AI Cost Overview

Umbrella AI Cost brings every AI provider - model APIs, per-seat assistants and AI running on your cloud providers - into a single view, so FinOps, finance and leadership can see what AI costs, understand whether that spend is efficient, and allocate every dollar to the business

Overview

Umbrella AI Cost brings every AI provider into a single view - usage-based model APIs (Anthropic, OpenAI, Google, AWS Bedrock), per-seat assistants (GitHub Copilot, Cursor, Microsoft 365 Copilot), and AI workloads running on your cloud providers. Each provider ships its own billing console, cost model and usage schema. Umbrella normalizes all of it, turns raw usage into unit economics, and enforces privacy and cost allocation consistently across every provider.

Why it matters

AI cost isn't one line item anymore. Organizations run a mix of providers, each with its own pricing model - per-token, per-request, per-seat, or bundled into cloud infrastructure bills. Without a single pane of glass, FinOps teams can't answer basic questions: what does AI actually cost us, is that spend efficient, and who should pay for it?

Umbrella AI Cost closes that gap so finance, FinOps and engineering leadership can catch overruns early, validate whether caching and model selection are working, prove unit economics without building a custom metrics layer, and charge back every dollar with confidence.

What you can do

Umbrella AI Cost provides visibility into every dimension of your AI spend - from high-level summaries and unit economics, through per-model and per-user drill-downs, to full cost allocation and privacy controls.

Anomaly Detection (coming soon)

Automatically flag unexpected AI spend - Anthropic, AWS and GCP usage presented hourly, daily or weekly.

Privacy & Access

Control how user identities are handled - full attribution, anonymized pseudonyms, or discard at ingest - with role-based access.

See it in action

Analytics Summary

The AI Overall Summary shows cost, token and usage metrics across every connected provider. Cost and usage trends by vendor and product, with a day-by-hour volume heatmap.

Tokenomics

Cost per request, cost per million tokens, cache hit rate and output-to-input ratios, by model and use case.

Cost & Usage Explorer

A chart paired with a matching details table you can group, filter and drill by model, user, team or workspace.

Models

Cost, requests and efficiency compared side by side.

Top Consumers

The biggest products, models, users and teams by spend.

User Activity

Efficiency, utilization and per-user spend against budget.


Why it pays off

Catch overruns early - Budget lines and daily trends flag spending jumps before they compound into surprise invoices.

Cut the waste - Validate caching ROI, right-size model selection by workload, and reclaim idle seats before renewal.

Prove unit economics - Answer "is our AI spend efficient?" with cost per request, per token and per user - no custom metrics layer to build.

Charge back with confidence - Map every dollar to a customer, product or department to inform pricing, renewals and feature profitability.



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