Solutions · Use case
Claims Summarisation.
Generative AI, scoped to the shape of 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 actual claim decisions — submission packets, medical reports, and adjuster notes are where the unit economics live. Adjusters routinely spend 30-60% of their time reading and re-reading the file before they can act, and that ratio is the lever most carriers are trying 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 once per document arrival and refreshed on each new attachment to the file. Measured by adjuster time-to-decision against a control group, factual-correctness rate on a labelled set of summary claims judged by senior adjusters, and omission rate on a checklist of clauses adjusters must not miss. Hallucinated facts in the summary are tracked as 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.
How this shows up across industries
Where claims summarisation lands in production engagements.
Insurance · Generative AI Consulting
See industry →In insurance, the strongest generative AI use cases are claims summarisation, underwriting research, and document classification across submission packets.
Insurance · Custom Software Development
See industry →For insurers, custom software shines in claims, underwriting, and reinsurance workflows where vendor systems force compromises on logic.
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 it lands first
Industries that include claims summarisation in their applicable use-cases.
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 actually moves the curve against your evaluation criteria.
Book strategy callWhy 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 a labelled set of summary claims judged by senior adjusters, and omission rate on a checklist of clauses adjusters must not miss. Hallucinated facts in the summary are tracked as a hard ceiling.
Fixed-fee
After paid discovery
Two-week discovery assembles the labelled evaluation set with your subject-matter experts, then converts into a fixed-fee proposal with explicit gates.
Your repo
Your IP, day one
Code, infrastructure-as-code, evaluation harness, and runbooks land in your accounts — no vendor lock-in on the data, models, or evaluation history.
Related use-cases
Document Intelligence
Citation-grounded retrieval and summarisation over heterogeneous document corpora.
Structured Extraction
Schema-conformant extraction of fields, entities, and tables from messy inputs.
Evaluation Harnesses
Continuous, automated evaluation pipelines for production generative-AI systems.
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 a labelled set of summary claims judged by senior adjusters, and omission rate on a checklist of clauses adjusters must not miss. Hallucinated facts in the summary are tracked as 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. During the paid two-week discovery we map the actual data surface — what exists, what is labelled, what residency posture it carries — and the proposal for the next gate is shaped against that, not against 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?
With a paid two-week discovery: workshops with leadership and operators, an evaluation-set assembled with your subject-matter experts, and a fixed-fee proposal for the next gate. The evaluation set anchors every subsequent decision — model choice, prompt strategy, retrieval design — so quality is measurable from week one, not from go-live.
Industries where claims summarisation applies
Service lines that ship claims summarisation