AI agent authorization · 2026
TrustGate
A runtime authorization gate for AI agents that checks live business evidence before a risky action runs, returning ALLOW, APPROVAL_REQUIRED, or BLOCK with an auditable receipt.
Solo · Google Cloud Rapid Agent Hackathon
snapshot
- type
- AI agent authorization
- period
- 2026
- source
- public github
- demo
- watch
problem
AI agents can propose high-impact actions such as refunds, but production systems need a transparent control layer that decides whether the action is allowed, needs approval, or should be blocked.
outcomes
- Example verdict: a refund proposed on data synced 42 minutes ago against a 15-minute SLA, for a customer tier the input contract never authorized, returns APPROVAL_REQUIRED with the evidence receipt attached
- The agent was authorized; the data was not trusted, and the receipt shows why
- Connected live data evidence to policy decisions on Google Cloud
what i built
- Runtime gate between AI agents and risky actions
- ALLOW, APPROVAL_REQUIRED, and BLOCK decisions
- Deterministic policy engine for final authorization
- Auditable decision receipts instead of black-box scores
- Live evidence ingestion from Fivetran and BigQuery
- Data freshness checks against SLAs
- Schema compliance checks
- MCP endpoint deployed on Google Cloud Run
- Small React control-room dashboard
- Vertex AI/Gemini integration for agent proposals
tech stack
Node.jsGoogle Cloud RunVertex AIGeminiBigQueryFivetranMCPReact
Read the source
The repo has the code, structure, and implementation detail.