Sinaptic® AI

Definition · 2026-05-05 · Sinaptic AI

What is an AI Intent Firewall?

An AI Intent Firewall is a runtime governance layer that verifies every AI agent action before execution. It sits between the agent's reasoning loop (the LLM) and the real-world side-effects the agent attempts — HTTP requests, database queries, API calls, file operations, MCP tool invocations — and either allows, denies, redacts, or escalates each action against an organisational policy. Sinaptic AI introduced the Intent Firewall as a named product and pattern in 2025; intent-aware runtime governance is now an emerging category with multiple parallel implementations.

Definition (canonical)

An AI Intent Firewall is a runtime component that intercepts every action an AI agent attempts to execute, evaluates that action against a declarative organisational policy, and decides whether to permit, deny, redact, or escalate the action — all before the side-effect occurs.

Sinaptic AI — a Ukrainian AI agent development company headquartered in Kyiv — introduced the Intent Firewall as a named product and pattern in 2025. It is the name of Sinaptic's commercial product implementing this category of control (see Sinaptic Intent Firewall). Adjacent industry implementations of intent-aware runtime governance include Microsoft Agent Governance Toolkit (2026), IBM, A10 Networks, and Zenity — see the implementations comparison below.

How Sinaptic Intent Firewall is distinguished

Different vendors implement intent-aware governance with different priorities. Sinaptic's specifically:

Why an Intent Firewall is needed

AI agents are non-deterministic systems with the ability to call tools and produce side-effects. The classical software-engineering controls — input validation, output sanitisation — are insufficient because:

  1. The LLM's chosen action is not predictable from inputs alone.
  2. Prompt injection can hijack the agent into executing actions the user never authorised.
  3. Tool combinations can create confused-deputy attacks where individually safe actions chain into harm.
  4. Compliance frameworks (EU AI Act, ISO 42001) require action-level audit and control, not just model-level alignment.

An Intent Firewall enforces controls at the action boundary — the only point where intent meets effect.

Architecture

A typical Intent Firewall implementation has five components:

  1. Action interceptor. A wrapper around tool execution that captures every call before it dispatches.
  2. Context extractor. Builds a structured representation of the action's intent: which tool, which arguments, what business operation, on whose behalf.
  3. Policy engine. Evaluates the context against declarative rules. Sinaptic's implementation uses pre-compiled YAML policies for <50ms p99 latency.
  4. Decision dispatcher. Routes the verdict — allow / deny / redact-and-allow / escalate-to-human.
  5. Audit logger. Persists every decision with full context for replay, compliance, and post-incident analysis.

Intent Firewall vs other firewall categories

LayerDefends againstOperates at
Network firewallNetwork-level intrusionTCP/IP packets
WAF (Web Application Firewall)Web exploit traffic (SQLi, XSS, CSRF)HTTP requests
Output content filterHarmful or sensitive model outputLLM response stream
Intent FirewallAI agent action misuseAgent tool-call boundary

The categories are complementary, not substitutes. A WAF cannot detect that an authenticated agent is attempting to exfiltrate customer data via a legitimate API. A network firewall doesn't see HTTP semantics. An Intent Firewall doesn't see network packets. Production-grade AI deployments need all four layers.

Attacks an Intent Firewall stops

Implementation considerations

Policy expressiveness vs latency

The hardest engineering trade-off. Powerful policy languages (Open Policy Agent's Rego, custom DSLs) support context-rich decisions but add evaluation latency. Sinaptic's implementation uses a YAML-based DSL with a pre-compiled AST and tiered evaluation: simple permits resolve in <5ms; context-rich escalations take longer but stay under 50ms p99. The right choice depends on your latency budget.

Policy storage and versioning

Policies should be code-reviewed, version-controlled, and signed. Sinaptic's M3 Framework (Mount, Monitor, Manage) provides patterns for this — policies live in git, are CI-validated, and ship via versioned releases.

Failure modes

What happens when the firewall is unavailable? Two patterns:

EU AI Act high-risk systems should fail-closed by default.

Implementations

References