Cognaize Makes Unstructured Financial Data Usable.
Accurate, auditable financial data: extracted to your rules, not a generic template.
Financial data lives in documents. Using it is the hard part.
Every institution reads the same document differently: its own definitions, adjustments, and rules. Turning vast amounts of unstructured data into numbers your institution can actually use has always meant a bad trade-off: slow manual work, or automation you can't trust.
Off-the-shelf extraction applies generic definitions. Analysts still end up manually reorganizing the data.
Same document, same prompt, two different answers with no audit trail to determine the correct answer.
Subtotals don't roll to totals.
Cognaize turns financial documents into accurate, structured data your institution can use.
It applies your definitions and verifies every output according to your policies. Every line item is fully auditable.
Your rules, not a template's
Your classifications, your adjustments, on every document.
How your rules get applied →Accurate and auditable
Every output is verified against your rules: no hallucinated numbers, and every check is traceable.
How verification works →Low cost at scale
A fraction of what manual review or general-purpose AI costs.
How the engine works →One platform, applied where unstructured data costs the most.
How it works
Cognaize is neuro-symbolic AI: neural models propose, symbolic models verify against your rules, and a workflow engine loops until every check passes.
failures escalate, not shipped
Built for regulated institutions: run Cognaize in your own environment where required, and keep every output auditable.
See it on your documents.
Request a demo and walk through your use case: your documents, your rules, your systems.
Request a demo