Claims automation
FNOL to settlement — document intake, coverage checks, reserve suggestions and straight-through processing for clean claims.
Industry
AI for Insurance
Accelerate claims and underwriting with multi-agent review, document intelligence, and controlled automation.
- 82%faster claims cycle times achievable
- 45%of underwriting prep automated
- 100%decision trails for every automated step
Capabilities
AI across the policy lifecycle
Claims automation, underwriting intelligence and fraud detection for insurers.
Underwriting copilots
Submission triage, data enrichment and risk summaries that let underwriters quote more, faster.
Fraud detection
Pattern detection plus investigation agents that assemble evidence and draft referral files.
FNOL and document AI
Extraction and validation across ACORDs, medical records, estimates and correspondence.
How we deliver in insurance
From document chaos to decisions
Insurance runs on unstructured documents and judgment calls. That's exactly the work modern AI does well — with guardrails fit for a regulated carrier.
Claims
Straight-through processing with judgment built in
Clean claims flow from FNOL to payment without touch; complex ones reach adjusters with documents read, coverage checked and a recommended path attached.
- Multi-format document extraction and validation
- Coverage verification against policy terms
- Confidence-based routing between auto and adjuster
Invoice exception workflowRunning
✓Extract invoice fields1.1s
✓Match against PO0.6s
Resolve mismatch with agentrunning
·Post to ERPqueued
Underwriting
Underwriters quoting, not re-keying
Submission packets get parsed, third-party data gets pulled, risk summaries get drafted — so underwriting time goes to pricing risk, not assembling it.
- Submission triage ranked by appetite fit
- Automated enrichment from external data sources
- Draft risk narratives with source links
Copilot
Draft renewal summary for Acme Corp
3 accounts show churn risk — view analysis
Ask anything…
Integrity
Fraud signals with an investigation trail
Beyond scoring: agents assemble claim histories, spot inconsistencies across documents and draft referral packages your SIU can act on immediately.
- Cross-document inconsistency detection
- Network analysis across claims and parties
- SIU referral drafts with cited evidence
✓PII detected & redactedenforced
✓Answer grounded in sourcespassed
✓Role-based data accessenforced
✕Out-of-scope tool callblocked
SOC 2GDPRAudit logHITL
Use cases
Where carriers deploy AI with us
FNOL intake automation
Every channel — email, portal, phone notes — structured on arrival.
Claims adjudication
Straight-through for clean claims, decision support for the rest.
Submission triage
Broker submissions ranked, enriched and routed by appetite.
Policy servicing
Endorsements, certificates and billing queries automated.
Subrogation recovery
Recovery opportunities spotted and demand packages drafted.
Agent and broker support
Product answers and quote support grounded in current filings.
Delivery
Industry-first delivery
Every engagement is grounded in your domain — regulations, operating models, and the use cases that actually move the needle.
- Domain-ready use cases
- Compliance-aware design
- Ops & CX impact
- Reusable industry playbooks
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1
Map the domain
Identify high-ROI workflows and risk boundaries.
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2
Prioritize use cases
Score impact, feasibility and data readiness.
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3
Pilot with guardrails
Ship a controlled production pilot fast.
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4
Scale across ops
Expand to adjacent processes with shared platforms.
Cycle time on auto physical damage went from eleven days to two. Adjusters now open a claim with the documents already read and a recommendation waiting.
Works with your stack
Works with your core systems
Guidewire, Duck Creek and legacy cores — integrated through validated, idempotent connectors with full audit.
- Guidewire
- Duck Creek
- Majesco
- Salesforce
- DocuSign
- Verisk
- LexisNexis
- AWS
- Azure
- Anthropic Claude
- OpenAI
- Snowflake
FAQ
Common questions
Can you integrate with Guidewire / Duck Creek?
Yes — we build against their APIs and event streams, with idempotent writes and validation before anything posts to the core. The core stays the system of record; AI works its queues.
How do you handle claims that shouldn't be automated?
Confidence thresholds and business rules route complex, high-value or sensitive claims to adjusters — with the AI's document analysis attached so the human starts ahead, not from zero.
What about regulatory scrutiny of AI decisions?
Every automated decision carries a reproducible trail: inputs, policy basis, model version and confidence. Unfair-discrimination testing and human oversight points are built into the design.
How fast can we see results?
A scoped claims or underwriting workflow typically reaches production pilot in eight to ten weeks, with measurable cycle-time impact in the first quarter.
Next step
Modernize claims and underwriting
Bring your slowest workflow — we'll show you the automation math within two weeks.