AI is the fastest-growing, least-governed line on your bill — and provider dashboards stop at the API key. Optmin connects every input and output token to the model that served it, the team that called it and the product that paid for it, in the same FOCUS fabric as your cloud cost.
Input, output and cached tokens broken out per request — then aggregated by model, key, user, team or any custom dimension. The number lands with the people who can act on it.
OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure OpenAI, Mistral and Cohere unified into a single model — folded into the same cost fabric as AWS, Azure and GCP. Read-only ingest, live in minutes.
ML-driven anomaly detection catches token spikes and prompt-length blowouts in near real time — and CloudFlow can pause a key or swap to a cheaper model automatically, inside your policy.
Tie tokens to value: cost per inference, per user, per feature — the margin numbers product and finance actually want, in the same showback and chargeback engine as your cloud cost.
Provider dashboards stop at the API key, shared costs land in one lump, and finance can't tie any of it to the value it creates.
You can see total spend, but not which team, product or customer drove it.
We attribute every token to a team, product and customer — the same way you allocate cloud cost.
Eval pipelines, embeddings and internal copilots get billed in one indivisible lump.
Split platform-wide AI cost across teams with fixed, proportional or custom rules you define.
A bad prompt or a loop can burn budget for days before it ever hits the invoice.
ML-driven anomaly detection flags token spikes in near real time and can pause a key or swap a model automatically.
Without unit economics, margins on AI features are a guess.
Cost per inference, per user and per feature — live, in the same engine as your cloud chargeback.
The pieces FinOps teams actually need when AI spend starts to matter.
See your token spend mapped to teams, products and outcomes. Book a walkthrough.