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FinOps for AI

/finops for ai/

The AI bill, before it lands — not after.

AI spend scatters across teams, agents, models, and vendors. Brutor meters every governed call in real time, enforces budgets before they’re breached, and honestly costs the AI you can only observe.

/meter & enforce/

Budgets that stop the call, not report it later.

Every request through the gateway is metered against the resource group it belongs to — and limits are enforced in the request path, at runtime.

Per-group budgets

Token limits, dollar ceilings, and rate caps per team, project, or agent — hierarchical resource groups mean finance-grade scoping, not one global dial.

Real-time attribution

Cost by user, team, model, agent, and tool — live in Mission Control, exportable for the systems finance already runs.

Operator alerts

Usage-limit breaches and anomalies raise alerts with an acknowledgement workflow — the bill surprise becomes a Tuesday notification.

/the ai you buy/

See and cost the AI that can’t be routed.

Closed SaaS AI — Claude Desktop, ChatGPT, vendor consoles — can’t flow through anyone’s gateway. Brutor imports its usage through vendor analytics APIs — Anthropic Enterprise (the fullest: chat, code, agent, and office usage), OpenAI (usage and costs), Google Vertex (token counts), and Microsoft (Azure cost plus Copilot activity) — categorizes it into resource groups, tracks it against the same token and dollar limits with advisory operator alerts, and syncs the observed models into your Asset Registry with auditable factsheets.

Honest by design

Observation is advisory: we don’t intercept that traffic, and we never see prompts or responses. Visibility and cost — not interference. Coverage per vendor varies and your quote never depends on it.

/spend less, honestly/

Cost that goes down, not just gets reported.

Smart routing

Routing groups send each workload to the cheapest suitable provider, with weighted failover and circuit breakers when one misbehaves.

Bring your own models

When the buy-vs-build math flips, deploy open-weight models in your own VPC (Ollama, KServe) behind the same governed endpoint.

Semantic cache

Embedding-based caching serves paraphrased repeats instantly; exact cache catches literal ones — cached answers cost nothing at the provider.

300+

models to arbitrage across

~0ms

detectable overhead at tested concurrency

0

per-token platform charges — flat annual license

1

inventory for the AI you build and buy

/start the conversation/

Know what AI actually costs you.

Download the free trial, or book a 30-minute demo with our team.

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