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See the full performance layer.
Time, tokens, cost, commits, score, heatmaps, and coaching are presented in one view that feels operational instead of decorative.
Local-first AI coding performance intelligence for developers and teams.
From solo developers to engineering teams, tokeIT tracks tokens, cost, time, commits, and efficiency so your AI workflow becomes visible, measurable, and easier to improve.
A real session shows how tokeIT tracks tokens, commits, and efficiency.

The desktop app gives developers and leads a clear visual dashboard. The CLI keeps the workflow close to the terminal. Both run on the same session intelligence.
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Time, tokens, cost, commits, score, heatmaps, and coaching are presented in one view that feels operational instead of decorative.

The product connects effort to outcomes, which is what makes the data useful. You can finally answer what a feature cost, which model was efficient, and whether the work actually shipped.
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Start with personal measurement. Expand to team-level visibility only when you need it. That keeps the product sharp for developers while still useful for engineering leads.
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Understand where AI budget is concentrated and how performance is trending.
Track AI effort by project or feature instead of only by individual developer.
Leaderboards create visibility without exposing prompt content or session notes.
tokeIT stores session intelligence locally and only syncs when a user chooses to connect an account for team features. The individual coaching layer stays personal; the shared metrics layer stays useful.
Session intelligence is stored locally by default, with cloud sync only when the user explicitly enables team features.
Admins and members can see shared performance metrics, but not private coaching notes or raw session content.
Projects, cost, commits, model usage, and trends stay structured enough for team reporting without turning the product into surveillance.