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Most enterprises can't see what AI their people are running, can't explain why an output went wrong, and can't enforce policy in real time. Classie is the visibility and control layer that makes AI governable — Discover what's active, Analyze what happened, and Supervise risky behavior across users, GenAI apps, and agents.

Four things: a live map of AI activity, an inventory of agents and GenAI apps, trace-level history of prompts, tools, files, and cost, and a policy view showing risky or non-compliant behavior. Practitioners operate it day-to-day; executives consume the summary posture, findings, and cost views.

Visibility first. Install, observe your actual AI usage for a short period, then write policy against what you genuinely find rather than what you assume. Many teams begin with a single high-risk business unit or with the browser extension alone, then expand.

Fast. A typical deployment is live in minutes, and the activity map and inventory start populating immediately — most teams surface unsanctioned tools and unexpected data connections in the first session.

Both, with different views. Security teams operate the console; executives and governance stakeholders get summary risk posture, policy findings, the AI activity map, and cost visibility.

Classie covers the full surface through lightweight collectors across the browser, your infrastructure, and the desktop — so sanctioned tools, shadow AI, and autonomous agents all show up in one place.

Private cloud and hybrid today, with on-prem coming soon. The platform is Kubernetes-native, and sensitive data stays inside your environment.

API logs show that a call happened, not why it happened, who triggered it, what intent was behind it, or whether it broke policy — and they miss browser GenAI, desktop apps, and shadow AI entirely. Classie adds the context and correlation that make AI activity interpretable at scale.

Yes. Classie reconstructs any session end-to-end, so you can see what the AI did, which data and tools were involved, and where it went off track.

Classie can act inline in real time — allowing, blocking, redirecting, or flagging risky interactions before they become incidents, with human-in-the-loop where it matters.

Classie produces the audit trail, data-handling controls, and reporting needed to support frameworks such as SOC 2, and industry-specific AI governance obligations. Contact us for framework-specific detail.

No. Your data is not used to train models. Classie is built so sensitive data stays within your control.

Sensitive data stays inside your infrastructure, encrypted in transit and at rest. Classie can deploy privately so inspection happens within your perimeter.

Classie meters AI usage and efficacy across prompts, agents, and models — so you can compare vendors, attribute spend, and cut usage that isn't earning its keep.

Classie classifies each interaction by intent — productive, suspicious, or high-risk — reading context rather than keywords, so intervention can be precise.