AI Observability by OpenObserve is an OpenTelemetry-native observability tool for AI agents and LLM applications. It traces every agent session across models, tools, services, datastores, and user sessions, showing where time, cost, and quality are lost. Teams can detect loops, run online evaluations on live traffic, attribute cost per token, and follow failures from the LLM call through backend and database alongside logs, traces, and metrics from the rest of the production stack.
AI Observability by OpenObserve
OpenTelemetry-native observability for agents and LLMs
AI Observability by OpenObserve Introduction
Key Features
- End-to-end tracing of agent sessions across models, tools, services, and datastores
- OpenTelemetry-native instrumentation
- Cost attribution per token and per request
- Detection of agent loops and anomalous behavior
- Online evaluations (evals) scored on live traffic
- Correlation of LLM calls with backend logs, traces, and metrics
Use Cases
- Diagnosing why an AI agent is slow or expensive
- Debugging agent failures across the full stack, from LLM call to database
- Monitoring quality of LLM outputs on production traffic
- Tracking and attributing AI cost across models and tools
Why Startups Use It
Startups building AI agents and LLM features need visibility into cost, latency, and output quality without stitching together multiple monitoring tools. AI Observability by OpenObserve combines agent tracing, online evals, and cost attribution with full-stack observability in one OpenTelemetry-native platform, helping small teams debug faster and control AI spend.
Alternative Options
LangSmith, Langfuse, Arize Phoenix
Frequently Asked Questions
What is AI Observability by OpenObserve?
An OpenTelemetry-native observability product for AI agents and LLMs that traces agent sessions, attributes cost, scores quality, and correlates LLM activity with the rest of your production stack.
Which standards does it support?
It is OpenTelemetry-native, allowing instrumentation through existing OpenTelemetry workflows.
How is it priced?
According to the product's website, it is priced per GB. Check the vendor's site for current pricing details.
Can it debug failures beyond the LLM call?
Yes, it lets you follow failures from the LLM call through your backend and database, alongside logs, traces, and metrics from the rest of your production stack.
More About AI Observability by OpenObserve
PricingPaid
Listed DateSep 11, 2026
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