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Unseen usage
You can't name the AI tools running on your endpoints, who runs them, or with what privilege. Discovery stops at the network edge.
Statefold is a two-tier platform that discovers every AI tool your people use, enforces policy on the endpoint, decides which agents and privileges are allowed to run — and remembers all of it in a deterministic Hive Mind you can simply ask.
Copilots, chat tabs, IDE assistants, MCP servers and autonomous agents arrive faster than security can review them. The old stack was built for files and networks — not for prompts, tokens, and agents that act.
You can't name the AI tools running on your endpoints, who runs them, or with what privilege. Discovery stops at the network edge.
Anyone can spin up an agent and hand it credentials. Nothing stops a malformed prompt, an over-privileged tool, or a quiet exfiltration.
Prompts, answers, code, MCP calls, tokens and spend evaporate. When an incident lands, there's nothing to ask.
The agent enforces locally and keeps protecting even when disconnected. The console gives operators fleet-wide discovery, policy, governance and the Hive Mind.
Observes every AI surface — proxy, browser, IDE, MCP, Bedrock, clipboard — classifies content with a pure-Python engine, and enforces on box.
Fleet telemetry, central policy, AI agent governance, discovery, coverage, and the Hive Mind — served behind one API with an embedded store.
Every device, identity and AI touchpoint — agents, models, APIs and MCP servers — drillable to one endpoint.
Inline classification of prompts and responses across surfaces, with allow / alert / redact / block — before send.
No agent runs until approved. The agent and its privilege are two separate decisions, each on a 72-hour grant that auto-expires.
A deterministic memory of all AI usage — and a chatbot over it. Ask it anything; no model required.
See exactly what's protected where, per surface, per group — and where the gaps are.
A red-team catalog and campaigns to prove the controls hold against prompt injection and exfiltration.
Every prompt and question. Every answer, code generation and MCP query. Token usage, AI billing and license consumption. Snapshots, alerts and audit logs. It builds continuously from every touchpoint — and then you build a chatbot over it.
Classification, policy and governance are rule-based and deterministic. A local model can sit on top later — never an external API.
The endpoint blocks, redacts and halts locally. The verdict is a literal halt, not a dashboard note.
Fleet sync is additive. Disconnect the endpoint and protection continues — never a dependency for safety.
An agent runs only if it and the privilege it seeks are both approved. Otherwise it's halted and killed.
Approvals auto-expire. The request and the agent both die down — no standing access by accident.
The Hive Mind is local. Prompts, tokens and spend never leave the perimeter.
Drop the light agent on endpoints; it self-registers to the console with a scoped token.
Every AI surface is discovered and classified, attributed to a user, endpoint and privilege.
Approve agents and privileges separately; policy and grants enforce at the endpoint.
The Hive Mind remembers it all. Ask in plain language; get a deterministic answer.
Purview and Defender govern files and email. EDR watches processes. SSE / CASB guard the network. Statefold governs the AI itself, on the endpoint, with a memory.
| Capability | Statefold | Purview / Defender | EDR (CrowdStrike · S1) | SSE / CASB / Prompt-FW |
|---|---|---|---|---|
| Endpoint-native AI enforcement | ● | ○ | ◐ | ○ |
| Prompt / response DLP, pre-send | ● | ◐ | ○ | ◐ |
| AI agent + privilege governance | ● | ○ | ○ | ○ |
| Works offline / on-box | ● | ○ | ◐ | ○ |
| Deterministic memory of all AI usage | ● | ○ | ○ | ○ |
| Token / billing / license visibility | ● | ○ | ○ | ◐ |
| No LLM dependency | ● | ○ | — | ○ |
See Statefold discover, govern and remember the AI already running across your fleet.