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Helicone vs LangWatch

Learn how Helicone and LangWatch differ in their key features, development activity, technology stack and community adoption, so you can decide which of these llm observability & evaluation is best for you.

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Favicon of Helicone

Helicone

AI
Open-source platform for logging, monitoring, and debugging LLM applications. Route, debug, and analyze AI apps with comprehensive observability tools.
6,153stars+84(+1.4%)

Last 30 days

Screenshot of Helicone
Favicon of LangWatch

LangWatch

AI
Tests AI agents through multi-turn simulations, LLM-based scoring, and production tracing so teams can ship reliable agents with confidence.
4,765stars+1,275(+37%)

Last 30 days

Screenshot of LangWatch

Detailed Comparison

Both Helicone and LangWatch have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.

Comparable
Community & Popularity

Both tools have similar popularity levels, with Helicone having 6,153 stars and LangWatch having 4,765 stars on GitHub. In terms of developer contributions, Helicone has 668 forks, indicating moderate developer engagement.

LangWatch wins
Growth Momentum

LangWatch is growing faster, adding 1,275 stars in the last 30 days (+37%) against adding 84 stars for Helicone (+1.4%). LangWatch is the smaller project of the two, so it is closing the gap rather than extending a lead.

Comparable
Development Activity

Both projects show recent activity, with Helicone last updated 2 days ago and LangWatch 9 hours ago.

Comparable
Technology Stack

Both tools share common technology foundations, being built with JavaScript, CSS, Bash, Typescript, JSX, Python. However, they differ in their additional technology choices: Helicone uses Next.js while LangWatch leverages SCSS, Golang, Ruby.

Comparable
Project Maturity

Both projects started around the same time, with Helicone beginning 4 years ago and LangWatch 3 years ago.

Comparable
Licensing

Both projects use the Apache-2.0 license, providing identical terms for usage and distribution.

Comparable
Use Cases & Features

Both tools serve similar use cases in LLM Observability & Evaluation.