What is Pezzo used for?

Pezzo is an open-source, cloud-native LLMOps platform for managing prompts, tracking versions, observing AI calls, caching responses and collaborating on LLM features. It is a good fit for managing prompts outside application code, debugging failing LLM calls in production, and tracking AI usage and cost across features.

Is Pezzo open source?

Yes. Pezzo is open source under the Apache-2.0 licence. Its source code is on GitHub at pezzolabs/pezzo and is written mainly in TypeScript.

Yes. Pezzo is open source, so the software itself is free to use.

Can I self-host Pezzo?

Yes. Pezzo can be self-hosted on your own server or infrastructure.

What is Pezzo an alternative to?

Pezzo is an open-source alternative to Weights & Biases and Vellum. Other open-source alternatives to Weights & Biases include Langfuse, Laminar and TraceRoot.

Is Pezzo actively maintained?

Yes. The most recent commit to Pezzo was on 21 August 2026, and the latest release is v0.9.2, published on 15 May 2024. The project has 3.3k stars on GitHub.

Pezzo: open-source alternative to Weights & Biases, Vellum

About Pezzo

Pezzo is an open-source LLMOps platform aimed at developers who build features on top of large language models. It gives teams one place to design and manage prompts, track versions, monitor and troubleshoot AI operations, and deliver prompt changes to applications without redeploying code.

The platform provides prompt management, observability and caching, with client libraries for Node.js, Python and LangChain. Teams can publish a new prompt version and have applications pick it up instantly, inspect requests and responses to find problems, and reduce cost and latency through caching. Topics on the repository also reference OpenAI, prompt engineering and monitoring.

Pezzo is built with TypeScript, Node.js and NestJS and depends on open-source infrastructure including PostgreSQL, ClickHouse, Redis and Supertokens, which can be started with Docker Compose. It is licensed under Apache-2.0 and designed to be run on your own infrastructure, with documentation covering architecture, tutorials and provider recipes. It suits product and engineering teams that want a self-managed prompt and observability layer.

Key features

Prompt management with versioning
Instant delivery of prompt changes
Observability of LLM requests
Response caching to cut cost and latency
Clients for Node.js, Python, and LangChain
Docker Compose deployment

Good fit for

→Managing prompts outside application code
→Debugging failing LLM calls in production
→Tracking AI usage and cost across features

Built with: TypeScript; Node.js; JavaScript; Python
Tags: llmops; prompt-management; observability; openai; llm; typescript; caching; self-hosted; monitoring

Pezzo: questions and answers

What is Pezzo used for?: Pezzo is an open-source, cloud-native LLMOps platform for managing prompts, tracking versions, observing AI calls, caching responses and collaborating on LLM features. It is a good fit for managing prompts outside application code, debugging failing LLM calls in production, and tracking AI usage and cost across features.
Is Pezzo open source?: Yes. Pezzo is open source under the Apache-2.0 licence. Its source code is on GitHub at pezzolabs/pezzo and is written mainly in TypeScript.
Is Pezzo free?: Yes. Pezzo is open source, so the software itself is free to use.
Can I self-host Pezzo?: Yes. Pezzo can be self-hosted on your own server or infrastructure.
What is Pezzo an alternative to?: Pezzo is an open-source alternative to Weights & Biases and Vellum. Other open-source alternatives to Weights & Biases include Langfuse, Laminar and TraceRoot.
Is Pezzo actively maintained?: Yes. The most recent commit to Pezzo was on 21 August 2026, and the latest release is v0.9.2, published on 15 May 2024. The project has 3.3k stars on GitHub.