AI Agents for Insurance
FISTA Solutions builds insurance AI agents that clear document and intake backlogs: submission triage against appetite, loss-run and ACORD extraction, claims summarization, coverage research, and subrogation screening. Agents produce cited evidence; licensed underwriters and adjusters make every coverage and pricing decision.
- 150+
- projects delivered
- 50+
- companies served
- 99.9%
- verified uptime
- 47%
- efficiency gains
- 12+
- countries reached
What we build
What can AI agents do in insurance?
Insurance agents triage inbound submissions against appetite, extract loss runs and ACORD forms into structured data, summarize claims with timelines and open questions, retrieve coverage language for questions, screen claims for subrogation potential, and assemble renewal packets.
- 01
Submission triage agent
Reads inbound submissions, extracts risk data, checks appetite rules, and routes or declines with the reasoning recorded.
Underwriting - 02
Loss-run extraction agent
Turns loss runs and ACORD forms into structured history with page-level citations for underwriter verification.
Data - 03
Claims summarization agent
Produces a claim summary with timeline, coverage questions, and outstanding items so adjusters start informed.
Claims - 04
Coverage research agent
Retrieves relevant policy language and prior interpretations, quoting form text rather than paraphrasing it.
Coverage - 05
Subrogation screening agent
Flags recovery potential from claim facts and prepares the referral packet for the subrogation team.
Recovery - 06
Renewal preparation agent
Assembles exposure changes, loss history, and open items into a renewal packet for the underwriter's review.
Renewal
Requirements
What guardrails do insurance agents need?
Insurance agents work on documents that drive regulated decisions, so guardrails focus on evidence and authority: every extracted value cites its page, licensed staff decide coverage and price, appetite rules are explicit configuration, and every run is reproducible for later examination.
| Guardrail | Why it matters here | How FISTA implements it |
|---|---|---|
| Licensed decisions | Coverage, pricing, and claim denials require licensed judgment. | Agents recommend with evidence; the licensed decision-maker is recorded on every outcome, and no autonomous denial path exists. |
| Evidence citation | Extracted data becomes the basis for pricing. | Page-level citations per field, confidence scores, and human review below the agreed threshold before values are used. |
| Appetite as configuration | Triage rules change and must be reviewable. | Appetite and routing rules held as versioned configuration your underwriting leadership can read and change. |
| Reproducibility | Decisions may be examined years later. | Versioned prompts, models, and rules with retained inputs and outputs, exportable per submission or claim. |
| Fair claims practice | Timelines and communications are regulated. | Deadline tracking per jurisdiction, drafted communications reviewed by staff, and audit trails on every status change. |
Where AI fits
Which insurance workflow should you automate first?
Start with submission triage or loss-run extraction. Both are pure document work with an existing human reviewer, a measurable backlog, and no direct coverage authority, which makes them the safest place to prove accuracy and speed.
- 01
1. Pick the document queue
Submissions and loss runs arrive constantly and are already read by people, so the agent changes throughput, not authority.
- 02
2. Build the labeled set
Take a representative sample of your own documents and label the fields, so accuracy is measured rather than estimated.
- 03
3. Set the review threshold
Decide with underwriting leadership what confidence level routes to human review, and tune the threshold against cost of error.
- 04
4. Run alongside the team
Compare agent output to underwriter and adjuster work on live volume before the agent's output is used directly.
- 05
5. Expand by line and jurisdiction
Add lines and states as accuracy holds, since forms and rules differ enough that each expansion deserves its own evaluation.
Cost and timeline
How much does an AI agent for insurance cost, and how long does it take?
Cost is driven by document variety, line and jurisdiction count, and integration with policy administration; timeline by system access and underwriting review cycles. FISTA does not quote blind: the scoping call returns an agent design and a phased estimate.
Document diversity is the cost driver. Commercial submissions arrive as PDFs, scans, spreadsheets, and email bodies with no consistent structure, and accuracy across that mix is earned through iteration against labeled data rather than assumed from a demo.
Line and jurisdiction expansion multiplies evaluation work, not just configuration. Each new line brings different forms, exposures, and rules. FISTA scopes expansion as its own phase with its own evaluation, so accuracy does not silently degrade as coverage widens.
Send the scope you have, even if it is a paragraph. You get a written brief, an architecture sketch, and a phased estimate before any commitment.
Get a scoped quoteDelivery
How does FISTA deliver an AI agent into production?
FISTA delivers agents in four gated phases: a discovery sprint that picks the workflow and writes the agent specification, a design that names tools, permissions, and approval points, a build with an evaluation harness and shadow runs on real work, and a production release with traces, dashboards, and rollback.
- 1
Select and specify
Choose the workflow with a measurable outcome, map its systems and edge cases, and write the agent spec with success metrics.
OutputAgent specification, golden test set
- 2
Design the guardrails
Tool inventory with least-privilege scopes, approval gates, escalation paths, data handling, and the evaluation plan.
OutputTool and permission matrix
- 3
Build and shadow-run
Implement tools as MCP servers or connectors, iterate against the evaluation harness, and run in shadow mode on live inputs.
OutputShadow-mode results, eval scores
- 4
Release and observe
Graduated rollout, full traces, cost and quality dashboards, on-call runbook, and a change process that re-runs the evals.
OutputProduction agent with SLOs
Why FISTA
Why choose FISTA Solutions to build your insurance agents?
FISTA builds insurance agents that produce verifiable evidence rather than opinions, keep appetite rules readable by underwriters, and leave every licensed decision with the licensed person. Work is contracted through a US entity with full IP assignment.
Insurance specifics
- Every extracted field quotes the source page, so underwriters verify rather than trust.
- Appetite and triage rules live as versioned configuration your leadership can read and change without an engineer.
- Coverage, pricing, and denial authority never sits with an agent, and the record names the decision-maker.
- Accuracy is measured per line and jurisdiction before expansion, because forms and rules differ materially.
How FISTA engineers
- Spec-Driven Development: every deliverable starts as a written specification with acceptance criteria, so scope is testable before it is built.
- AI-native delivery: engineers direct coding agents under review gates and evaluation harnesses, compressing build time without loosening verification.
- Official Anthropic partner, with production experience across Claude, OpenAI, Google, and open-weight models, chosen per workload rather than by default.
- One accountable delivery lead, weekly demos on your environment, and code in your repositories from week one.
What you get as a client
- 150+ projects delivered for 50+ companies across 12+ countries since 2017, with 99.9% verified uptime on systems we operate.
- A US entity (FISTA Solutions Inc., Wilmington, Delaware) for contracting, invoicing, and IP assignment, with an engineering center in Faisalabad, Pakistan for cost-efficient senior capacity.
- US business-hours overlap for standups and reviews; written decision logs so nothing depends on a meeting you missed.
- Flexible engagement: fixed-scope build, embedded forward deployed engineers, or a dedicated team that you can scale month to month.
Clear answers
What teams ask before deploying agents.
Straightforward guidance for evaluating scope, fit, and the next step.
01Can an agent underwrite a risk end to end?
Not in a FISTA deployment. Agents extract, enrich, check appetite, and prepare the file with evidence; a licensed underwriter makes the accept, decline, and pricing decisions, and the record captures who decided and on what basis.
02How accurate is loss-run extraction?
It is measured, not claimed: a labeled sample of your own loss runs establishes field-level accuracy, and anything below the agreed confidence threshold routes to human review. Clean carrier PDFs perform better than scanned faxes, which is why your real mix defines the target.
03Can agents handle claims intake?
Yes — capturing FNOL details across channels, structuring the information, and summarizing the file for the adjuster. Coverage determinations and payments remain with licensed staff, with jurisdictional timelines tracked and alerted.
04How do you handle multi-state rules?
Jurisdiction rules are configuration rather than code, and each state's forms and timelines are evaluated before the agent operates there, so expansion is deliberate and measurable rather than assumed to transfer.
05Can this work for an MGA or brokerage?
Yes. Submission triage, market matching, and renewal preparation are often more valuable to MGAs and brokerages than to carriers, because the document volume per staff member is higher.
06How long until an insurance agent is useful?
Document agents typically reach shadow mode within weeks and supervised production within a quarter, depending on document access and underwriting review availability. Discovery dates those dependencies.
Continue exploring
Related capabilities
Scoped in writing before you commit
Read every submission the day it arrives.
Bring the submission inbox, the loss-run backlog, or the claims queue. The scoping call returns an agent design, an accuracy plan, and a phased estimate.