Avallon AI agents secure $4.6M to automate insurance claims
The industry is facing a talent crunch. Nearly 400,000 insurance workers are expected to leave by 2026, and claims teams are already feeling the strain with backlogs, rising costs, and tougher customer expectations.
Avallon, a New York-based startup, raised a $4.6 million seed round led by Frontline Ventures, with participation from Y Combinator, 1984, Liquid2, and Booom. Their pitch is simple: use specialized AI agents to offload repetitive, manual claims work so adjusters can focus on higher-value decisions.
What Avallon does
These aren't basic chatbots. Avallon's multimodal and voice AI agents run the front line and the back office, then push clean, structured data into your systems.
- Handle intake calls and capture structured FNOL data
- Answer status and billing questions 24/7
- Track case progress and trigger follow-ups
- Contact external parties (e.g., repair shops, providers)
- Summarize medical reports, invoices, and other documents
- Analyze policy terms to flag exposures and next steps
- Integrate with existing CMS platforms and IVR flows
"Our founding team plodded through automotive claims manually for years and knew there had to be a better way," said Cornelius Schramm, Co-Founder and CEO of Avallon. He frames the product for a new economy: move repetitive work to software, free people for judgment-heavy tasks.
Traction you can point to
Since launching earlier this year, Avallon reports 10x revenue growth during its Y Combinator Spring 2025 cohort and signed administrators across the U.S. and Europe, including California's Athens Administrators. Danny Smith, VP of IT at Athens Administrators, called out the team's ability to meet business needs while keeping the customer experience intact, noting the platform's intuitive setup and responsiveness.
The founding team - Cornelius Schramm, Bryan Guin, Moritz Bartusch, and Leander Peter - blends AI, insurance tech, and enterprise systems backgrounds from institutions like Cornell and MIT, and companies including FINN and EY.
Why this matters for TPAs and carriers
Rising claim volumes, higher fraud risk, and a thinning talent bench are squeezing margins. Voice AI that understands claim context and plugs into your current workflows can shorten cycle times, reduce leakage, and improve service levels without a headcount binge.
Will Prendergast, Partner at Frontline Ventures, who will join Avallon as a Board Observer, sees insurance as primed for AI-driven profitability gains - especially for TPAs willing to embed voice agents where the work actually happens.
Scope and roadmap
Avallon started with Workers' Compensation and Automotive, and plans to extend across Property & Casualty lines and into healthcare. The new funding will go toward hiring software and systems engineers and accelerating product depth - more integrations, sharper policy analysis, and broader document coverage.
How to pilot AI agents in your claims operation
- Pick one line of business and 2-3 call types (e.g., FNOL, status, billing) to start.
- Define success up front: average handle time, first-contact resolution, cycle time, CSAT, and leakage reduction.
- Integrate with your IVR and CMS; map data fields so every call updates the record automatically.
- Use human-in-the-loop review for edge cases and policy interpretation during phase one.
- Run a 60-90 day A/B test against a control group; measure savings, service levels, and compliance outcomes.
- Scale to outbound follow-ups (repair shops, providers) once intake is stable.
Bottom line for insurance leaders
The staffing gap isn't going away, and customers won't tolerate slower service. AI agents that actually do the work - calls, updates, summaries, and policy checks - are a direct path to lower cost per claim and faster resolution without sacrificing accuracy.
If you're building internal capability around AI workflows for claims, explore practical training and playbooks for insurance teams here.
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