a16z backs FurtherAI with $25M to modernize core insurance workflows
October 7, 2025
FurtherAI raised a $25 million Series A led by Andreessen Horowitz, just six months after a $5 million seed. Total funding now sits at $30 million. It's a clear signal that investors see vertical AI as the practical path to updating a $7 trillion industry that still runs on PDFs, spreadsheets, and disconnected systems.
The AI co-pilot for underwriting, claims, and compliance
FurtherAI positions itself as an insurance-native workspace. Teams can start with a single workflow-submission processing or policy comparisons-and expand across operations without stitching together point solutions.
"Insurance is the backbone of the economy, but the people running it have been stuck with outdated tools," said Aman Gour, Co-Founder and CEO of FurtherAI. "With this funding, we're doubling down on building AI workflows that give underwriters, brokers, and claims teams superpowers."
Early traction and proof points
FurtherAI reports it is processing billions in premiums for clients including Accelerant, MSI, and Leavitt Group. Teams are seeing up to 2x productivity, a 15% lift in submission-to-quote ratios, and proposal generation that is up to 10x faster. Leaders at Leavitt Group cite faster turnarounds, higher accuracy, and a platform they can keep expanding across lines and regions.
Andreessen Horowitz partner Joe Schmidt said the firm views FurtherAI's founders as technical partners to their customers, with early traction that hints at a generational opportunity to transform insurance operations.
Where the new capital goes
FurtherAI plans to expand its catalog of insurance-specific workflows, deepen integrations with carrier and broker systems, and scale go-to-market and customer success to support rising demand.
Why this matters for carriers, brokers, and MGAs
- Reduce manual touch: Triage inboxes, extract data from submissions, and normalize documents without adding headcount.
- Smarter decisions: Structured insights for pricing, appetite fit, and policy comparisons-delivered inside existing tools.
- Faster cycle times: Shorten time from submission to quote and from FNOL to settlement with consistent, auditable steps.
- Compliance at scale: Standardize requirements, produce checklists, and log actions for audit trails.
Practical next steps to capture value
- Pick a high-friction entry point: Start with submission intake, policy comparisons, or FNOL triage. Define "done" in measurable terms.
- Set the data foundation: Map document types, standardize naming, and clarify source of truth for policy, claims, and broker records.
- Integrate where work happens: Connect to your policy admin, CRM, email, and document repositories to avoid swivel-chairing.
- Pilot with clear ROI targets: Aim for metrics like 30-50% reduction in handling time, 10-20% improvement in hit ratios, or cycle-time cuts measured in days.
- Establish governance early: Document prompts, approvals, exception handling, and audit logs; include compliance and legal from day one.
- Upskill your teams: Train underwriters, brokers, and claims handlers on AI-assisted workflows and review protocols.
The bigger picture
Talent shortages, climate-driven loss volatility, and regulatory pressure are squeezing margins. Generic chatbots won't fix document-heavy, rules-bound workflows. Specialized, insurance-native AI that plugs into core systems is the practical path to higher throughput and better risk selection.
If you're building an internal training path for AI-assisted underwriting and claims, explore role-based upskilling options at Complete AI Training.
