TokenAtlas

AI spend management

Take control of every dollar you spend on AI.

TokenAtlas is the AI spend management platform for teams building with LLMs. See exactly where token spend goes, catch anomalies before the invoice, and pick the right model for every workload.

  • Real-time spend per model, feature, environment and team
  • Anomaly alerts before the monthly bill arrives
  • Side-by-side cost simulation across GPT, Claude, Gemini and more
  • Forecast 12 months of spend on realistic growth curves

Why AI spend management needs its own tool

Cloud FinOps dashboards weren't built for token economics. AI bills move with prompt length, model tier, cache hits, and reasoning mode — not CPU hours. TokenAtlas gives you a model-aware cost layer so engineering and finance see the same numbers.

What you can do

Attribute every API call to a feature, customer, or environment. Compare current spend to forecasts and to peers. Run what-if scenarios before you swap a model in production. Export clean reports your CFO will actually accept.

Who it's for

Engineering leads who need a defensible AI budget. CTOs who want to know what AI costs before the next funding conversation. FinOps teams that have outgrown spreadsheets.

Frequently asked questions

What is AI spend management?
AI spend management is the practice of monitoring, allocating, and optimizing what your team pays for LLM APIs and AI infrastructure. It combines cost visibility, usage analytics, model selection, and budget control in one workflow.
How is AI spend management different from FinOps?
FinOps is the broader cloud financial-operations discipline. AI spend management is the AI-native slice: token-level cost attribution, model-mix optimization, and prompt-efficiency reviews — things traditional cloud FinOps tools weren't built for.
Does TokenAtlas track every LLM provider?
Yes. OpenAI, Anthropic, Google, Mistral, Groq, DeepSeek, Cohere and others are all supported, with pricing kept current as new models ship.

Continue exploring