IntentFrame is structural prevention—not just surveillance. We don't just monitor agents; we prevent them from acting without validation.
Fail-closed by default. Zero hopeful trust.
What IntentFrame Is
One platform to define, monitor, and enforce rules across every AI agent.
Every attempted action is evaluated for:
Does this action actually match the request?
Is the agent operating where it's allowed?
Does this resemble injection or manipulation?
Are the consequences acceptable?
If validation fails, the action does not execute.
If anything is unclear, execution stops.
Nothing passes silently.
The Security Problem
Most deployments still rely on hopeful trust:
Hope is not a security model.
The Value of Centralization
Instead of managing security in 10 different tools, IntentFrame centralizes governance in one layer.
Prevention & Response
Define a policy once and it applies to every agent across the organization. No per-tool configuration.
Revoke agent permissions instantly from one central dashboard. Immediate effect, no tool-by-tool cleanup.
Agents never hold credentials directly. Only validated execution paths have access to production systems.
Audit & Accountability
Structured decision records linking what the agent wanted, which policy governed it, and what happened. Built for regulators.
Running tasks use the policy snapshot captured at task start. Predictable, auditable behavior with clear version history.
Every decision is attributed: what was requested, why it was allowed, what occurred.
The Core Distinction
Watch agents as they act. Detect problems. Alert. Respond.
The agent already has capability when you notice something wrong.
Agents cannot act directly. Period. Every action must pass validation before it touches your systems.
IntentFrame is structural prevention.
| Structural Prevention | Surveillance (Monitoring) | |
|---|---|---|
| Credential access | Only validated execution path has credentials | Agents have credentials |
| Attack timing | Prevents execution capability entirely | Detects attacks after capability exists |
| Defense type | Architectural (novel attacks still blocked) | Pattern-based (can miss novel attacks) |
| Response model | Proactive enforcement | Reactive alerting |
| Security outcome | Stops what shouldn't happen | Logs what happened |
Monitoring tells you what went wrong.
IntentFrame ensures it doesn't happen.
Threat Prevention
Malicious instructions embedded in data lead agents toward unsafe actions. IntentFrame blocks actions that diverge from the original request.
Agents attempting to operate outside their authorized domain are stopped — regardless of phrasing or intent.
Actions that appear benign but produce dangerous outcomes are blocked before execution.
Attempts to access higher-risk resources are rejected automatically, without exceptions.
Security Invariant
Any ambiguity results in rejection or escalation — never silent approval.
Security is the default state.
Scope
We enforce execution security.
Nothing else.
The Principle
AI capabilities should scale freely.
AI execution must be secured.
IntentFrame separates the two.
Status
IntentFrame is in active development with early partners operating in high-risk environments.
We're building security infrastructure for autonomous systems — not demos.
If you're deploying AI that has access to production systems, handles sensitive data, operates without continuous oversight, or requires a defensible security posture — let's talk.
IntentFrame
Because "the AI made a mistake" is not an acceptable incident report.