AI for insurance that actually ships to production
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.
Where Insurance Operations Lose Time and Money
The inefficiencies run deeper than most carriers admit: Every process listed below is one your competitors are starting to automate. The question is whether you get there first or spend the next two years watching your loss ratios suffer while they don't.
Claims Intake Takes Too Long
Adjusters often spend days re-entering information and verifying documents that customers have already submitted. Automating these routine steps speeds up claims and lets teams focus on resolving cases.
Underwriters Spend Too Much Time on Paperwork
Instead of assessing risk, underwriters often review documents and manually enter data. AI can handle repetitive tasks, giving them more time to make better underwriting decisions.
Compliance Reporting Is Repetitive
Quarterly reports require collecting, formatting, and checking data from multiple systems. Automating this process reduces errors and saves valuable time.
Policy Information Is Hard to Find
Important policy details are buried in lengthy PDFs, making it difficult for agents to answer customer questions quickly. AI-powered search delivers the right information in seconds.
Fraud Often Goes Undetected
Fraud indicators already exist in your data, but reviewing every claim manually isn't practical. AI helps identify suspicious patterns early, reducing financial risk.
Customer Support Handles Too Many Routine Requests
Most calls are about claim status, coverage details, or certificates. AI can answer these common questions instantly, reducing wait times and allowing support teams to focus on complex cases.
What We Build: What 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.
Claims Processing Automation
First Notice of Loss Through Document Verification
- Automated FNOL intake across web, email, and phone transcripts; structured data extracted before an adjuster sees the file
- Document verification AI that checks submitted materials against policy terms and flags discrepancies automatically
- Loss reserve recommendations generated from claim details and historical patterns, ready for adjuster review
- Status update automation so policyholders don't call to ask where their claim is
- Typical result: claims intake cycle reduced from 4-5 days to same-day triage on most straightforward cases
Underwriting Assistant LLM
Trained on Your Policy Guidelines and Loss History
- LLM-powered assistant that reads submission documents, extracts key risk factors, and surfaces 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 historical data
- Draft endorsement and declination language generated from your own templates, underwriter reviews and approves, doesn't write from scratch
- Typical result: 40-60% reduction in time spent per submission on data gathering tasks
Compliance Reporting Automation
State Filings, Bordereaux, and Reinsurance Submissions
- Automated data pipelines that pull from your policy admin, claims, and finance systems into a single clean source of truth
- Report generation for state regulatory filings, NAIC submissions, bordereaux, and reinsurance data calls; formatted correctly, automatically
- 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
- Typical result: quarterly compliance reporting cycle reduced from 5-7 days to 1-2, same staff
Policy Knowledge Assistant
Your Policy Library, Actually Searchable
- RAG-based LLM trained on your policy forms, endorsements, coverage guides, and procedural documentation
- Agents and adjusters ask questions in plain language and get answers sourced from the actual documents, with citations
- Customer-facing version that handles common coverage questions, certificate requests, and billing inquiries without a call center agent
- Updates automatically when policy language changes, no manual retraining required
- Typical result: agent handle time on coverage questions cut by 60-70%
THE EDGEFIRM DIFFERENCE
Unlike InsurTech SaaS products:
- • Built on your policy language, not generic training data
- • You own the code and the model; no per-user or per-call pricing that compounds against you
- • Integrates with your actual systems (Guidewire, Duck Creek, Applied Epic) rather than requiring you to export everything to a third-party platform
Unlike large consultancies:
- • 4 to 5 month delivery, not 18
- • Fixed-price engagements scoped on real engineering hours, not sales targets
- • The technical founders write the code; there's no handoff between a sales team and a delivery team
- • Compliance and security built in from week one, not retrofitted
Unlike internal IT projects:
- • We've built production AI systems before; your team doesn't have to figure out what "production-ready" means for LLMs
- • We take on the engineering risk; your team focuses on the business requirements
- • At handoff, your team gets the code, the documentation, and training; not a vendor dependency
Built on Production-Grade Infrastructure: The stack behind insurance AI that actually runs in production
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
- SOC 2 Type II framework
- GDPR / CCPA / state regs
- Full audit logging
Infrastructure
- Python & FastAPI
- React / Next.js
- AWS / Azure / GCP
- Docker / Kubernetes
- End-to-end encryption
Insurance AI Use Cases We Have Shipped: What each system actually addresses
Claims Processing Automation
First Notice of Loss Through Triage
Challenges
- • Manual FNOL intake averaging 4-5 days before an adjuster touches the file
- • Adjusters re-keying information that claimants already submitted
- • No automatic document verification before loss reserve is set
- • Policyholders calling for status updates multiple times per claim
Our Solutions
- • Automated intake across web, email, and phone; structured and ready before adjuster assignment
- • Document verification AI that checks submissions against policy terms
- • Reserve recommendation engine trained on your historical claims data
- • Proactive status update automation across SMS, email, and portal
Typical Results
- • Intake cycle cut from 4-5 days to same-day on standard claims
- • Adjuster time freed from data gathering to actual claim decisions
- • Status call volume reduced significantly with proactive updates
- • Reserve accuracy improved with data-driven recommendations
Illustrative outcomes from comparable deployments. Actual results depend on your data, scope, and use case.
How We Deliver Insurance AI in 4 to 5 Months
Discovery and Data Audit
- Map your claims, underwriting, or reporting workflow end-to-end
- Audit data quality across your policy admin, claims, and finance systems
- Identify the single highest-ROI process to automate first
- Define accuracy targets, compliance requirements, and handoff rules
Deliverable: Technical architecture, data readiness report, scoped project plan
Core System Development
- Build the claims intake, underwriting assistant, or reporting pipeline core
- Integrate with your policy admin and claims systems via API
- Implement human review and escalation logic from the start
- Test against real documents and real claim scenarios
Deliverable: Working system tested on real data from your environment
Integration and Compliance Check
- Connect to all required downstream systems
- Add monitoring, audit logging, and compliance controls
- Pilot with a slice of real claims, submissions, or filings
- Tune accuracy and output format from pilot feedback
Deliverable: Compliance-ready system running on live traffic
Launch and Handoff
- Full rollout with performance monitoring in place
- Accuracy and throughput optimization from production data
- Full documentation, system training for your team
- 30 days post-launch support included
Deliverable: Full launch, 30 days support, complete code and IP ownership
Transparent Pricing for Insurance AI
Typical Investment Range
$75,000 - $175,000
Full project delivery in 4 to 5 months. Fixed price, scoped before we start.
Factors that affect pricing:
System Complexity
Claims intake only versus a full workflow including document verification, reserve setting, and adjuster assignment
Integration Scope
How many systems need connecting, policy admin, claims, finance, document management, and regulatory reporting platforms
Compliance Requirements
Regulated lines of business requiring additional audit trail, access controls, and documentation for state filings or reinsurance
Volume and Lines
Daily claim or submission volume, and whether the system covers one line of business or several with different policy structures
What's Included:
Questions about AI for insurance
The highest-ROI starting point is the intake and triage layer, extracting structured information from FNOL submissions, verifying documents against policy terms, and routing claims to the right adjuster or queue automatically. This doesn't replace adjusters; it removes the 2-3 hours of data gathering work that happens before an adjuster actually 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, extracts the key risk factors, pulls 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 work to SOC 2 Type II standards, implement 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 requiring you to 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 factors we assess during discovery, and we're honest about what's straightforward versus what will take additional time to do properly.
Four to five months to production. Most insurance engagements run $75,000 to $175,000 depending on scope, integration complexity, and compliance requirements. We quote a fixed price after a discovery call, so you know the total investment before we write a line of code, and it doesn't change based on how long things take us. ROI projections are 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, 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.
Built With These Services:
Intelligent Process Automation
The AI systems behind claims intake automation, document processing, and adjuster workflow routing.
Learn MoreCustom LLM & RAG Development
Policy knowledge assistants and underwriting tools built on retrieval over your own documents and guidelines.
Learn MoreAI Automation Agency
The unified data layer connecting your policy admin, claims, and finance systems for compliance reporting.
Learn MoreDecision Intelligence & Analytics
Natural language interfaces over your claims and underwriting data so leaders get answers without waiting for a report.
Learn MoreReady to Transform Your Business with AI Solutions?
Schedule a free strategy call to discuss your project and get a custom AI implementation roadmap.
Or email us directly at hello@edgefirm.io. We typically respond within 2 hours during business days.