Patent pending · USPTO May 2026
The AI governance layer
for regulated industries
The LLM reasons. Your systems decide.
Proviguard governs the boundary.
Every LLM tool call intercepted, validated against regulatory requirements, and cryptographically proven before it reaches your decisioning engines, payment rails, or compliance workflows.
Use cases
Any workflow where LLM output feeds a regulated system
Proviguard governs the boundary between LLMs and consequential systems — wherever that boundary exists. The workflows below are representative examples, not an exhaustive list.
Banking & Fintech
Healthcare Coming soon
Insurance Coming soon
Legal Coming soon
The governing principle: if an LLM's output feeds a system that executes a regulated consequence — a credit decision, a payment, a compliance filing — Proviguard intercepts, validates, and proves the handoff. These workflows are illustrative examples, not an exhaustive list.
CreditIncome & asset extraction — underwriting input
LLM extracts from W-2s, tax returns, bank statements. Output feeds nCino or Zest AI. The LLM does not approve or deny — it extracts. Proviguard governs the handoff.
FraudFraud signal generation — real-time
LLM generates risk signals in <500ms. Output feeds deterministic rules engine. The engine makes the block/allow decision. Proviguard proves the signal was OFAC-clear before arrival.
BSA / AMLSAR narrative drafting — BSA officer review
LLM drafts the narrative. BSA officer reviews, edits, and owns the FinCEN filing. Proviguard blocks any model substitution on regulated output.
AMLAML alert triage — narrative & scoring
LLM drafts alert narrative for analyst review. Analyst makes the SAR/dismiss decision. Mandate records exactly what the LLM produced and when it reached the analyst queue.
PaymentsWire pre-validation — BEC detection
LLM assesses wire instructions for business email compromise indicators and SWIFT anomalies. Compliance officer makes the execution decision.
KYCKYC document review — onboarding
LLM extracts and validates identity documents against onboarding criteria. PII never leaves the VPC during review.
Reg BAdverse action letter — Reg B compliance
LLM generates compliant adverse action notices with specific CFPB reason codes. Loan officer reviews before delivery. Mandate proves exactly what letter went to the customer.
APInvoice & document extraction — AP automation
LLM extracts structured fields from invoices and purchase orders. PAN and account numbers tokenized before the LLM sees the document.
These are illustrative examples. Any banking or fintech workflow where an LLM's output reaches a decisioning engine, payment rail, compliance system, or regulatory filing is a Proviguard use case. If your compliance team needs to prove what your AI did — this is the infrastructure layer.