BlackLake (cloud) vs cloud FinOps tools
Cloud FinOps stops at the API call.
AI control and analytics attributes every token.
Traditional FinOps tools see the cloud bill or the model-provider invoice. BlackLake sees every AI call before it happens — attributed to the AI Actor that asked, capped by budgets that deny pre-spend, and bound into the same receipt that proves the decision was allowed.
Feature comparison
AI control & analytics vs cloud FinOps
The bill comes too late. Attribution has to happen at the call.
| Feature | BlackLake | Cloud FinOps tools |
|---|---|---|
| Sees AI / LLM spend at the call level | Yes — Anthropic, OpenAI, Bedrock, Vertex, Foundry, Gemini, Ollama | No — sees the cloud bill or the provider invoice |
| Attributes spend to the AI Actor that asked | Yes — AI Actor / tool / user / capture path | Service / project / team only |
| Pre-call cost estimation | Yes — POST /v1/cost/estimate, fed into the policy engine | No — looks at billed cost |
| Budgets that deny pre-spend | Yes — at govern() time, before the LLM call | Alerts after the spend |
| Cost decomposition (input / output / cache / thinking) | Yes — every receipt | No |
| Versioned pricing snapshots | Yes — historical totals stable through price changes | Re-prices on read |
| Counterfactual model substitution analysis | Yes — 'what would Sonnet have cost?' | No |
| Cost cryptographically bound to a governance receipt | Yes — v2 decision tokens | No |
| Signed CSV / NDJSON exports for finance | Yes — workspace HMAC chain | Plain CSV |
| Used as a governance + compliance artifact | Yes — same record | No — separate tool |
Why this matters
The cloud bill doesn't say which AI Actor asked.
FinOps formalised cloud-cost attribution because the cloud bill alone wasn’t enough — finance needed to know which team, which service, which feature. AI compounds that problem: a single backend service can host a dozen AI Actors, each with a different prompt, model, retry behaviour, and tool surface. Without per-AI-Actor attribution, the question “why did our AI bill double last month” cannot be answered.
BlackLake attributes every AI call to the AI Actor that asked, the tool it called, the model it used, and the user the call was on behalf of. Budgets cap the spend at govern() time. Counterfactual substitution shows what a different model would have cost. Finance gets a signed export. The receipt is the artifact.
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