Verifin
The numeric-trust layer for AI finance.
Verifin independently checks every consequential number and claim produced by an AI finance system. It recomputes from source, catches period and unit errors, cites provenance, and holds low-confidence output for human review.
“Net burn fell 18% to $214k in Q3.”
Original output blocked. Corrected figure is ready for approval.
Illustrative verification flow. Dedicated verifier model is planned.
One wrong number erases every right answer.
General-purpose models can write convincingly while silently misreading a period, unit, or table. Verifin is designed as an independent critic—not the same model checking its own work.
Derive the figure again from source.
Verifin checks the ledger and connected systems rather than accepting the value embedded in the draft.
Catch period, unit, and narrative conflicts.
Every claim is checked against time ranges, currencies, dimensions, and related statements.
Stop when confidence is not sufficient.
Low-confidence or policy-sensitive output is held for a human instead of being presented as certain.
A separate verification path for every consequential output.
Capture the claim
Receive the draft, figures, source references, and action context.
Retrieve evidence
Load the relevant ledger entries, policies, and approved assumptions.
Check independently
Re-derive values and test numeric, period, unit, and policy consistency.
Approve or escalate
Attach provenance, correct the claim, or send it to a human reviewer.
Finance-specific verification, served inline.
The planned verifier is trained on finance failure modes and optimized to run inside the request path without making every answer feel slow.