Agenta
Open-source LLMOps platform for prompt engineering, evaluation, and observability in one workspace.
In short
Agenta bundles prompt playgrounds, evaluation harnesses, and tracing into one open-source workspace. It is best for product teams where non-engineers need to iterate on prompts alongside developers.
Pick Agenta if you want a single open-source workspace where PMs, engineers, and domain experts can iterate on prompts and evals together.
Skip it if you're a solo dev who just needs basic logging, or if you've already standardized on LangSmith or Langfuse.
Agenta is an open-source LLMOps platform that bundles the three things every team building on LLMs ends up writing in-house: a prompt playground with versioning and side-by-side model comparison, an evaluation harness with custom evaluators and human feedback, and request-level observability with tracing. The promise is full API and UI parity, so engineers can script the same workflows that PMs and domain experts run from the dashboard.
It sits in the same category as LangSmith, Langfuse, Helicone, and PromptLayer, but leans harder on the collaborative prompt-engineering side and the open-source positioning. You can self-host it or use the managed cloud at cloud.agenta.ai. Integrations with LangChain, LlamaIndex, and any OpenAI-compatible model mean it slots into existing stacks without forcing a framework rewrite, which is the main reason teams pick it over more opinionated tools.
Best fit is product teams shipping LLM features who want non-engineers actually iterating on prompts instead of pinging the dev team in Slack. Pricing on the cloud tier is tiered (free dev tier plus paid plans), and the OSS version covers most of the core workflow if you're willing to run the containers yourself.
Agenta is one of the more credible open-source answers to LangSmith, and the collaboration angle is genuinely useful when non-engineers own prompt quality. It's not the most polished option on the market, but the self-host story and framework-agnostic stance make it an easy pick for teams allergic to lock-in.
— The AI Tool Bible editorial team
Pros
- ✅ Open-source with self-host option, no vendor lock-in
- ✅ Covers prompt engineering, evals, and observability in one tool
- ✅ Full API/UI parity lets PMs and engineers share the same workflow
- ✅ Plays nicely with LangChain, LlamaIndex, and raw OpenAI calls
Cons
- ⚠️ Smaller community than LangSmith or Langfuse
- ⚠️ Self-hosting adds ops burden vs pure SaaS competitors
- ⚠️ Eval tooling less mature than dedicated eval-first platforms
Use cases
Frequently asked
- What core features does Agenta provide?
- It offers a prompt playground with versioning and model comparison, an evaluation harness with custom evaluators, and request-level observability with tracing.
- Can Agenta be self-hosted?
- Yes, Agenta is open-source and can be self-hosted, or you can use the managed cloud version at cloud.agenta.ai.
- Does Agenta integrate with existing LLM frameworks?
- It integrates with LangChain, LlamaIndex, and any OpenAI-compatible model, allowing it to slot into existing stacks without forcing a framework rewrite.
- Who is Agenta designed for?
- It is best for product teams shipping LLM features who want PMs and domain experts to iterate on prompts and evals without relying solely on engineers.
- What are the pricing options for Agenta?
- Pricing includes a free Hobby tier, Pro at $29/month, Business at $299/month, custom Enterprise plans, and a free open-source version.
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