What can AI realistically automate in a carrier's claims operation?

The best starting point is the intake and triage layer. That means pulling structured information from FNOL submissions, checking documents against policy terms, and routing claims to the right adjuster or queue automatically. This doesn't replace adjusters. It removes the data gathering that happens before an adjuster makes any decisions. Most straightforward claims can be fully triaged before a human touches the file.

How does the underwriting assistant work with our existing guidelines?

We train the system on your actual underwriting guidelines, appetite statements, and rate filings, not generic insurance data. When a submission comes in, the assistant reads it, pulls out the key risk factors, gets relevant loss history from your claims system, and flags anything outside your current appetite. Underwriters review a structured summary and a recommendation rather than starting from a blank submission. The system doesn't make binding decisions. It gives underwriters better information faster.

How do you handle the compliance and data security requirements?

Compliance and security requirements go into the architecture in week one, not after the build. We design with SOC 2 guidance, add end-to-end encryption, build role-based access controls from the start, and log every data transformation with a full audit trail. For state regulatory work, we bring your compliance team in early, so the system is built to their requirements rather than adapted to them later. We also sign NDAs and BAAs as standard practice.

Will this integrate with our existing policy admin and claims systems?

Yes, we build on top of what you have rather than making you replace anything. We've built integrations with Guidewire, Duck Creek, Applied Epic, and custom policy admin systems. The scope of integration work is one of the things we assess during discovery, and we're honest about what's simple and what will take more time to do properly.

How long does an insurance AI project take and what does it cost?

Four to five months to production. Projects start from $20K and the price depends on scope, integration complexity, and compliance requirements. We quote a fixed price after a discovery call, so you know the total cost before we write a line of code, and it doesn't change based on how long things take us. A payback model is part of what we deliver at the end of discovery, based on your actual volumes and current process costs.

What happens after the project is complete, do we depend on EdgeFirm going forward?

No. At handoff you get complete code ownership, full documentation, and training for your internal team so they can run and extend the system themselves. There's no per-call pricing, no platform fee, and no vendor lock-in. If you want ongoing support, retainer options are available, but the choice is yours. Most clients take the full handoff and come back when they're ready to build phase two.

AI for insurance
that actually ships to production with EdgeFirm

Insurance carriers, MGAs, and InsurTech companies use EdgeFirm to automate claims intake, build underwriting assistants trained on their own policy data, and cut the compliance reporting work that consumes analyst time every quarter. Custom systems, fixed price, production in 4 to 5 months.

Book Strategy Call See How We Build It

Claims intake, underwriting and compliance reporting4 to 5 months from first call to productionYou own the code, no vendor lock-in

In production

What We BuildWhat AI looks like in a working insurance operation

We build insurance AI around the processes that cost you the most, not around what's technically interesting. Everything below ships in 4 to 5 months and comes with full code ownership.

Live operations,ranked in one view.

claims.yourcarrier.com/triage

Claim typeClaimsTrendStraight-through

Auto glass1,28492%

Property waterLive97271%

Auto collision61258%

Travel39884%

Liability24132%

Pet19888%

Commercial15621%

Head-to-head,against your targets.

claims.yourcarrier.com/triage

ClaimSeverityFraudRoute

CLM-48213Low0.04Auto-approve

CLM-48217High0.71Adjuster

CLM-48220Low0.09Auto-approve

CLM-48224Med0.38Adjuster

CLM-48231Low0.02Auto-approve

CLM-48236Low0.11Auto-approve

Every request,routed automatically.

claims.yourcarrier.com/triage

Question typeAnswered bySource

Coverage limitsPolicy assistantPolicy wording

ExclusionsPolicy assistantEndorsements

Renewal pricingUnderwriterGuidelines

Claim statusPolicy assistantClaims system

Regulatory filingCompliance AILedger

What we build

Purpose-built forInsurance & InsurTech.

We build insurance AI around the processes that cost you the most, not around what's technically interesting. Everything below ships in 4 to 5 months and comes with full code ownership.

1First Notice of Loss Through Document Verification

Claims Processing Automation

Automated FNOL intake across web, email, and phone transcripts, with structured data pulled out before an adjuster sees the file
Document verification AI that checks what customers send against policy terms and flags discrepancies automatically
Loss reserve recommendations based on claim details and past patterns, ready for adjuster review
Status update automation so policyholders don't call to ask where their claim is

2Trained on Your Policy Guidelines and Loss History

Underwriting Assistant LLM

LLM-powered assistant that reads submission documents, pulls out key risk factors, and shows relevant loss history, in the same interface underwriters already use
Appetite screening that flags submissions outside your guidelines before underwriters spend time on them
Risk comparison against similar risks in your book, pulled automatically from your past data
Draft endorsement and declination language made from your own templates. The underwriter reviews and approves, and does not write from scratch

3State Filings, Bordereaux, and Reinsurance Submissions

Compliance Reporting Automation

Automated data pipelines that pull from your policy admin, claims, and finance systems into one clean source of truth
Automated generation of state regulatory filings, NAIC submissions, bordereaux, and reinsurance data calls, in the right format
Exception flagging before reports go out, so a human reviews the anomalies rather than re-reading everything
Audit trail built in from the start. Every data transformation is logged and traceable

4Your Policy Library, Actually Searchable

Policy Knowledge Assistant

RAG-based LLM trained on your policy forms, endorsements, coverage guides, and procedure documents
Agents and adjusters ask questions in plain language and get answers sourced from the actual documents, with citations
Customer-facing version that answers common coverage questions, certificate requests, and billing questions without a call center agent
Updates automatically when policy language changes, with no manual retraining needed

Reporting

One clear view,ready for every stakeholder.

Live dashboards and pipelines turn scattered operational data into one picture your team can act on, exportable for leadership.

Claims triage on first notice of loss
Underwriting support from your own policy data
Customer support around the clock
Policy and billing administration

See How We Build It

claims.yourcarrier.com/triage

Claim typeClaimsTrendStraight-through

Auto glass1,28492%

Property waterLive97271%

Auto collision61258%

Travel39884%

Liability24132%

Pet19888%

Commercial15621%

Production stack

Built on Production-Grade InfrastructureThe stack behind insurance AI that actually runs in production

Every system we deliver runs on infrastructure your team can own and extend, no black boxes, no per-seat licensing.

Insurance Systems

Guidewire ClaimCenter / PolicyCenter · Duck Creek Platform · Applied Epic / TAM · Custom policy admin systems via API · Document management platforms

AI & Models

GPT-4 / Claude (policy reasoning) · LangChain / LlamaIndex · RAG over policy & claims documents · Anomaly detection models · Custom fine-tuning where needed

Data & Compliance

PostgreSQL / MongoDB · dbt data transformation · Designed with SOC 2 guidance, hosted on AWS or Google Cloud · Designed for GDPR, CCPA and state requirements · Full audit logging

Infrastructure

Python & FastAPI · React / Next.js · AWS / Azure / GCP · Docker / Kubernetes · End-to-end encryption

Observability & Ops

CI/CD pipelines · Logging & metrics · Error tracking · Uptime monitoring · Automated backups

Full production stack

The models, vector stores, data tooling and infra behind every build.

Common questions

Questions about AI for insurance

: The best starting point is the intake and triage layer. That means pulling structured information from FNOL submissions, checking documents against policy terms, and routing claims to the right adjuster or queue automatically. This doesn't replace adjusters. It removes the data gathering that happens before an adjuster makes any decisions. Most straightforward claims can be fully triaged before a human touches the file.
: We train the system on your actual underwriting guidelines, appetite statements, and rate filings, not generic insurance data. When a submission comes in, the assistant reads it, pulls out the key risk factors, gets relevant loss history from your claims system, and flags anything outside your current appetite. Underwriters review a structured summary and a recommendation rather than starting from a blank submission. The system doesn't make binding decisions. It gives underwriters better information faster.
: Compliance and security requirements go into the architecture in week one, not after the build. We design with SOC 2 guidance, add end-to-end encryption, build role-based access controls from the start, and log every data transformation with a full audit trail. For state regulatory work, we bring your compliance team in early, so the system is built to their requirements rather than adapted to them later. We also sign NDAs and BAAs as standard practice.
: Yes, we build on top of what you have rather than making you replace anything. We've built integrations with Guidewire, Duck Creek, Applied Epic, and custom policy admin systems. The scope of integration work is one of the things we assess during discovery, and we're honest about what's simple and what will take more time to do properly.
: Four to five months to production. Projects start from $20K and the price depends on scope, integration complexity, and compliance requirements. We quote a fixed price after a discovery call, so you know the total cost before we write a line of code, and it doesn't change based on how long things take us. A payback model is part of what we deliver at the end of discovery, based on your actual volumes and current process costs.
: No. At handoff you get complete code ownership, full documentation, and training for your internal team so they can run and extend the system themselves. There's no per-call pricing, no platform fee, and no vendor lock-in. If you want ongoing support, retainer options are available, but the choice is yours. Most clients take the full handoff and come back when they're ready to build phase two.