Token optimization for AI teams

Make every AI token count.

Understand where your tokens go, cut unnecessary context, and build AI products with healthier unit economics.

Estimate your opportunity See the optimization loop

Model agnostic
Quality aware
Built for scale

Request traceLive sample

Task1,240

Knowledge5,820

Duplicated context4,270

Policy1,150

Optimization pass−34%

Task1,240

Relevant knowledge5,820

Policy1,150

Optimized input8,210 tokens

Seetoken demand by workflow

Findavoidable context and calls

Provecost and quality tradeoffs

The optimization loop

Less guesswork.
Better AI economics.

Tokenmize is designed to turn raw model usage into decisions your product, platform, and finance teams can act on together.

Observe

Map where tokens go across prompts, context, models, and workflows.

Optimize

Find oversized context, repeated instructions, and avoidable model calls.

Control

Turn insights into policies your team can measure and improve over time.

Opportunity estimator

What could token efficiency unlock?

Use a simple planning model to explore how request volume, context size, and model pricing shape your optimization opportunity.

Requests / monthAverage tokens / requestBlended cost / 1M tokensTarget token reduction

Illustrative monthly impact

Current token spend$9,000

After optimization$6,300

Potential savings$2,700450M fewer tokens

Planning estimate only. Actual savings depend on model mix, traffic, and optimization policy.

One system, shared language

Built for teams shipping AI.

AI product teams

Keep feature economics visible as usage and context windows grow.

Platform engineering

Give every team a shared view of token demand and model cost.

FinOps leaders

Connect AI consumption to budgets without slowing builders down.

Private beta