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Agenta is an open-source LLMOps platform for building reliable AI apps. Manage prompts, run evaluations, and debug traces. We help developers and domain experts collaborate to ship LLM applications faster and with confidence.
Grounded in available product and source data
Prompt management for LLM projects often breaks down as teams grow: prompts scatter across ad-hoc tools, developers and domain experts work in silos, and deployments ship without validation, turning debugging into guesswork. Agenta was built to close that gap — it is an open-source LLMOps platform that helps developers and domain experts build and ship LLM applications together, centralizing prompt management, evaluation, and observability in one place so teams work from the same source of truth.
The platform is organized around three activities. In the playground, teams can compare prompts and models side by side and keep a complete, model-agnostic version history. For evaluation, Agenta replaces manual guesswork with automated evaluation, supporting LLM-as-a-judge, built-in evaluators, custom code, or human evaluation. For observability, it traces every request so teams can find failure points, turn any trace into a test with one click, and monitor production behavior with live evaluations.
According to Agenta's documentation, its open core — including all SDKs, client libraries, and APIs — is MIT licensed, and it can be self-hosted, modified, and used in commercial projects without restriction. The site also states it integrates with frameworks such as LangChain and LlamaIndex and with models including OpenAI. The documentation does not specify which parts, if any, sit outside this open core — such as hosted or enterprise-only features — so teams considering self-hosting should check the repository rather than assume full parity with any hosted version.
Agenta is an open-source LLMOps platform that developers and domain experts use to manage prompts, run evaluations, and debug LLM application traces together, instead of working across scattered, siloed tools.
Yes — according to Agenta's documentation, the UI lets domain experts work directly in the playground to compare prompts and models, and run evaluations (LLM-as-a-judge, built-in evaluators, or human evaluation) without touching the codebase, rather than needing a developer to make every change.
Yes — the MIT license covers the open core: all SDKs, client libraries, and APIs, which can be self-hosted, modified, and used commercially without restriction. The documentation does not state pricing or support terms for a hosted or managed version, so teams weighing self-hosting against a managed option should check directly with Agenta for those details.
Agenta's site states it integrates with frameworks such as LangChain and LlamaIndex and with models including OpenAI, letting teams connect their existing LLM stack to the platform. The source does not list which other specific models beyond OpenAI are supported.
