AI API cost intelligence & control
Control Your Burn.
Real-time AI API cost intelligence and guardrails for AI-native applications. As AI systems scale and agent workflows trigger multiple model calls, costs become unpredictable. AtlasBurn helps teams monitor usage, forecast burn, and prevent runaway costs.
Free during beta · No credit card required
AI API costs are hard to predict.
Most teams don't see the problem until the invoice arrives.
Retry storms eating margin silently
A single upstream timeout triggers cascading retries. Your costs triple in hours. Your dashboard won't show it until the invoice arrives.
Model overkill on low-value requests
GPT-4 answering questions that GPT-3.5 handles fine. You're paying premium prices for commodity inference — at scale.
Revenue growing while runway shrinks
More users should mean more time. Instead, each new customer accelerates your burn. Growth becomes a liability.
Manual spreadsheet forecasting
You're projecting burn in Google Sheets with linear assumptions. API costs don't scale linearly. Your model is wrong.
This isn't another dashboard.
AtlasBurn is not
- A logging dashboard
- A generic token counter
- A billing report with charts
- Another monitoring sidebar
AtlasBurn is
- Cost intelligence for AI APIs
- A burn forecasting layer
- Guardrails against runaway spend
- An operational control plane for AI costs
What you get.
Clear visibility and control over AI API costs — from monitoring to guardrails.
AI API Cost Intelligence
Real-time visibility into token usage, cost distribution, and model spend across providers. Understand exactly where your AI budget goes.
Burn Forecasting
Predict API cost trajectories based on usage patterns and growth. Detect runway compression early so you can act before it becomes a problem.
Guardrails & Cost Controls
Define thresholds and enforce protections against runaway AI usage. Set limits that prevent unexpected cost spikes from impacting your runway.
Agent Usage Monitoring
Track complex AI workflows and multi-call agent behavior. See how chained model calls contribute to total spend across your application.
I'm talking to teams building AI-native products to understand how they manage API costs. If this is a problem you're dealing with, I'd like to hear from you.
Talk to the Founder
Limited spots available
Built for teams running AI in production
- OpenAI
- Anthropic
- Google Gemini
- AWS Bedrock
"We were growing fast and had no visibility into how our API costs were scaling. AtlasBurn helped us see the trends early and set guardrails before costs got out of hand."
— Early Beta Founder · Series A AI SaaS
Skeptic? Good.
I already track my costs in Stripe and billing dashboards.
Billing dashboards show you what already happened. AtlasBurn helps you understand what's likely to happen next — and gives you guardrails to act on it before the next invoice.
My burn is fine right now.
That's great. But AI API costs tend to change faster than expected as usage scales. AtlasBurn helps you stay ahead of that curve so there are no surprises.
This sounds like another monitoring tool.
Monitoring shows you metrics. AtlasBurn adds forecasting and cost controls on top — so you're not just watching numbers, you're setting guardrails that protect your runway.
Can't I just build this myself?
You could, but it takes meaningful engineering time to build cost tracking, forecasting, and alerting across multiple AI providers. AtlasBurn handles that so your team can focus on product.
Know your AI costs. Control them.
If you're building with AI APIs, AtlasBurn helps you understand and manage what you're spending.
Book a Strategy Call
AI API cost intelligence. Simple visibility. Real control.