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AutoPIL v0.6.0: The governance layer for enterprise AI is ready

135 pre-built policies across 12 industries, a tamper-evident audit chain, and integrations for every major framework. What we built, what building it taught us, and what we're opening up ahead of a public launch in May.

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Govern the Context. Trust the Agent.™ Here's what that actually means.

Every AI governance framework focuses on what agents can do. The real risk is what they can see. Context is where the sensitive data lives — and governing it is the only path to genuine trust.

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Policy enforcement has to be infrastructure, not an agent feature

At five agents, baking governance into each one looks manageable. At fifty, you have fifty different failure modes and no single lever to pull when policy changes.

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Multi-agent systems need a different governance model

When agents hand work to other agents, your governance surface doesn't add — it multiplies. Governing each agent individually is not governance. It's sampling.

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What SOC 2 actually requires from your AI agent stack

Most teams treat SOC 2 as a paperwork exercise. Here's what CC6.1 and CC6.3 actually demand — and why your API key strategy needs to change before your next audit.

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