Solutions / Insurance

Your carrier's AI questionnaire just stalled the deal. Answer it today.

MGAs, TPAs, and insurtechs lose weeks when a carrier's security or AI review hits a wall, usually because the reviewer on the other side has no capacity to work through what you sent. Castle gives the deal owner a packet that checks itself: one command returns a verdict and names any failures, so the carrier reviews exceptions instead of documents. Delivered as a fixed-fee engagement: you hand us the questionnaire, we run the assessment and assemble the packet.

Current status, stated plainly

Castle is built and tested and in early access. It is not yet live-proven with a customer or auditor, and it holds no certifications. Regulatory summaries on this page are for orientation, not legal advice; regime mappings are reference mappings for your counsel to review, not regulator endorsements.

01 / For MGAs & TPAs

The deal is stuck. Here's how it moves.

Delegated authority now comes with AI questions attached: what models and agents run inside the program, what data they touch, who approved them, and what records exist. Answering from email threads and spreadsheets is slow and hard to defend.

Castle gives an MGA or TPA the same machinery a carrier uses: the obligation map drawn from your program agreements and applicable guidance, the AI inventory, the approval trail, and an evidence packet you can hand up the chain. The carrier-delegation pack bundles that into one handoff: attestation packet, exam-readiness export, and the agent and model inventory, framed for the carrier's oversight of AI used under its delegated authority. The goal is that carrier diligence becomes a handoff, and your governance becomes part of why carriers want your program.

And the carrier does not have to take the packet on faith: its own instance, or a free verification node, re-verifies your evidence and countersigns it, so what rolls up the chain is independently verified rather than self-reported. Where delegated authority runs on bordereaux spreadsheets today, this is the verifiable version for AI governance evidence.

02 / Who this is for

The teams that answer for AI in an insurance workflow

  • Carriers using AI or vendor-supplied models in underwriting, rating, claims handling, or fraud detection, and preparing for AI questions in market-conduct exams.
  • MGAs and TPAs that operate AI inside delegated authority, and increasingly receive AI governance, documentation, and audit requirements through carrier program agreements.
  • Insurtechs selling AI-driven products into carriers, where a credible governance story is becoming part of the sale.

A wording we hold ourselves to: the NAIC bulletin addresses licensed insurers. It does not bind MGAs or TPAs directly. The practical pressure reaches them through the carriers and contracts above them, and that is the pressure Castle helps answer.

03 / Why now

The triggers are on the calendar

The carrier whose paper you write on owes its own oversight duty. Under the NAIC Managing General Agents Model Act (#225), an insurer using an MGA is expected to review that MGA's underwriting and claims operations on a recurring basis, and AM Best's rating criteria ask carriers to demonstrate oversight of delegated underwriting authority, including a regular audit programme. That duty sits with the insurer, not with you, which is exactly why the request lands on your desk: the carrier cannot demonstrate what it cannot evidence.

The NAIC Model Bulletin on the Use of Artificial Intelligence Systems by Insurers has been adopted in 25 jurisdictions, 24 states plus the District of Columbia, per the NAIC's implementation tracker (status April 1, 2026, retrieved July 2, 2026). It expects a written program for responsible AI use, governance proportionate to risk, internal controls, and documented oversight of third-party AI and data.

From January to September 2026, the NAIC is piloting its AI Systems Evaluation Tool in 12 states, giving market-conduct examiners a standardized AI-governance checklist. Standardized asks mean the evidence can be prepared in advance instead of reconstructed under exam deadlines.

And independent of any one regulator, carriers that must answer for their AI are pushing documentation, audit, and governance requirements down through program agreements. Whoever you are in the chain, someone above you will eventually ask you to show your governance.

04 / What Castle does

One system from obligation to evidence

You need
Castle provides
A complete, current inventory of AI use and autonomous agents.
The AI use case and agent registry: purpose, risk tier from fixed rules, owner, declared tools and data access, mapped controls and obligations.
The obligations that apply to insurance AI, mapped to your systems.
Insurance obligation libraries for the NAIC AI Model Bulletin, NYDFS CL-7, Colorado SB 21-169, Texas TDI Bulletin B-0036-20, and the EU AI Act, shipped as reference mappings your counsel can review.
Governance decisions that are consistent and documented.
Deterministic policy decisions from rules you can read, with human sign-off gates, named owners, and an exceptions register.
Control of what agents actually do, beyond what they are supposed to.
Runtime enforcement at the action boundary: allow, deny, and block decisions recorded on a tamper-evident hash chain. How enforcement works.
Evidence a carrier, auditor, or examiner can verify independently.
Signed evidence packets with a Merkle manifest, verified by the standalone castle-verify tool on the recipient's own machine. One command, castle insurance examiner-packet, bundles the packet, that verifier, and a verify-first 00-START-HERE.md cover sheet into a single portable deliverable the examiner checks offline, without installing Castle.
Proof the model behaves, not a checklist of controls.
First-party model validation: a battery for bias and fairness (disparate impact), grounding, robustness, and drift, emitting pass/fail results mapped to NAIC bias-testing and SR 11-7 obligations, stamped into the same signed evidence packet. You validating your own models, not an independent audit.
Proof your content guardrails actually fired.
Castle ingests your NeMo Guardrails / Llama Guard / Presidio rail decisions (toxicity, PII, jailbreak) as obligation-mapped, verifiable evidence tied to market-conduct duties. Governing your guardrails, not running them.
A dry run before the examiner's checklist arrives.
The exam simulator: a response package structured to Exhibits A through D of the NAIC AI Systems Evaluation Tool 4.0 exposure draft (use quantification matrix, governance checklist with a citation column, per-model detail sheets, data provenance rows), assembled from live registry data with explicit "requires insurer input" placeholders, never fabricated values. One command, castle insurance examiner-packet, emits it as a single portable deliverable, optionally one ZIP, with a signed Merkle attestation and the bundled standalone verifier. Structured to the Tool 4.0 exposure draft as publicly posted by the NAIC; the exposure draft is in active revision and states may customize it. Preparation material, counsel reviewable, not regulator endorsed.
The pack your carrier asks for under delegated authority.
The carrier-delegation pack for MGAs and TPAs: attestation packet, exam-readiness export, and the agent and model inventory, framed for the carrier's oversight of AI used under its delegated authority.
Partner evidence the carrier can trust without taking anyone's word.
Countersigned evidence chains: the carrier's instance, or a free verification node (castle countersign serve), re-verifies the MGA's packet and signs a receipt bound to its exact bytes; receipts aggregate into one offline-verifiable Transparent Statement, and an oversight report summarizes coverage across the delegation chain. Aligned to the IETF SCITT architecture (published as RFC 9943).
What happens when a producer's evidence fails.
A fix loop with proof, not a ticket queue: each failing producer gets one tracked exception with a named owner and a cure date, a deterministic cure notice held behind a human approval gate before anything is sent, monitoring that flags producers past their cure window, and closure only by a resubmission that verifies clean, recorded with the closing artifact's hash. The oversight report separates what is still owed from what is already proven closed.
Where each jurisdiction stands on the NAIC bulletin.
A jurisdiction-by-jurisdiction adoption record inside the product, with each instrument and date source-dated, plus a content-currency check that flags staleness. Kept current to public sources as of the recorded dates; not legal advice.
05 / Where this goes next

The one-off answer becomes the standing oversight record.

Answering one questionnaire is a transaction. What the carrier actually needs is a repeatable way to show how it oversees the AI running under its delegated authority, every review cycle, across every producer writing on its paper. Castle's oversight report aggregates the evidence each producer submitted into one view, re-verifying every artifact from the artifact itself and reporting failures verbatim rather than smoothing them over. It is an evidence view over cryptographic facts, never a compliance determination.

A note on scope, because the word matters in this market: this is the bordereaux replacement for AI governance only. Castle does not process premium or loss bordereaux and is not a delegated-authority platform, a policy administration system, or a substitute for one. It governs the AI and produces the proof, alongside whatever runs your bordereaux today.

The same evidence graph becomes your market-conduct exam preparation later, with no rework. For the full treatment of what examiners ask and exactly what Castle exports for each ask, read the exam-readiness guide.

Read the exam-readiness guide

06 / Next step

See it on your own program

Watch the real product authorize, deny, and block in under ninety seconds, then bring us one program agreement or AI use case and we will walk the full pass live.

Watch the demo Talk to Castle