Claim-grade evidence for AI agent insurance.
GeoClear helps insurers, MGAs, brokers, and enterprises verify what an autonomous agent did, what it was allowed to do, what evidence it used, and when. Denial records, reason codes, outcome records, and escalation outcomes can support future model evaluation, governance, and policy tuning. Verified action outcomes can support future risk and underwriting evaluation.
GeoClear does not verify the AI was right. It provides verifiable evidence that the action followed the approved evidence path before the customer system accepted it.
The problem
Autonomous agents are creating a new liability problem. They can approve refunds, send messages, call tools, move money, access data, and make commitments. When something goes wrong, screenshots, vendor logs, and depositions are not enough. Three things insurers cannot get from those artifacts:
- Tamper-evidence. A log can be edited. An operational evidence record cannot, without breaking verification.
- Policy-period semantics. A screenshot does not know which version of the policy was active at the moment the action ran.
- Independent verification. The insurer's claims team should be able to verify the artifact without depending on the vendor that produced it.
Insurers writing AI-agent liability coverage need evidence that survives disputes, audits, vendor changes, and time.
How GeoClear helps
The same substrate works at three moments in the insurance workflow.
Example claim
Want to walk through this with real cryptography in your browser? The same scenario is wired into a 5-step interactive demo: ▶ run the AI Agent Claim Review demo → (about 7 minutes; nothing leaves your browser; download a real Evidence Bundle ZIP at the end).
An enterprise deploys a customer-support agent. The agent is authorized to answer billing questions and create support tickets. It is not authorized to issue refunds above $500 or make contractual commitments. A customer asks for a refund and threatens legal action.
The agent does three things: promises a $7,500 refund, tells the customer the company accepts liability, and calls the refund API without the required human approval. Now the insurer has to answer: was this covered behavior or outside authorized scope? Three review steps, one independently verifiable bundle.
Tamper test, what a screenshot can't survive
The insurer's reviewer changes the refund amount in the bundle from $7,500 to $500 to test the verification. The operational evidence record no longer matches the recorded payload.
GeoClear does not determine coverage. We preserve the evidence insurers need to review what happened.
The five evidence artifacts
Each artifact is a domain-specific Evidence Bundle or operational evidence record produced on the same platform. The substrate is unchanged; the artifact name maps onto the moment in the insurance workflow.
| Artifact | Insurance moment | What it captures |
|---|---|---|
| Agent Scope Evidence | Pre-bind | Agent identity · authorized + restricted actions · spending limits · data access · approval thresholds · policy version |
| Underwriting Evidence Bundle | Pre-pricing | Governance assessment · adversarial probe summary · security posture · tool access map · risk controls · escalation rules |
| Action Evidence Record | Per high-risk action | Agent identity · tool invoked · arguments · result · policy at action time · approval status · timestamp |
| Customer-Held Evidence Bundle | Post-incident | Scope certificate · action evidence records · policy snapshot · tool calls · approvals (or absence) · verification report |
| Renewal Evidence Summary | Pre-renewal | High-risk action count · escalations · exceptions · drift indicators · control improvements · evidence coverage |
These are packagings of the existing GeoClear substrate, not new primitives. See the developer glossary →
Buyer value
- Faster claim review
- Better underwriting evidence
- Less ambiguity on scope
- Stronger renewal data
- Stronger enterprise trust
- Easier procurement
- Better risk posture
- Evidence for enterprise buyers
- Stronger insurance application
- Faster incident review
- Clear accountability
- Reviewable agent behavior
- Evidence for governance
- Better vendor risk management
- More confidence deploying agents
One platform, multiple operational evidence record profiles
GeoClear is real-time operational evidence record infrastructure for machine-driven systems. AI Agent Insurance is the reference implementation of the platform applied to AI-agent liability evidence. The same evidence-record substrate powers the other record profiles:
- Location Record Profile, physical-presence claims (drone, logistics, IoT).
- Flood & Census Record Profile, mortgage / insurance / secondary-market review.
- Decision Record Profile, AI and rules-based decisions (credit, underwriting, agent actions).
- AI Agent Insurance, claim-grade evidence for insured autonomous agents (this page).
What GeoClear is not
To make the boundary unambiguous: GeoClear is not an insurer, not a broker, not a claims adjuster, not a coverage-determination service. We do not price risk. We do not write policies. We do not approve or deny claims. We do not make legal conclusions about an agent's actions.
What we do: produce customer-held Evidence Bundles that an insurer, insured, broker, regulator, or auditor can independently verify with retained verification material. The insurer determines coverage. We preserve the evidence.
Last updated: 2026-05-06