AI · Tokenomics
Token-level spend visibility, across every LLM provider you use.
98% of FinOps practitioners now manage AI spend, and granular token/request visibility is the single most-requested capability the industry says nobody delivers. CloudPivot ingests it, normalizes it, and ties it to value.
Every provider, one normalized view
Anthropic, OpenAI, Amazon Bedrock, Azure OpenAI, Google Vertex, OpenRouter, and xAI all land in one store — no more stitching together seven billing consoles.
See what's actually driving cost
Spend broken out by token class — uncached input, cache write, cache read, output — plus effective vs. list $/M tokens, so cache and batch savings are visible, not assumed.
Attribute spend even providers can't tag
Virtual tagging maps API keys, projects, and models to team, product, and use-case — the same attribution vocabulary as your cloud CUR data.
Finally, ROI per AI use case
The use-case value ledger pairs spend with declared value — deflected tickets, hours saved, revenue attributed — so 'is this AI feature worth it' has an answer. No other tool ships this.
Advisories that size the exact prize
Cache-adoption, batch-eligibility, and model-routing recommendations quantify savings from your own traffic mix, not a generic benchmark.
Budgets built for AI's volatility
A looping agent or a leaked key can burn five figures in a weekend. Anomaly detection runs at daily-to-hourly granularity and names the exact key or model that moved.
Where the dollars go
Token-class breakdown, and what caching actually buys you.
Cache and batch discounts move effective cost more than list price does — this is the number that proves optimization is working.
See your AI spend the way FinOps sees cloud spend.
Connect your LLM providers for token-level visibility — reconciled against provider billing, not estimated.