Claims Triage Agent
Performs first-pass claim review, coding and routing with mandatory human review.
The problem. Claim triage is a queue problem: cycle time is driven by how fast a human can assemble the facts, and inconsistent first-pass decisions create rework, leakage and audit exposure.
The agent assembles the claim — documents, policy terms, coverage and prior history — applies the medical or policy rules, and proposes a disposition with a written rationale.
It codes, sets severity, flags missing evidence and routes to the right queue, so the human reviewer starts from a complete, structured case.
No denial, adverse determination or payment is ever issued by the agent; a qualified human reviews every one.
Reviewers spend most of their time assembling facts, cycle time runs into days, and first-pass consistency varies by reviewer.
Reviewers open complete cases with a proposed disposition and evidence, and decide rather than assemble.
Where this agent sits in the stack.
Agents that take action need more than a model — they need tools, policy, approvals and an audit trail wired in from the first workflow.
- 01
Task intake & channels
Requests arriving from chat, email, queues, forms, tickets and events — normalised into work items with owner, priority and SLA.
- 02
Agent runtime
Planner, memory, tool registry and evaluation loop, with deterministic guardrails on what each agent may attempt and when it must stop.
- 03
Tools & actions
Typed API actions against CRM, ERP, ITSM and core platforms, each with auth scope, rate limits, idempotency and rollback behaviour.
- 04
Human-in-the-loop
Approval checkpoints for regulated or high-value steps, exception queues and a reviewer console with full reasoning and evidence.
- 05
Systems of record
The transactional systems the agent updates — records written once, reconciled, and traceable back to the triggering request.
Integration surface
- Claims adjudication platform
- Policy administration
- Medical or underwriting policy content
- Document capture and OCR
- Workflow and queue management
Guardrails & human oversight
- Mandatory human review before any denial or adverse determination — no exceptions.
- Rationale, evidence and policy citation attached to every recommendation.
- Every action outside policy stops at a reviewer queue with the agent's reasoning, evidence and proposed change attached.
- Confidence thresholds route ambiguous cases to a senior reviewer rather than a default outcome.
What has to be true first
- Structured access to claim, policy and document data.
- Written medical or underwriting policy the agent can be evaluated against.
- A labelled sample of historic decisions for the evaluation set.
Security, data & compliance
- HIPAA-aligned handling with a signed BAA where PHI is in scope.
- Customer and employee data stays inside your tenancy and region; no training on your data by default.
- PII is redacted before it reaches a model, and prompts, responses and tool calls are retained under your retention policy.
- Every tool call, input, decision and system write is logged and replayable for audit and model-risk review.
How this agent reaches production.
Weeks 1–3 · Scope
Claim-type selection, policy capture, evaluation set built from historic decisions.
Weeks 4–8 · Build
Document assembly, rule application, rationale generation, reviewer console.
Weeks 9–12 · Production pilot
Shadow mode then live with 100% human review and agreement-rate tracking.
Quarter 2+ · Scale & run
Additional claim types with model-risk governance and audit reporting.
What we agree to be measured on.
Ranges drawn from comparable production engagements. Your baseline is agreed before build starts, and the same numbers are reported after go-live.
| Metric | Expected range |
|---|---|
| Claim triage cycle time | 40–65% faster |
| Reviewer agreement with the proposed disposition | 85–95% |
| Rework from incomplete cases | 30–50% lower |
| Audit findings on reviewed decisions | No increase — evidence attached to every case |
Model the business case: Insurance Claims AI ROI calculator →
One claim type in shadow then live with 100% review, measured on agreement rate and cycle time.
Fixed-price scope · milestone billing · price on request.
Multi-claim-type coverage with model-risk governance, drift monitoring and audit reporting.
Retained pod · quarterly outcome review · price on request.
The full Claims Triage Agent specification, as a PDF.
A multi-page specification your architecture, security and procurement reviewers can read without a call: what the agent does, the architecture, the integration surface, autonomy and guardrails, security posture, rollout plan, measurement plan and engagement shape.
- Process before and after, with the decision that stays with a human
- Layered architecture diagram and named integration surface
- Guardrails, approval gates, escalation and audit trail
- Security, data handling and compliance posture
- Phase-by-phase rollout and the measurement plan
The Agentic Process Automation Playbook: Replacing Legacy RPA
A migration playbook for enterprises moving from brittle, screen-scraping RPA to agentic AI that reads documents, handles exceptions, makes judgment calls and integrates with existing systems. Includes a retire-vs-replace decision tree, governance controls and the ROI case for finance and operations leaders.
Read the playbook →- FNOL intake agent that assembles adjuster-ready claims
35% lower intake cost per claim · 2x faster claim assignment
- Attachment agent for claims adjudication
40–60% shorter cycle time on attachment-blocked claims · 25% fewer SLA breaches
- Prior-authorization agent that submits and follows up
60% fewer manual touches per authorization · clinical hours returned to care
Get a written estimate for the Claims Triage Agent.
Tell us the process, the systems it touches and the compliance scope. We come back with a scope, a measurement plan and a written estimate — no published band that would not apply to you.
solutionClaims Triage Agent — routed to this team
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