Docy AI

What is an AI execution layer?

An AI execution layer sits between foundation models (like OpenAI, Claude, or Gemini) and your enterprise systems. Unlike monitoring tools that observe AI from the outside, an execution layer processes every AI decision through a compliance pipeline — fingerprinting inputs, applying domain rules, routing exceptions to humans, and sealing outputs with a replay token. Docy AI is purpose-built as this layer for regulated industries.

How does Docy AI ensure compliance for LLM decisions?

Every LLM output passes through a five-step pipeline: (1) ingest and fingerprint the input, (2) run domain-specific compliance rules, (3) route exceptions to a human approval queue, (4) record human approve/reject decisions with identity and timestamp, and (5) seal the decision record and activate the replay API. Every step is logged immutably.

What industries does Docy AI support?

Docy AI supports any regulated industry through swappable domain rule sets. Current production deployments include energy and regulatory compliance, credit assessment and financial services, and operational accounting and BPO workflows. The platform architecture allows new domains to be added by swapping the rule set while keeping the audit infrastructure unchanged.

What is decision replay?

Decision replay allows you to reconstruct exactly how any AI decision was reached — the original input, the model version used, the compliance rules applied, the data at the time of processing, and the human approval chain. Each sealed decision includes a replay token that activates the replay API, making every decision auditable months or years after execution.

How does human-in-the-loop approval work in Docy AI?

When compliance rules flag an exception, the decision is routed to a human approval queue with full context — the original document, extracted data, rule that triggered, and risk assessment. The human reviewer approves or rejects with their identity and timestamp recorded as an immutable record. This creates a legally defensible audit trail.

How does Docy AI differ from AI governance tools?

AI governance tools like Credo AI or OneTrust focus on policy frameworks and risk assessment — they observe AI from the outside. Docy AI sits in the execution path: decisions flow through it, not around it. Every output is fingerprinted, compliance-checked, human-approved where needed, and sealed with a replay token. Governance tools tell you what should happen. Docy proves what did happen.

Does Docy AI support regulatory compliance?

Docy AI's architecture — immutable audit logs, human-in-the-loop gates, decision replay, and data lineage — is designed to support compliance requirements across regulated industries. Every AI decision is fingerprinted, sealed, and replayable, giving compliance teams the documentation infrastructure they need.

How quickly can Docy AI be deployed?

Most teams are live within five business days. Docy connects to existing document sources (email, portals, APIs, uploads) and enterprise systems (ERPs, CRMs) without requiring a rip-and-replace of your current stack. Deploy on-premise or as Docy-hosted SaaS.