Most organizations have AI acceptable use policies. What they lack is the tooling to enforce them.

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Today's enforcement tools are static, fragmented, and generic, built for no industry in particular and no organization specifically. Policies vary across teams and resist translation into adaptive, enforceable controls. Meanwhile, AI behavior has outpaced text-level guidelines. It now spans agents, API calls, and multi-step workflows where the risk isn't just what the model says, but what the model and agents do.

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Without AI-native policy enforcement, enterprises carry an uneven risk posture: tight in some places, absent in others, and nowhere strong enough to contain an incident or satisfy an audit.

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PolicyGuard gives you complete control over how AI policy is defined and enforced across your environment at runtime, without retraining your models.

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Define and extract policies from existing assets

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Write policies in plain natural language, or let PolicyGuard extract them automatically from existing documents. It ingests PDFs and JSON files, converting them into structured, enforceable controls. Policies can then be continuously refined through Policy Lab, where backend agents analyze coverage, close gaps, and reduce inefficiencies over time. No retraining required.

Enforce policy on actions, not just text

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PolicyGuard evaluates agent traces and function calls, applying policies to inputs, outputs, and the actions in between. Policy follows the full decision chain across tool calls, autonomous workflows, and multi-step agent behavior, where the real risk lives.

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Eliminate translation blind spots

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PolicyGuard evaluates content in its original language. Powered by a lightweight model optimized for runtime efficiency and strong reasoning, it applies policy where context is clearest, reducing false positives without sacrificing speed.

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Layer regulatory frameworks and internal policies in one place

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Teams can apply and combine standardized frameworks (EU AI Act, GDPR, FINRA, OWASP, MLCommons) alongside custom policies in a single, traceable enforcement layer. No duplicative effort across frameworks, and audit-ready by default.

Full visibility, with reasoning behind every decision

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Every allow/block decision includes a detailed explanation generated asynchronously, adding zero latency. A centralized dashboard surfaces queries, violations, policy groups, users, API keys, and latency in one place, giving teams a single source of truth for all AI enforcement activity.

Deploys into your existing infrastructure

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PolicyGuard supports on-prem, cloud, and SaaS environments. Its lightweight architecture means fast rollout without significant infrastructure changes or compute overhead.

As AI systems evolve, PolicyGuard keeps policy enforcement aligned with how they actually operate: consistently, traceably, and without falling behind.

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Read the full press release.

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Read PolicyGuard Frequently Asked Questions (FAQ).