Insurance

Where a decision carries loss and liability.

AI is moving through underwriting and claims faster than the controls around it. The decisions that matter — a risk flagged before a policy binds, an exception outside the model's confidence, a claim recommended for denial — still need a qualified person to own them. HumanAgent routes those decisions to a reviewer and returns a named, attributed record of who decided and why.

Get a demo →

How it works.

01
Your workflow or AI agent sends the decision
02
We route it to a qualified reviewer
03
They decide in a structured form
04
You get the decision plus a verifiable record

Use cases.

Pre-bind risk sign-off

Your model flags a property hazard. A reviewer confirms the risk and the mitigation before the policy binds.

  • Reviews the flagged hazard against inspection photos, reports and third-party data
  • Verifies claimed mitigation is documented and credible
  • Issues bind, bind with conditions, or decline
  • Documents reasoning for the underwriting file
Typical budget $15–75 per propertyTalk to us →

Claims exception review

Your AI clears the routine claims. A reviewer handles the ones that don't fit the rules.

  • Reviews claim detail against policy terms and coverage limits
  • Assesses whether the circumstances warrant an exception
  • Checks documentation completeness
  • Approves, denies, or requests more information
Typical budget $15–75 per claimTalk to us →

Site & property verification

Data compiled by a model, confirmed by a person before it's relied on.

  • Confirms flagged points against source: power, water, zoning, ownership, flood
  • Corrects any value that doesn't match
  • Returns a verified or flagged result
Typical budget $15–75 per siteRequest this review →

Policy data verification

Fields extracted by AI from a policy document, confirmed against the source.

  • Checks extracted values against the original document
  • Flags and corrects mismatches
  • Works in the document's own language
Typical budget $10–50 per policyRequest this review →

Policy underwriting review

Borderline risk scores get a human decision instead of an automatic one.

  • Reviews the score and the submission behind it
  • Decides approve, decline, or adjust terms
  • Records the reasoning
Typical budget $10–75 per applicationTalk to us →
Regulatory

Aligned with the NAIC Model AI Bulletin, adopted in 24+ states, and state requirements for human oversight of AI-assisted insurance decisions.

Don't see your use case?

If a decision in your workflow needs a qualified person to own it, we can route it. Or read how the API works.

Get a demo →API docs →