Token cost tracking for every LLM call
Stop guessing where your AI budget goes. AI Vyuh FinOps tracks token costs in real time across every model, feature, and team — so you can attribute spend to the exact line of business that generated it.
How token cost tracking works
Our lightweight SDK intercepts LLM API calls and records token usage with zero performance overhead. Every call is tagged with your custom dimensions.
Instrument your calls
Add a 2-line SDK wrapper around your LLM calls. Supports OpenAI, Anthropic, Google, and any OpenAI-compatible endpoint.
Tag by dimension
Attach feature name, team, user ID, or any custom label. Group and filter spend by what matters to your business.
See cost breakdowns
View real-time dashboards showing cost per feature, cost per user, and model-level spend. Export to CSV or connect via API.
Why token cost tracking matters
Your AI bill is a black box
Most teams see one line item on their cloud bill: "LLM API usage." Token cost tracking breaks that into hundreds of attributable data points — by feature, endpoint, model, and user.
Unit economics require granularity
You can't price an AI feature if you don't know what it costs. Per-feature token tracking gives you the data to set margins, identify unprofitable features, and make model-swap decisions.
Multi-model complexity is growing
Teams now use GPT-4, Claude, Gemini, and open-source models simultaneously. Each has different token pricing. Tracking costs across providers in one dashboard eliminates spreadsheet chaos.
Catch runaway costs early
A single prompt regression can 10x your token usage overnight. Granular tracking feeds directly into our anomaly detection and budget alerts to stop overruns before they hit your invoice.
Start tracking token costs today
Free tier includes real-time token cost tracking for up to 10K API calls/month. No credit card required.
Start FreePart of the AI Vyuh portfolio. Also see: AI Agent Security · AI Code QA