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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.
1PandaProbe is an open-source platform released under an Apache 2.0 license, offering self-hostable core features without limitations.
2The platform includes 11 built-in agent-focused metrics for comprehensive evaluation of AI agent quality and regressions.
3PandaProbe offers a free Hobby tier, providing 100 base trace ingestions and 100 trace evaluation runs per month.
4Launched on Product Hunt on May 3, 2026, PandaProbe supports automatic integrations for frameworks like LangGraph, CrewAI, and Claude Agent SDK.
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PandaProbe at a Glance
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About PandaProbe
Pricing Plans
Free Tier
Free / monthly
- • Self-hostable
- • Open source
- • Basic features
Cloud Tier
Varies / monthly
- • Managed infrastructure
- • Advanced features
- • Support
Leadership
Chirpz AI TeamFounding Team
📄 API DocsOpen Source
Connect
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X / Twitter@PandaProbe
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overview
What is PandaProbe?
PandaProbe is an agent engineering platform developed by Chirpz AI that enables developers and AI engineers to debug and improve their AI agents. It provides deep observability, evaluation, monitoring, and debugging for AI agent applications in both development and production. The platform offers a unified solution for the entire agent development lifecycle, from initial runs to continuous improvement, by capturing LLM calls, Multi-Agent Communication Protocol (MCP) calls, tool usage, workflow steps, and custom agent logic as structured traces and spans. Related traces are aggregated under sessions to provide a comprehensive understanding of an agent's full lifecycle. PandaProbe was launched on Product Hunt on May 3, 2026, addressing the challenges of understanding and trusting AI agents in production environments.
quick facts
Quick Facts
| Attribute | Value |
|---|---|
| Developer | Chirpz AI Team |
| Business Model | Freemium (Open Source core with Cloud tiers) |
| Pricing | Free (open-source core), Hobby (Free cloud tier), Pro ($99/month) |
| Platforms | Web, API |
| API Available | Yes |
| Integrations | LangGraph, CrewAI, Claude Agent SDK, major LLM providers |
| Founded | 2026 |
| HQ | USA |
| Funding | Bootstrapped |
features
Key Features of PandaProbe
PandaProbe provides a comprehensive suite of tools designed for deep observability and management of AI agent applications. Its architecture supports scalability and offers both open-source and self-hostable options, ensuring flexibility and control for developers. The platform's core functionalities are structured to cover the entire agent development and deployment lifecycle, from initial debugging to continuous production monitoring.
- 1Open-source and self-hostable core under an Apache 2.0 license, providing full feature access without vendor lock-in.
- 2Deep observability for AI agent applications, enabling detailed insights into agent behavior.
- 3Tracing capabilities for LLM calls, Multi-Agent Communication Protocol (MCP) calls, tool usage, workflow steps, and custom agent logic.
- 4Session aggregation to provide a comprehensive view of an agent's full lifecycle and related interactions.
- 5Evaluation features with 11 built-in agent-focused metrics to measure quality, reliability, and regressions over time.
- 6Monitoring functionality for scheduling recurring evaluations to automatically validate new traces and sessions in production.
- 7Analytics for tracking performance, cost, latency, errors, and quality trends of AI agents over time.
- 8Automatic integrations for popular agent frameworks, including LangGraph, CrewAI, and Claude Agent SDK.
- 9Zero-code LLM wrappers for major LLM providers, simplifying integration and tracing setup.
- 10Manual instrumentation options for developers requiring full control over custom agent architectures and logic.
use cases
Who Should Use PandaProbe?
PandaProbe is specifically designed for individuals and teams involved in the development, deployment, and maintenance of AI agent applications. Its robust set of features addresses the critical need for understanding, debugging, and improving complex agent behaviors across various stages of development and production.
- 1AI Engineers: To debug intricate agent behavior across diverse components such as LLMs, tools, and custom workflows, ensuring agent reliability.
- 2Platform Teams: To establish and maintain quality, monitor regressions, and ensure the overall reliability of AI agents operating in production environments.
- 3Builders Experimenting with Agents: To quickly identify and understand failures, facilitating faster iteration and improvement cycles during agent development.
- 4Developers: To leverage modern observability, evaluation, and monitoring tools, enabling the confident shipment of reliable AI agents.
pricing
PandaProbe Pricing & Plans
PandaProbe offers a freemium business model, combining a fully featured open-source core with cloud-based tiers to cater to different user needs, from individual developers to larger teams. The open-source option provides complete access to the platform's core capabilities, while cloud tiers add convenience and additional support.
- 1Open Source: Free. Users can self-host all core PandaProbe features without limitations under an Apache 2.0 license. This includes all core platform features, APIs, scalability, deployment documentation, and community support.
- 2Hobby: Free. This cloud-based tier includes 100 base trace ingestions per month, 100 trace evaluation runs per month, 10 session evaluation runs per month, human annotation capabilities, 1 seat, and community support via GitHub. No credit card is required to get started.
- 3Pro: $99/month. This tier offers expanded limits and features beyond the Hobby plan, catering to more intensive usage requirements.
competitors
PandaProbe vs Competitors
PandaProbe positions itself as an open-source, unified platform for the full AI agent development lifecycle, emphasizing deep observability. While the market for LLM and AI agent observability is evolving, several tools offer overlapping functionalities, each with distinct differentiators.
1
Langfuse↗
Offers a unified, open-source platform for LLM observability, prompt management, and evaluations with strong self-hosting capabilities and data control.
Like PandaProbe, Langfuse is open-source and self-hostable, providing comprehensive tracing and evaluation for AI agents. It also includes prompt management, which PandaProbe's description doesn't explicitly highlight.
2
Arize Phoenix↗
An OpenTelemetry-native, open-source observability and evaluation tool for LLM applications, emphasizing portable data and embedding analysis.
Phoenix is open-source and focuses on observability and evaluation for LLM applications, similar to PandaProbe. It leverages OpenTelemetry for tracing, offering a standardized approach, and provides embedding analysis.
3
LangSmith↗
Provides a complete AI agent and LLM observability platform with deep integration into the LangChain ecosystem, offering tracing, evaluation, and prompt playgrounds.
LangSmith offers comprehensive tracing, evaluation, and debugging for AI agents, similar to PandaProbe. It stands out with its native integration for LangChain users and offers self-hosting options for enterprise needs.
4
Comet Opik↗
An open-source platform for evaluating, testing, and monitoring LLM applications, providing tracing, annotations, and a prompt/model playground.
Opik, like PandaProbe, is open-source and offers tracing and evaluation for LLM applications. It provides a free hosted plan, similar to PandaProbe's freemium model, and includes a prompt and model playground.
5
DeepEval↗
An open-source LLM evaluation framework providing a wide array of research-backed metrics for testing and benchmarking LLM applications, akin to pytest for LLMs.
While PandaProbe offers evals as part of its suite, DeepEval specializes in a comprehensive, open-source evaluation framework with a strong focus on metrics and testing. It can be integrated with Confident AI for broader tracing and monitoring.
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Frequently Asked Questions
+What is PandaProbe?
PandaProbe is an agent engineering platform developed by Chirpz AI that enables developers and AI engineers to debug and improve their AI agents. It provides deep observability, evaluation, monitoring, and debugging for AI agent applications in both development and production.
+Is PandaProbe free?
Yes, PandaProbe offers a free open-source core that can be self-hosted without limitations under an Apache 2.0 license. Additionally, it provides a free cloud-based Hobby tier, which includes 100 base trace ingestions and 100 trace evaluation runs per month.
+What are the main features of PandaProbe?
PandaProbe's main features include open-source and self-hostable core, deep observability, tracing of LLM calls and agent logic, session aggregation, evaluation with 11 built-in metrics, production monitoring with scheduled evaluations, and analytics for performance and cost. It also offers automatic integrations for popular agent frameworks like LangGraph and CrewAI.
+Who should use PandaProbe?
PandaProbe is designed for AI Engineers to debug agent behavior, Platform Teams to monitor quality and reliability in production, Builders Experimenting with Agents to understand failures and iterate faster, and Developers seeking modern tools to ship reliable AI agents with confidence.
+How does PandaProbe compare to alternatives?
PandaProbe differentiates itself as an open-source, self-hostable platform focused on deep observability for AI agents. While competitors like Langfuse, Arize Phoenix, LangSmith, Comet Opik, and DeepEval also offer LLM/agent observability and evaluation, PandaProbe emphasizes its unified platform for the full agent development lifecycle and its Apache 2.0 licensed core, providing no vendor lock-in.