UltraTrace collects usage and identity data from every AI provider you run, normalizes it into one model, enriches it with the way your business is actually organized — and tells you what to do next.
Connect ChatGPT Enterprise, Claude, Copilot, Gemini, and more through their native admin APIs, audit logs, and exports. Sessions, tokens, API volume, and identity data are normalized into a single standardized schema — with users correlated across providers automatically.
Map every user to the dimensions your business runs on — by IdP attribute sync, bulk import, or manual assignment. Assignments are effective-dated, so when someone changes teams, history stays true to the org chart as it was at the time of usage.
Every user is classified into an engagement state — leveraged, active, churned, or never used — and rolled up by any dimension. Three diagnostic levers turn the picture into action: Expand where demand is proven, Elevate where engagement is shallow, Reallocate where seats sit idle.
An optional three-layer classification model summarizes what kind of work AI is doing — code generation, data analysis, drafting, research — plus a sensitivity signal. Classification runs entirely inside your environment, and raw prompt content is purged the moment it's categorized. Labels stay. Prompts don't.
Everything UltraTrace computes — normalized telemetry, business context, and adoption classifications — is exposed through an MCP-compatible API. Pipe it into your BI stack, feed it to your internal agents, or drive your own automations.
We'll deploy into a sandbox in your cloud, connect one provider, and show you your real adoption picture.