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TokenAtlas
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AI cost tracking

Know what every AI feature costs you, in real time.

Stop guessing at the next invoice. TokenAtlas tracks every LLM call — input tokens, output tokens, cache hits, and dollar cost — and breaks it down by feature, model, environment and customer.

  • Per-call cost attribution by feature, team or tenant
  • Token usage analytics across every provider
  • Anomaly alerts when spend deviates from forecast
  • Exports your CFO and procurement team will accept
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Why provider dashboards aren't enough

OpenAI's usage screen shows one provider. Anthropic's shows another. Neither attributes spend to your features or customers. TokenAtlas unifies every provider into one cost view so you can answer 'which feature spent $4,200 last week?' in seconds.

Tracking that finance trusts

Token-accurate accounting, daily reconciliation against provider invoices, and tagged exports for chargeback and cost-of-goods reporting. Finance gets the numbers they need; engineering keeps shipping.

From tracking to optimization

Once costs are tracked, the next step is to act on them — model swaps, prompt rewrites, caching wins. TokenAtlas surfaces the highest-leverage optimizations automatically.

Frequently asked questions

What does AI cost tracking actually measure?
Token volume in and out, request count, model used, latency, and the dollar cost of each call — broken down by feature, environment, or customer so you know what's driving the bill.
How fast can I see new usage?
Near real-time. TokenAtlas ingests usage as it happens, so the dashboard reflects production traffic within minutes, not at the end of the billing cycle.
Do I need to change my code?
Minimal change. Drop in the TokenAtlas SDK or proxy your provider calls — usage flows in automatically and your existing prompt code stays untouched.

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