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BLACKLAKE

BlackLake (cloud) vs governance-only

AI control and analytics is bigger than governance.
Capture, govern, cost, and prove — one ledger.

Governance-only platforms decide whether a call is allowed and write the decision to an audit log. AI control and analytics is the larger function — capture the action, govern it, cost it, and prove it with a receipt every other system can verify.

Feature comparison

AI control & analytics vs governance-only

Same allow / deny decision; the rest of the artifact is different.

FeatureBlackLakeGovernance-only platforms
Captures every consequential AI actionYes — IDE, CI, shell, cloud, code, durable workflowsLimited — usually one capture path
Per-call dollar cost attributionYes — Anthropic, OpenAI, Bedrock, Vertex, Foundry, Gemini, OllamaRarely — cost is a separate product
Cost-aware policies (deny on spend, model, input length)Yes — first-class DSL, monitor or enforce modeNo — policies see only the call shape, not the spend
Budgets that deny pre-spend at govern() timeYes — workspace / AI Actor / tool / user, hard + softNo
HMAC-signed receipts (independently verifiable)Yes — paste into /verify, read the chainAudit logs only — not signed
Decision tokens that bind cost cryptographicallyYes — v2 receiptsNo
Policy simulation against historical trafficYes — with dollar-impact estimatesSometimes — without cost
Two-person approval, break-glass, magic-linkYesSometimes
Durable workflows under the same control layerYes — long-running AI work uses the same ledgerOut of scope
Signed exports for SIEM, BigQuery, financeYes — NDJSON + CSV with workspace HMACPlain audit log

Why this matters

A governance decision without a cost is half a receipt.

When the auditor asks “was this AI action allowed?”, a governance platform answers yes or no. When the CFO asks “how much did this AI Actor cost us this quarter?”, the same platform shrugs. AI control and analytics answers both, on one record.

That matters because the buyers are different. Security cares about the decision and its evidence. Finance cares about the spend, attributed to the AI Actor that asked. Compliance cares about both, plus a receipt they can hand to an external auditor. Engineering cares about the policy not breaking the dev loop. Four buyers, one ledger.

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