The clause that applies, with its version attached.

• 01

  Coverage questions for adjusters and brokers

  Plain-language questions resolved to the specific clause, endorsement and version that governs the policy in front of them.

• 02

  Claims manual assistance

  Procedure retrieved with its revision date, so a handler follows the current process rather than the one they learned in training.

• 03

  Wording change impact analysis

  New wording diffed against the existing set, with the list of procedures and templates it contradicts drafted for review.

• 01

  The coverage decision stays with a human

  The system extracts, retrieves the applicable wording and drafts the reasoning. An adjuster confirms or overrides, and their reasoning is recorded — which is what a complaints process and an ombudsman will ask for.

• 02

  Version-aware retrieval or nothing

  Every retrieved clause carries its document version and effective date, and queries are scoped by policy inception. Quoting the wrong revision is a regulatory problem, not a UX one.

• 03

  Extraction accuracy is reported per document type

  A typed invoice and a handwritten claim form are different problems. We publish accuracy per type before you decide what to automate.

1. 1

   Data inventory

   What docs / databases / APIs / feeds matter? What's PII vs public? What changes daily vs quarterly? We map it before writing code.

2. 2

   Retrieval architecture

   Hybrid (BM25 + vector) retrieval, chunking strategy, reranking, citations. Tuned for your domain not a generic benchmark.

3. 3

   Eval suite

   Real-world question set with golden answers. Faithfulness, context precision, latency. So you know when changes ship a regression.

4. 4

   Guardrails

   Prompt-injection defense, PII scrubbing, refusal patterns, output schemas. Especially critical for customer-facing deployments.

5. 5

   Production + iterate

   Cost-effective inference (caching, fallback models), monitoring, weekly eval reports. Fine-tune when the data justifies it.

• Guidewire & Duck Creek
• Policy administration systems
• OCR and layout-aware extraction
• Salesforce & Zendesk
• Twilio & WhatsApp Business
• Snowflake
• Document management systems

FAQ

RAG for insurance policy wording: your questions.

• What if two endorsements conflict?

  Both are surfaced with their dates and precedence flagged for a human — the system doesn't arbitrate. In practice, finding these conflicts is one of the more valuable early outputs.

• Can brokers use it too?

  Yes, with a separate index scope and permission set so a broker sees the wording they're entitled to and nothing internal. Same system, different retrieval boundary.

• Should I use RAG or fine-tuning?

  RAG for facts that change. Fine-tuning for style, format, or domain reasoning. Most production systems use both — and we'll tell you which mix is right after a 1-week discovery.

• Can I use my own LLM (open-weights)?

  Yes. We work with Llama, Mistral, Qwen, and similar — useful for data residency, cost predictability, and air-gapped environments.

• AI agents for claims processingAgents that extract from claim documents, chase what's missing, and hand the adjuster a complete file with the coverage reasoning already drafted.Read
• AI governance for insurersRisk classification, model documentation and oversight design for insurance use cases — built around what a complaint, an audit or an ombudsman review will ask for.Read

• RAG for banking and financial servicesRetrieval over circulars, product terms and internal procedure — returning the clause, the revision date, and a link to the page it came from.Read
• RAG for healthcare and clinical documentsRetrieval over clinical guidelines, payer policy and internal SOPs — with the citation, the version, and an explicit refusal when the library doesn't cover the question.Read
• AI product search and catalogue RAGSemantic search and grounded product Q&A over your catalogue, reviews and size guides — with stock and price read live rather than remembered.Read