Insurance Claims Automation

A claim doesn't need eight people and three weeks. It needs eight seconds and a rule.

Unmeshed runs FNOL, coverage checks, fraud screening, and adjudication as one governed workflow. AI reads the documents. Rules make the calls that should always be consistent.
Adjusters stay in the loop for anything that actually needs judgment.

Live in WeeksAudit-Ready by DesignSelf-Host or Cloud

Trusted by teams at leading organisations

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The Real Question

Does this step need judgment, or just a rule executed consistently?

Most claims steps, once you ask that honestly, land on the rule side. That distinction is what separates automation a regulator can approve from automation nobody can fully explain.

Needs AI
Reading photos and documents to extract loss details
Classifying an ambiguous or unstructured loss description
Flagging claims with fraud-relevant language or inconsistencies
Drafting a claimant-facing update in plain language
Needs a Rule
Checking policy limits and coverage against the claim
Calculating deductibles and payout amounts
Matching invoices to approved repair estimates
Routing exceptions to the right adjuster tier

Claims Intake

Event Intake and Signal Validation

Claims processing starts with high volume intake. Entry point validation keeps incomplete claims from consuming expensive downstream checks.

  • RULE

    Validate required fields and policy context at entry

  • RULE

    Stop malformed or duplicate claims before they reach adjusters

  • RULE

    Create a stable case ID so every claim stays traceable

Claims Intake Path

Ingest Claim

# claim.ingest

Validate Fields

# Switch

valid
invalid

Assign Case ID

# case.create

Exit

# stop

Risk Enrichment

Parallel Signal Enrichment

Once a claim is accepted, enrichment runs concurrently. Fetching policy history, fraud signals, and third-party risk data in parallel keeps decisions fast.

  • RULE

    Fetch policy, fraud, and history signals in parallel

  • RULE

    Normalize responses into one risk object

  • AI

    Flag inconsistencies in claimant-submitted documents

Parallel Signal Enrichment

Fetch Signals

fan out

Policy History

# policy_lookup

Fraud Signal

# fraud_ai_check

Claim History

# history

Organize Risk Object

Underwriting Decision

Decision Engine for Claim Routing

Underwriting policy changes often. Keeping criteria in decision tables instead of backend code means updates don't require a redeploy.

  • RULE

    Keep approval and denial criteria in editable decision tables

  • RULE

    Route outcomes to auto-approve, manual review, or deny

  • HUMAN

    Send flagged cases to an adjuster with full context

Claim Routing Path

Decision Table

# decide_claim

Auto-Approve

clean claim

Adjuster Review

flagged

Deny

policy violation

Human Review

Human Review for High-Risk Claims

Some claims need adjuster judgment. Human in the loop steps let the workflow wait without custom scheduling code, preserving full context for review.

  • HUMAN

    Pause high-risk claims at adjuster checkpoints with full context

  • RULE

    Resume from the same state when a reviewer acts

  • RULE

    Preserve auditability across long-running investigations

Human-in-the-Loop Path

Ask Adjuster

# wait_for_review

Waiting

Reviewer Acts

async

Resume

# finalize

Unmeshed's Own Deployment

Across a live underwriting deployment, only 9 of 45 capabilities actually needed a model. AI cost per submission dropped from $0.41 to $0.08, an 80% reduction, without losing accuracy on the steps AI was handling.

Same orchestration model, applied to claims: AI on the steps that need judgment, code on everything repeatable.

9/45

Capabilities that needed AI

80%

Lower AI cost per submission

36

Ran as deterministic code

Industry-wide, insurers running a governed automation model this way report claims cycle times falling 30 to 75% and straight-through processing on 70 to 90% of low-complexity claims. (Industry benchmarks — McKinsey 2025, Hiscox/Moody's case study, Ping An reporting. Not Unmeshed customer results.)

Connects to Your Stack

100+ built-in integrations. Plus hosted functions for anything custom.

SlackMS TeamsOutlookGmailSharePointGoogle DriveGoogle DocsGoogle SheetsNotionGitHubTwilioSendGridPagerDutyMongoDBBigQuery+100 more

Inside the Workflow

Four pieces, one workflow.

Decision tables

The rule that keeps showing up, encoded once.

Coverage checks, deductible math, and payout thresholds run as editable rules. Update policy without a code deploy.

Human in the loop

Adjusters review, not re-key.

Standard claims move straight through. Anything flagged routes to an adjuster with an AI-drafted summary, not a blank file.

Fail-safe execution

Recovery is a command, not an incident.

Native hold, skip, and retry on any step, mid-run, without restarting the case from scratch.

Full audit trail

What ran, what data it used, what it decided.

Every step logged automatically, including AI steps. The difference between explaining a decision to NAIC and guessing at one.

Answers to a Regulated Environment

The kind of scrutiny NAIC and NYDFS actually apply.

RBAC

Scoped access controls and reusable roles across your organization.

SSO / SAML

Identity and access management that plugs into what you already run.

Audit logging

Every action, every case, timestamped and searchable.

SOC 2 Type II

Compliant with SOC 2 Type II and GDPR requirements.

Frequently asked questions

Still have questions? Talk to us.

Cut your claims processing costs.

We'll map your current claims workflow, show you exactly where the cost is, and have Unmeshed running in weeks, not months.

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