Underwrite agentic AI without asking your client to integrate anything.
Bastion's pre-underwriting assessment probes any client's public-facing AI agent (phone number, chatbot, API endpoint) and produces a risk posture you can price from. No SDK on their side. No friction. The quote gets written. Integration becomes a condition of coverage.
Every MGA writing AI policies in 2026 will need independent telemetry.
The first ones to integrate it will own the category before regulation forces it.
From quote to claim. Bastion is in the loop.
01 — Pre-underwriting
Non-invasive Assessment
Every agentic AI system has an external surface: a phone number, a chatbot endpoint, a public API. Bastion probes it adversarially before your client integrates anything. No SDK. No install. No friction. You get an initial risk posture that prices the policy. Your client gets a preview of their actual failure surface. The quote gets written.
02 — In-force
Active Telemetry Across the Policy Period
Once the policy is bound, Bastion integration becomes a coverage condition. One endpoint change on the client side. From that point, every agent interaction writes structured tamper-evident evidence into a continuously updated posture file. You see the risk profile in real time, not at renewal, not when a claim is filed. When a client's agent starts drifting toward known failure patterns, you know before it becomes your problem.
The same continuous-telemetry model that reshaped cyber underwriting, applied to agentic AI behavior.
03 — Renewal
Dynamic Risk Profile
At renewal, you don't re-underwrite from a questionnaire. You re-underwrite from a policy-period-long evidence trail. Every model update, every prompt change, every behavioral delta is documented and mapped to your risk framework. Clients who ran clean get rewarded. Clients whose risk profile degraded get repriced. Accurately.
Proof Of Model
Active underwriting works. The cyber-insurance industry proved it.
64%
fewer claims vs. industry
2017
continuous-telemetry underwriting since
Cyber carriers underwriting on continuous independent telemetry have, since 2017, run 64% fewer claims than the industry average. The model is simple: continuous independent telemetry produces more accurate pricing, earlier intervention, and better loss ratios than point-in-time assessment.
Bastion brings that model to agentic AI. We don't underwrite. We don't compete with carriers. We produce the independent evidence layer your policy period requires, in a format any carrier panel can consume.
Every deployment makes your underwriting more accurate.
The Data Edge
Bastion leverages Aggregated Risk Telemetry. Our Knowledge Graph identifies emerging "Agentic Failure Classes" across the ecosystem, providing you with Day-Zero protection against logic drift that hasn't even hit your vertical yet.
Ecosystem learning operates on anonymized failure classes, never customer payloads. We don't train models on your data and we don't sell or share it. See data handling.
Bastion sees across every agentic deployment it monitors. Failure patterns discovered in one deployment get tested against all others. A vulnerability class that appears consistently across voice AI agents in clinical settings becomes a pricing signal for every policy in that category. There is no AI liability loss history anywhere in the market right now. Bastion is building it, and every MGA that partners with us gets access to the taxonomy that makes accurate pricing possible.
This edge compounds. The more deployments, the richer the taxonomy, the more accurate the underwriting.
Why independence matters.
Bastion is the independent infrastructure layer that produces the evidence your policy period requires. A carrier cannot underwrite on self-reported logs. The evidence has to come from outside the system being assessed. That independence is what makes the posture file carrier-consumable and what makes claims defensible when they're filed.