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Claims & Underwriting
Automate claims and underwriting on data as messy as the real thing.
Validate document intelligence, decisioning and claims-automation vendors against representative synthetic claims, statements and documents, then move straight into beta.
3 days
to a ready environment
25+
synthetic personas & scenarios
0
real records exposed
The problem
Underwriting and claims live or die on edge cases, not averages.
Document AI and decisioning tools demo beautifully on clean inputs and stumble on the fragmented, multi-source reality of real claims. Proving fit means representative data, missing pages, conflicting histories, awkward formats, in an environment you control. NayaOne generates exactly that data and the workspace to test it, so teams reach a confident decision in weeks and step into beta with realistic personas.
What teams prove here
Every test runs in an air-gapped workspace, on representative data, with an evidence pack at the end.
Document intelligence
Compare extraction and classification vendors on synthetic statements, forms and identity documents seeded with real-world mess.
Claims automation
Prototype straight-through claims flows against synthetic claims data and measure accuracy and handling time before rollout.
Underwriting decisioning
Test decisioning and pricing models on synthetic applications, including the edge cases that drive loss and leakage.
Beta with real personas
Move from prototype to pilot users on representative personas, the single biggest blocker removed.
The data
Representative by default. Real only if you choose.
Synthetic datasets come pre-loaded, so evaluation starts on day one with zero exposure.
Synthetic claims & supporting documents
Synthetic bank statements & forms
Multi-persona, multi-scenario health & policy data
Straight answers
Q.
Can the data reflect our lines of business?
Yes. Synthetic datasets are built around genuine personas, scenarios and geographies, including deliberately messy conditions, so representative actually means something.
Q.
How fast can a team start?
Environments stand up in minutes and a tailored synthetic dataset typically in days, so evaluation begins almost immediately rather than after a procurement cycle.
Q.
Does this replace our model governance?
No, it feeds it. You generate the evidence early so governance and validation run on a decision that is already de-risked.
Prove it on your use case.
A 30-minute walkthrough, scoped to exactly what you’re trying to evaluate.