AI Agent Guardrails That Run Before Execution

Guardrails should not only advise the model. They should protect the action boundary. Aletheia Core gives AI agents a pre-execution enforcement layer for risky actions, tool calls, and policy violations.

Problem

  • Model-level guardrails can be bypassed through prompt manipulation
  • Output filtering happens too late — the action may already be queued
  • Guardrails built into the prompt are not enforced at the backend
  • Autonomous agents need controls that survive adversarial inputs

How Aletheia Core solves it

  1. Pre-execution blocking — stops the action, not just the response
  2. Signed policy manifests — tamper-evident rules
  3. Cryptographic receipts — proof of every decision
  4. Semantic prompt-injection checks — catches disguised attacks
  5. Open-source core — fully auditable
  6. Hosted and enterprise options

Use cases

  • AI app builders
  • SaaS teams adding agents
  • Automation consultants
  • Internal tool teams
  • Security-conscious startups

FAQ

What is AI agent security?

AI agent security protects systems where AI agents can call tools, access data, trigger workflows, or execute actions. It focuses on preventing unsafe behavior before the action happens.

What is runtime enforcement?

Runtime enforcement means checking an action while the system is running, before the agent executes it. This is different from reviewing logs after the fact.

What is prompt injection protection?

Prompt injection protection detects and blocks malicious instructions that try to override the agent's original rules, leak data, or force unsafe tool use.

What are signed audit receipts?

Signed audit receipts are cryptographic records of security decisions. They show what action was checked, what decision was made, and whether the receipt has been modified.