AtlasBurn

AtlasBurn helps AI teams understand where their AI spend is going and catch costly runtime behavior before it grows. It attributes spend across models, providers, features, workflows, and agents while detecting retry spikes, runaway loops, token bloat, unexpected model switching, and abnormal usage patterns. Teams can monitor real-time AI costs, forecast future spend, investigate anomalies, and enforce budget guardrails before expensive workflows turn into surprise invoices. AtlasBurn supports multi-provider AI workloads through SDK, proxy, and ingestion-based instrumentation, making it useful for AI-native startups, agentic applications, agencies, and teams operating production LLM systems. Instead of just showing what was spent after the fact, AtlasBurn is built around a simple idea: understand what is driving AI cost, predict where it is heading, and control it before it becomes a problem.