Provider invoices turned into a normalised, decimal-accurate ledger — so every AI dollar has an owner.
Cut idle agents and over-provisioned workloads the moment savings signals surface them.
Optimise on cost-per-successful-task, so every dollar buys measurable outcomes.
Attribute every provider charge to the team and cost centre that drove it.
Turn raw invoices into budgets and chargeback finance can sign off.
Global AI spend is projected at $2.59T in 2026. As budgets balloon, the gap between spend and what you can explain becomes a board-level problem.
98% of FinOps teams now manage AI cost. It is a core line item that needs the same rigour as cloud.
Most AI spend arrives as provider invoices with no attribution and no budget. You can see the total, but not who spent it or why.
A normalised ledger, budgets and chargeback that tie AI spend to cost centres.
Cost-per-successful-task to optimise AI workloads on real unit economics.
Allocate AI cost to the teams that drive it and forecast with budgets that hold.
Ingest the usage you already have, normalise it, and turn it into budgets and allocations.
Pull usage from your AI providers — OpenAI, Anthropic and more — into one place.
Imports are normalised into a single, decimal-accurate ledger with idempotent, audited runs.
Define budgets, then allocate spend to cost centres with chargeback workbooks.
See cost-per-successful-task and savings signals that point to where to optimise next.
AI Cost Analytics is a capability inside AI FinOps — analytics, budgets and chargeback together.
Normalise usage from major AI providers into one ledger — and bring any other via the import API.
OpenAI and Anthropic are live today; further connectors are on the roadmap. Any provider can be ingested through the import API.
Talk to TAI to scope AI FinOps, or book a Platform demo to see the cost ledger in action.