Feature-level AI observability using real runtime data
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Orbit is a tool designed to provide comprehensive analytics on AI performance and cost at a feature level in production environments. It allows businesses to track real-time data on cost, latency, errors, and usage of AI features, providing insights into how each feature operates and its impact on overall expenses. Orbit enables users to understand which AI features are costly, slow, or failing by tying every large language model (LLM) call to a specific product feature and workflow. The tool offers feature-level analytics, error visibility, and cost trend analysis, helping teams to manage AI expenses effectively and avoid unexpected financial impact. Orbit supports multiple AI providers, ensuring secure data collection without intercepting requests or accessing API credentials. The solution helps organizations maintain efficient AI operations and prevents margin collapse by offering clear visibility into AI-driven workflows.
AI production spend and failures lack feature-level attribution.
SDK captures runtime calls to report cost, latency, errors per feature.
AI product, engineering, finance teams running LLM features.
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