AI spend on autopilot.
Control token spend by Employee, Agent, and Task.
Set budgets per employee, attribute spend per task, and never blow your month in a week.
- Employee ramin $128 / $200
- Agent nano-research $42 / $80
- Task refactor-auth $11 / $25
What you control
Tempo for agents, apps, and background jobs.
- 01
Budget
Set a spend envelope on whatever matters — a teammate, an autonomous agent, or a single task. Sub-agents inherit. Limits are real, not advisory.
- 02
Pace
TokenPlan throttles instead of blocking. Underused budget rolls forward within the window, so a quiet morning funds a busy afternoon — and your month never ends on day nine.
- 03
Steer
Slice your bill by employee, agent, or task to see where the money went. Adjust any budget on the fly without redeploying or rotating keys.
Provider neutral
TokenPlan works with your models.
TokenPlan sits between the apps and agents spending tokens and the model providers you already use. It keeps limits, pacing, and spend history consistent even when the underlying model changes.
Workloads
- Coding agents
- Research jobs
- Chat tools
- Background tasks
Pacing loop + budgets
One endpoint routes requests through live spend envelopes for each employee, agent, and task.
Providers
- ChatGPT
- Claude
- Gemini
- Open source
Security & compliance
Enterprise controls for every model your teams use.
TokenPlan gives teams one secure layer for model access, usage policy, and spend governance, so AI workloads stay controlled even when employees, agents, and apps move across providers.
One control plane for AI usage.
Centralize model access, budget policy, and usage oversight in TokenPlan instead of letting every team wire agents directly to separate model providers, keys, and billing accounts.
- Data protection
Keep customer data out of training.
Route AI traffic through enterprise-grade model infrastructure designed so prompts, outputs, and customer data are not used to train foundation models.
- Regional control
Keep workloads where they belong.
Apply region-aware routing and policy controls to help teams align model usage with internal data residency and jurisdiction requirements.
- Vendor optionality
Use the right model without new sprawl.
Give teams access to leading commercial and open models while keeping budgets, access rules, and audit trails consistent across providers.
- Procurement-ready
Simplify security review.
Consolidate AI usage behind a governed layer with clear logs, predictable controls, and fewer direct provider integrations to approve.
Early access
Give your agents a steady token budget.
Get an endpoint, plug it into your stack, and stop refreshing billing pages. We're onboarding builders one by one.
- Coding assistants
- Autonomous agents
- Side projects
- Background jobs