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PandaProbe Review

PandaProbe is an open-source agent engineering platform for deep observability, evaluation, monitoring, and debugging of AI agent applications.

shipped May 3, 2026freemium
PandaProbe - AI tool

Why it matters

1PandaProbe is an open-source, self-hostable platform developed by Chirpz AI.
2It provides deep observability, tracing, evaluation, and monitoring capabilities for AI agents.
3The platform supports debugging complex multi-step AI agents across LLMs, tools, and custom logic.
4PandaProbe offers a freemium pricing model, including a free tier for users.

Stork’s verdict on PandaProbe

PandaProbe offers deep observability for AI agents with open-source control, but it's likely overkill for basic LLM applications.

PandaProbe reviewed by Stork AI · stork.ai/en/pandaprobe

About PandaProbe

Business Model
Open Source
Headquarters
USA
Team Size
10-50
Funding
Bootstrapped
Platforms
Web, API
Target Audience
Developers and AI engineers

Pricing Plans

Free Tier
Free
  • • Self-hostable
  • • Open source
  • • Basic features
Cloud Tier
Varies / monthly
  • • Managed infrastructure
  • • Advanced features
  • • Support

Leadership

Chirpz AI TeamFounding Team
API DocsOpen Source

overview

What is PandaProbe?

PandaProbe is an agent engineering platform tool developed by Chirpz AI that enables developers, AI engineers, and platform teams to debug, evaluate, and monitor AI agent applications. It provides deep observability to trace, evaluate, and debug AI agents in both development and production environments. The platform is architected for scale and offers a unified solution for the entire AI agent development lifecycle, from initial runs to continuous improvement, ensuring reliability and quality in production.

features

Key Features of PandaProbe

PandaProbe offers a comprehensive suite of features designed for the observability and improvement of AI agent applications. Its open-source and self-hostable architecture provides flexibility and control for developers and platform teams. The platform's core functionalities are centered around understanding and enhancing AI agent behavior in complex, multi-step environments.

  • Open-source architecture allowing for self-hostable deployment and local control.
  • Deep observability specifically tailored for AI agent applications.
  • Comprehensive tracing capabilities, capturing full agent executions across LLMs, tools, sub-agents, and custom logic.
  • Research-grounded evaluation with agent-specific metrics and LLM-as-judge scoring for quality and regression detection.
  • Automated monitoring through scheduled evaluation runs against production traffic to detect behavioral drift.
  • Analytics for tracking performance, cost, latency, errors, and quality trends over time.
  • Debugging tools for complex multi-step AI agents where traditional logs are insufficient.
  • Session and user tracking to provide context and insights into AI agent application usage.

use cases

Who Should Use PandaProbe?

PandaProbe is primarily designed for technical professionals involved in the development and deployment of AI agents. Its capabilities address the specific challenges faced by engineers and platform teams in ensuring the reliability, quality, and performance of agent-based systems in both development and production environments.

  • Developers and AI engineers: For debugging complex multi-step AI agents involving LLM calls, tools, APIs, and sub-agents, and for ensuring the reliability and quality of agents in production.
  • Platform teams: For providing modern observability, evaluation, and monitoring infrastructure that supports AI agent development.
  • Builders experimenting with agents: For gaining deep understanding of agent behavior and continuously improving their AI agent applications.
  • Startups: For efficiently building, understanding, and shipping reliable AI agents with confidence, leveraging an open-source and scalable solution.

pricing

PandaProbe Pricing & Plans

PandaProbe operates on a freemium business model, providing accessibility for individual developers and offering scalable solutions for larger teams. The platform includes a free tier, allowing users to explore its core functionalities without initial investment. For advanced features, managed services, or higher usage, a Cloud Tier is available with variable pricing.

  • Free Tier: Free (includes core open-source functionalities and self-hosting options).
  • Cloud Tier: Varies (pricing is dependent on usage, features, and support requirements for managed cloud services).

Similar Tools

PandaProbe vs Competitors

PandaProbe positions itself as an open-source agent engineering platform specializing in deep observability for AI agent applications. While it shares some functionalities with broader ML platforms and other LLM observability tools, its focus on agent-specific metrics and full session evaluation distinguishes its offering in the competitive landscape.

1
LangfuseOn Stork

Langfuse is an open-source LLM engineering platform that provides comprehensive observability and evaluation capabilities with the flexibility of self-hosted deployment.

Like PandaProbe, Langfuse is open-source, self-hostable, and offers tracing and evaluation for AI agents. It provides a freemium model, similar to PandaProbe's pricing structure.

2
MLflowOn Stork

MLflow is the largest open-source AI engineering platform, providing a complete suite for debugging, evaluating, monitoring, and optimizing AI agents, LLMs, and ML models across the entire lifecycle.

MLflow is also open-source and offers robust debugging, evaluation, and monitoring for AI agents, aligning with PandaProbe's core features. However, MLflow provides a broader platform for the entire machine learning lifecycle, extending beyond just AI agent observability.

3
Arize PhoenixOn StorkCompare

Arize Phoenix is an OpenTelemetry-native, open-source observability and evaluation tool specifically designed for LLM applications, emphasizing vendor-neutral instrumentation and local data privacy.

Similar to PandaProbe, Phoenix is open-source and focuses on tracing and evaluation for AI applications. Its strong OpenTelemetry integration offers a vendor-neutral approach, which complements PandaProbe's self-hostable and scalable architecture.

4
AgentOpsOn Stork

AgentOps provides purpose-built observability for autonomous AI agents, featuring unique time-travel debugging, session replay, and multi-agent workflow visualization.

AgentOps directly targets AI agent observability, similar to PandaProbe, by tracking the entire agent lifecycle. Its distinct 'time-travel debugging' and comprehensive multi-agent visualization capabilities offer a different approach to debugging compared to PandaProbe.

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