FurtherAI Raises $25M to Automate Insurance Workflows
FurtherAI has secured $25 million in Series A funding led by Andreessen Horowitz, bringing total funding to $30 million after a prior $5 million seed round from Nexus Venture Partners, Y Combinator, and others. The focus: automate core insurance workflows with AI so teams can move faster with fewer manual touchpoints.
Why this matters for insurers
Carriers and brokers are stretched by talent shortages, rising climate risk, and tighter oversight. Many AI pilots stall because generic tools miss policy and submission nuances, and point solutions only fix isolated steps.
FurtherAI is building insurance-native workflows that start small and scale across operations, with accuracy and audit trails as first-class features.
What FurtherAI is building
- Workflow automation for submissions processing, underwriting audits, claims handling, and policy comparisons.
- An insurance-native workspace that lets teams start with one workflow and expand steadily across lines and functions.
- Deeper integrations with carrier and broker systems to reduce swivel-chair work and rekeying.
- Built-in accuracy, auditability, and scalability to meet compliance and enterprise standards.
How the new funding will be used
- Expand the library of insurance-specific workflows.
- Deepen integrations with carrier and broker systems.
- Scale go-to-market teams to meet demand.
Practical next steps for carriers, MGAs, and brokers
- Pick one workflow with clear pain: submissions intake, coverage comparisons, or claims triage.
- Define success metrics upfront: cycle time, touch count, accuracy, leakage, and SLA adherence.
- Start with a limited book (one region or product) and a short list of brokers or partners.
- Integrate with your core systems (policy, claims, document management, CRM) and set strict user permissions.
- Establish QA and sampling protocols to validate outputs before scaling.
- Expand to adjacent workflows only after hitting target KPIs for two consecutive reporting periods.
Evaluation checklist
- Document understanding: accuracy on ACORDs, quotes, binders, endorsements, and loss runs.
- Explainability: full audit trails, versioning, and review/approve controls.
- Data safeguards: PII/PHI handling, retention policies, redaction, and role-based access.
- Integration depth: APIs, SSO, and event-based triggers to avoid manual uploads.
- Change management: training, playbooks, and clear handoffs between human and automated steps.
- Governance: model updates, monitoring, exception handling, and regulatory alignment.
KPIs to track
- Submission-to-quote time and manual touch count per file.
- Quote-to-bind conversion and rework rate.
- Underwriting audit findings and documentation completeness.
- Claim cycle time (FNOL to settlement) and loss adjustment expense.
- Straight-through processing rate and exception volume.
What the company says
"We're grateful to partner with leaders across the industry as they modernize operations. Insurance is the backbone of the economy, but the people running it have been stuck with outdated tools. With this funding, we're doubling down on building AI workflows that give underwriters, brokers, and claims teams superpowers - freeing them to focus on the work that truly matters." - Aman Gour, Co-Founder and CEO of FurtherAI
Bottom line
AI that understands insurance documents and workflows can remove bottlenecks without sacrificing control. Start with one high-friction process, define measurable outcomes, integrate tightly, and scale only after proof of value.
Want structured upskilling paths for your team? Explore insurance-focused AI learning tracks at Complete AI Training.
