Zero Trust Security
for AI Agents

AZTP validates that every agent action aligns with its declared purpose. Cryptographic identity meets semantic intelligence.

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The Problem

Permissions don't guarantee purpose

TRADITIONAL SECURITY
✓ Agent has db_read permission
✓ Action: Query ALL customer records
✓ ALLOWED — Has permission
Data breach. Nobody noticed.
AZTP
✓ Agent has db_read permission
⭐ Semantic alignment: 0.25 (purpose: billing support)
✗ BLOCKED — Semantic drift detected
Breach prevented. Trust degraded.

Live Demo

Watch semantic drift get caught

Two actions, same agent, same permissions. Only semantic alignment tells them apart.

AZTP Validation Engine
🤖
agt_01a9627e1d0a
Purpose: "Customer billing support agent"
Trust: 1.00
✅
database_query → "Get billing details for customer 123"
Alignment: 0.91 APPROVED 4ms
Trust Score 1.00 — Trusted
Trust degrades with semantic drift. Falls below 0.5 → Auto-revoked.

How It Works

Three layers of trust

Every agent action passes through cryptographic, semantic, and behavioral validation.

01 — IDENTITY
Verified Agent Identity
Every agent is issued a tamper-proof identity before it can act. Purpose, capabilities, and lineage are bound at creation - not assumed at runtime.
02 — BEHAVIORAL VALIDATION
Continuous Intent Monitoring
Every action is validated against the agent's declared intent in real time. Actions that deviate from purpose are blocked automatically - even when permissions are valid.
03 — ADAPTIVE TRUST
Behavioral Trust Scoring
Agent trust is earned through consistent behavior, not assumed from credentials. Anomalous patterns trigger automatic restrictions. Full audit trail for every decision.

Request Early Access

We're onboarding design partners. Free for 6 months.

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