Solutions · Use case

Claims Summarisation.

Generative AI, scoped to the problem it solves.

Adjuster-ready summaries of claims packets, medical reports, and adjuster notes.

Use-case context

Insurance claims spend more on document handling than on the claim decision itself. Submission packets, medical reports, and adjuster notes are where the unit economics live. Adjusters spend 30-60% of their time reading and re-reading the file before they can act, and that ratio is the lever most carriers want to move. We build summarisation pipelines that produce role-shaped briefs (adjuster, medical reviewer, fraud investigator), each with citation back to the source document and structured extracts (dates, providers, ICD codes, payment ledgers) attached. The summary is generated when a document arrives and refreshed on each new attachment. Measured by adjuster time-to-decision against a control group, factual-correctness rate on summary claims judged by senior adjusters, and omission rate on a checklist of clauses adjusters must not miss. Hallucinated facts are a hard ceiling. We do not deploy claims summarisation as a decisioning system. The summary feeds the adjuster queue, the adjuster makes the call, and every coverage decision still routes through the existing claims-platform workflow. In our coverage footprint this lands first across insurance: the sectors where the data shapes and evaluation criteria line up cleanly with what this use-case actually measures.

Data shape

Submission packets, medical reports, adjuster notes, photographs and estimates, recorded statements transcribed to text, and the claims-platform metadata that frames each file.

Where we draw the line

We do not deploy claims summarisation as a decisioning system. The summary feeds the adjuster queue, the adjuster makes the call, and every coverage decision still routes through the existing claims-platform workflow.

Talk to us about a claims summarisation engagement

A 30-minute call to scope where claims summarisation moves the curve against your evaluation criteria.

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Why work with Veso AI on claims summarisation

Measured

Evaluation, not opinion

Measured by adjuster time-to-decision against a control group, factual-correctness rate on summary claims judged by senior adjusters, and omission rate on a checklist of clauses adjusters must not miss. Hallucinated facts are a hard ceiling.

Proven

Quality you can measure

In the first two weeks we build a labelled evaluation set with your experts, so quality is measured from day one, not hoped for.

Production

Built to operate

We hand over working software, infrastructure-as-code, and an evaluation harness your team can run and maintain.

Related use-cases

FAQ

Claims Summarisation: frequently asked questions

How is success measured for claims summarisation engagements?

Measured by adjuster time-to-decision against a control group, factual-correctness rate on summary claims judged by senior adjusters, and omission rate on a checklist of clauses adjusters must not miss. Hallucinated facts are a hard ceiling. The evaluation harness is part of the deliverable, not an afterthought. We build it during the engagement so your team can run it against the next prompt, model, or pipeline change without us.

Where does Veso AI NOT apply claims summarisation?

We do not deploy claims summarisation as a decisioning system. The summary feeds the adjuster queue, the adjuster makes the call, and every coverage decision still routes through the existing claims-platform workflow. This is a deliberate trust boundary, not a capability gap. We are equipped to build the systems we decline to build, and we decline to build them because the risk-to-value ratio in those surfaces does not justify it.

Which industries does claims summarisation apply to?

In our coverage footprint, claims summarisation most commonly lands in insurance. The specific deployment shape varies by industry: data shapes, evaluation criteria, and regulators differ enough that we re-scope each engagement against the sector it lands in.

What data shape do you need to start a claims summarisation engagement?

Submission packets, medical reports, adjuster notes, photographs and estimates, recorded statements transcribed to text, and the claims-platform metadata that frames each file. In the first two weeks we look at the real data (what exists, what is labelled, where it has to live) and build the plan around what is actually there, not around an assumption.

Which Veso AI services ship claims summarisation?

claims summarisation ships under our Generative AI Consulting, Custom Software Development, AI Integration Services, Data Science & Analytics service lines, depending on the integration surface and the build-vs-platform trade-off. Most engagements draw on more than one. The boundary between consulting, custom build, and integration is a scoping decision we make explicit during discovery.

How does a claims summarisation engagement typically start?

We spend two weeks with your leadership and operators, build an evaluation set with your subject-matter experts, and come back with a clear plan and a clear price. That evaluation set anchors every decision after it (model choice, prompt strategy, retrieval design) so quality is measurable from week one, not from go-live.