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Documentation Index

Fetch the complete documentation index at: https://docs.finpace.tech/llms.txt

Use this file to discover all available pages before exploring further.

AI runtime overview

Finpace public positioning presents AI as part of the operating core, not as a chatbot bolted onto the edge. This documentation therefore models the AI runtime as a governed execution layer with five parts:
  1. Agent UI for customer and staff interaction
  2. MCP gateway for safe tool exposure
  3. AI Shield for perimeter and policy enforcement
  4. Policy engine for action evaluation
  5. AI audit store for evidence and traceability

AI design principles

Assist before acting

AI can summarize, propose, draft, explain, and route before it executes a protected action.

Tools, not raw system access

AI agents receive task-scoped tools such as:
  • retrieve arrangement summary
  • draft customer message
  • prepare payment instruction
  • request covenant waiver review
  • summarize application documents

Policies precede execution

Every state-changing AI call is evaluated for:
  • entitlement
  • consent
  • approval requirement
  • product and jurisdiction rule
  • risk score
  • tool safety profile

Evidence is mandatory

Each AI-assisted action writes:
  • prompt or request context hash
  • tool selection
  • policy evaluation result
  • approvals obtained
  • final business outcome