PandaProbe
What is PandaProbe?
TL;DRPandaProbe is an open-source AI agent observability platform for tracing, evaluating, monitoring, and debugging agent workflows, with self-hosted and managed options for production engineering and AI teams.
- Trace full agent executions across LLMs, tools, and logic
- Score traces and sessions with agent-specific evaluation metrics
- Monitor latency, quality trends, token costs, and reliability
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About
PandaProbe is an open-source agent engineering and observability platform for tracing, evaluating, monitoring, and debugging AI agents. It is built for teams moving from local AI experiments into production workflows where normal application logs do not explain why an agent made a decision.
The product focuses on agentic APM. Developers can trace full agent executions, inspect LLM calls and tool steps, score sessions with agent-specific metrics, schedule recurring evaluations, track latency, monitor token costs, and watch quality trends across production traffic.
PandaProbe offers both a free open-source self-hosted option and a hosted cloud product. Its pricing page lists Hobby, Pro, Startup, Enterprise, and Open Source routes, making it useful for hobby projects, startups, and teams that need self-hosting or hybrid deployment.
For FutureStack, PandaProbe belongs in Developer Tools because observability is becoming required infrastructure for serious AI agents. It is best for teams using LangGraph, CrewAI, Claude Agent SDK, or similar systems that need traces, evals, reliability monitoring, and debugging depth.
Use Cases
Agent Observability
Trace agent executions across LLM calls, tools, logic, and sessions to understand production behavior.
Agent Evaluations
Score traces and sessions with custom evaluation metrics to measure reliability and quality over time.
Production Debugging
Inspect failures, latency, token costs, and execution details when an agent behaves unexpectedly.
Self-hosted Monitoring
Run an open-source observability stack for agent workflows when infrastructure control is important.
Key Features
- Trace full agent executions across LLMs, tools, and logic
- Score traces and sessions with agent-specific evaluation metrics
- Monitor latency, quality trends, token costs, and reliability
- Cloud plans plus free open-source self-hosting option
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Pricing summary
PandaProbe lists Hobby at $0/forever, Pro at $29/month, Startup at $299/month, Enterprise custom, and a free open-source self-hosted option.
Pricing & Plans
Hobby
Free hosted plan for getting started with agent traces.
Free
- 100 base traces/month
- 100 trace evals/month
- 10 session evals/month
- 1 seat
Popular
Pro
Developer plan for small production agent workflows.
$29/month
- 5K base traces/month
- 5K trace evals/month
- 100 session evals/month
- 2 seats
Startup
Higher limits for scaling agent projects.
$299/month
- 50K base traces/month
- 50K trace evals/month
- 1K session evals/month
- 10 seats
Other pricing notes
- Cloud plans use trace and evaluation limits, while the open-source self-hosted route is available separately.
- Enterprise terms can include custom support, SSO, hybrid, or self-hosted requirements.
Pricing last checked: July 2026Official pricing
Pros & Cons
Pros
- Strong fit for production AI agent observability
- Open-source self-hosting option reduces lock-in
- Clear cloud pricing for hobby, pro, and startup teams
- Supports traces, evals, costs, and monitoring together
- Useful for LangGraph, CrewAI, and agent SDK workflows
Cons
- Best value appears after real agent traffic exists
- Adds another system to operate or integrate
- Cloud overages can matter at high trace volume
- Teams still need to design meaningful eval metrics
- Enterprise needs may require custom sales process
The Best PandaProbe Alternatives
The best PandaProbe alternatives are Staso AI, LangChain, and Relevance AI.
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