeks with operators embedded alongside the team. ### Why Launchpad (July 2026) Great MGAs run a lot of business with lean teams, but the AI build that would compound their advantage is too expensive and slow to ever get to. Launchpad, an AI Insurance Accelerator by Dearborn Labs, closes that gap: Dearborn Labs funds and builds the AI infrastructure and workflows for a small cohort of MGAs, the partner owns what gets built, and the partner pays only when it produces results. The difference from a workflow platform vendor isn't the demo, it's the business model underneath it — rent a shared workflow and your competitor rents the same edge, while owning the build keeps the advantage yours. Dearborn Labs steps into the build-versus-buy slot that used to mean a multi-year consulting project (a client was quoted four years against a conservative four months) because it operated a live carrier for a decade, starts every build from a production library instead of zero, and builds AI-native so systems ship in weeks. These are full production builds funded with Dearborn Labs' own capital, so the inaugural cohort is small and application-only, with applications open through September 8, 2026. ### Insurance Has an AI Last Mile Problem (March 2026) Most insurance AI projects die between prototype and production. Carriers don't lack AI ambition or proof-of-concepts—they lack the operational expertise to move from pilot to deployment. The "last mile" includes systems integration with legacy PAS, regulatory compliance and explainability, workflow design for human-AI collaboration, change management, and edge case handling. Success requires operators who've already solved these problems at scale, not consultants who produce roadmaps but don't ship production systems.