AutoFlow
Research
External verification, the honest scope of provability, and the architecture that keeps probabilistic generation apart from deterministic checks.
Probabilistic
AI generation
Extracts and reasons over documents
Deterministic
External verification
Evidence, rules, exact calculations
01
LLMs can extract and reason over financial documents, but their answers are not independently checked before entering underwriting, covenant monitoring, or portfolio workflows. Retrieval adds context; it does not verify how that context was used.
02
AutoFlow’s position is that eligible financial claims should be checked outside the model—against source evidence, approved definitions, compatibility constraints, and deterministic calculation rules—before release into a credit decision.
03
Supported numerical and rule-bound financial claims can be verified. Ambiguous definitions escalate. Missing or conflicting evidence blocks calculation. Interpretive, causal, or unsupported claims are not falsely certified. Deterministic verification of supported financial claims is not mathematical proof of every AI answer.
04
Separate the probabilistic AI layer from the deterministic verification layer. EvidenceGraph, claim compilation, rule runtime, findings, and certificates form a reproducible path from document packages to reviewable outcomes—designed to support auditability, traceability, and AI-governance workflows.
Related: Product · Benchmarks
Design partners bring one recurring credit package. We show which claims can be verified, blocked, or escalated.
