AgentGuard — AI Governance Layer

The trust layer missing from most AI deployments. Confidence scoring decides what the AI handles autonomously vs. what needs a human. Every decision — automated or overridden — is logged with full reasoning. Live demo: HR candidate screening.

AI GovernanceClaude AINode.jsSQLiteHuman-in-the-LoopExplainabilityOpenRouter

Problem

Enterprise AI adoption stalls because there's no trust layer. Teams need to know when the AI is confident vs. guessing, keep humans in control of edge cases, and produce audit trails that satisfy compliance and legal. Most AI demos skip this entirely — which is exactly why they don't convert to production deployments.

Solution

A middleware layer that sits between your AI agent and its actions. Every decision gets a confidence score. High-confidence decisions (≥70%) execute automatically and are logged. Low-confidence decisions go to a human review queue before any action fires. Everything is auditable — inputs, outputs, confidence, latency, outcome, and any human override with reason. A governance report surfaces intervention rates, failure patterns, and performance trends.

Demo

Results

3 confidence tiers: auto-execute, human review, escalate
Full audit trail on every AI decision
Human override with reason logged
Governance report with explainability summary
Live demo: HR candidate screening scenario

Tech Stack

Node.jsExpressClaude AIOpenRouterSQLiteVanilla HTML/CSS/JSVercel

Want something like this for your team?

Fixed-price engagements. No retainers. Most projects ship in 1–6 weeks.

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