Putting generative AI to work in insurance operations

A FinTech business working with Cloud Combinator on AWS. The client is anonymised at their request.

The engagement had three focus areas, each a separate proof of concept with its own success measure.

We delivered the three use cases as parallel proofs of concept on a shared Amazon Bedrock foundation, prompt engineering and testing each against the client's own example documents so the outputs reflected their real criteria and language.

All three proofs of concept were delivered and demonstrated against the client's own example documents, giving them concrete, working evidence of where generative AI on AWS can add value across contract review, claims and document processing.

• Contract review proven — Clause by clause classification with a reason and compliance reference for each clause, tested across multiple prompt strategies to tune consistency.
• Claim resolution grounded in precedent — Recommendations that determine fault, coverage and deductibles by referencing similar past cases, not just model generalities.
• Documents made analysable — Reliable extraction of policy and claim fields plus sentiment analysis of correspondence, delivered as clean structured data.
• Explainability by design — Every output pairs a decision with its justification, keeping a human reviewer in control and the result auditable.
• Handover — The client left the engagement with three working reference implementations and the prompt and architecture patterns behind them, ready to inform a decision on production investment.

With the value of each use case demonstrated on their own material, the client are well placed to prioritise which workflow to take from proof of concept to production, building on a governed Amazon Bedrock foundation that can support whatever they take on next.