Multi-agent claims review
Intake, coverage, fraud-screen and settlement agents coordinated by a supervisor with human gates.
Insurance · Case Study
Claims Automation Platform
A multi-agent claims platform that extracts evidence, checks policy rules, flags fraud signals, and routes exceptions to adjusters.
- 82%faster claims processing
- 64%straight-through on clean claims
- 100%of decisions with audit trails
Delivered
What we built
82% faster claims processing with multi-agent review for a leading insurer.
Document intelligence
ACORDs, estimates, medical records and correspondence extracted and validated automatically.
Policy rule grounding
Every decision grounded in the policy wording that authorizes it — cited and checkable.
Exception workflows
Complex claims routed to adjusters with analysis attached and full context preserved.
Inside the build
From eleven days to same-day
A specialty insurer drowning in claim documents needed speed without sacrificing control. Here's how the platform delivers both.
The challenge
Growth outpacing the claims team
Claim volume had doubled in three years while cycle times stretched past eleven days. Adjusters spent most of their day reading documents and re-keying data instead of exercising judgment — and every attempt at rule-based automation had shattered on document variety.
- 11-day average cycle time and rising
- 70% of adjuster time on document handling
- Previous RPA attempt abandoned after format changes
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The solution
Agents that read, check and decide — with gates
A supervisor agent orchestrates specialists: document extraction, coverage verification against policy wording, fraud screening and settlement calculation. Clean claims flow straight through; anything ambiguous reaches an adjuster with the analysis already done.
- Supervisor topology with four specialist agents
- Deterministic validation between every hop
- Confidence-based routing with human approval gates
Shared stateHandoffsRetriesTraces
The impact
Faster for customers, calmer for the team
Cycle time fell 82% overall; clean claims settle same-day. Adjusters now work the genuinely complex cases — and regulator questions get answered with decision trails, not reconstructions.
- 82% cycle-time reduction in six months
- Adjuster capacity redirected to complex claims
- Full audit trail accepted in regulatory review
−62%p95 latency
Before
3.4s
After
1.3s
Cost / 1k tasks
$41
Optimized
$14
Outcomes
What changed for the business
Customer experience
Same-day settlement on clean claims transformed NPS.
Team capacity
Doubled volume absorbed without headcount growth.
Loss-adjustment expense
Cost per claim down by more than a third.
Fraud posture
Screening on 100% of claims instead of samples.
Compliance confidence
Every decision traceable to policy wording.
Platform foundation
Same infrastructure now powering underwriting intake.
Delivery
From challenge to outcome
We publish the architecture decisions, delivery approach and measurable results — so you can see how similar outcomes could apply to your enterprise.
- Measurable KPIs
- Architecture transparency
- Cross-industry patterns
- Repeatable playbooks
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1
Challenge
Business pressure, legacy process and constraints.
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2
Solution
Architecture, agents and integration design.
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3
Delivery
Build, evaluate, secure and launch.
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4
Impact
Efficiency, cost, quality or revenue outcomes.
Adjusters used to open a claim and start reading. Now they open it and start deciding. That's the whole transformation in one sentence.
Under the hood
The stack behind the platform
Deployed in the carrier's private cloud, integrated with their core systems.
- Anthropic Claude
- LangGraph
- Temporal
- Guidewire
- AWS
- Postgres
- Pinecone
- Datadog
- Terraform
- Kubernetes
FAQ
Common questions
How long did this take to deliver?
Ten weeks to production pilot on one claim type, then progressive expansion across lines over two quarters — each expansion gated on eval scores and adjuster feedback.
What claims does it decline to automate?
Anything below confidence thresholds, above severity limits or matching sensitive criteria routes to humans automatically — with the analysis attached so no work is wasted.
Could this work for our claims operation?
If your claims involve document reading, coverage checks and repeatable decisions — very likely. A two-week assessment against your claim mix gives you the honest answer.
Next step
Want claims numbers like these?
Bring your cycle-time data — we'll show you what the same architecture would do for it.