Prompt clarification
When a request is too vague, TokenTally asks the employee for a more specific prompt instead of sending wasteful context to a model.
Token optimization platform
Token optimization for company AI usage
TokenTally helps companies reduce wasted AI tokens by checking prompts locally, asking for clarification when prompts are vague, routing requests to approved models, and enforcing token budgets before AI usage becomes expensive.
Direct answer
Token optimization is the discipline of using fewer, better-targeted AI tokens while preserving useful output quality. For companies, that means controlling prompt size, model choice, response limits, employee permissions, and budget policies from one gateway.
How TokenTally optimizes tokens
Model routing
Routine tasks can use lower-cost approved models while sensitive or complex work stays limited to departments that need it.
Output controls
Admins can set maximum output tokens during slowdown mode to prevent long, expensive answers when budgets are tight.
Local accounting
The gateway estimates and records tokens locally, applies configured provider prices, and shows budget impact to administrators.
Best use cases
- Companies moving employee AI usage into a local model gateway.
- Teams that need token budgets per month or week.
- Departments that should not access every AI model or every task category.
- IT teams that need local policy checks before any model response is generated.
- Organizations that want AI economy without sending employee usage data to a SaaS control plane.