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AgentaOpen-source LLMOps platform for building, evaluating, and deploying LLM apps

4.8 (4)
Daniel NikulshynReviewed by Daniel Nikulshyn·Updated July 2026

Overview

Agenta is an open-source LLMOps platform that helps teams develop, test, and ship applications powered by large language models. It brings prompt engineering, evaluation, observability, and deployment together in one workspace, so developers and subject-matter experts can collaborate on iterating LLM-based products. Users can experiment with prompts and model configurations side by side, run systematic evaluations against custom datasets, and trace requests in production to debug issues. Because it is open source, Agenta can be self-hosted, giving teams full control over their data and infrastructure while integrating with popular model providers and frameworks.

Key features

  • Prompt playground with side-by-side comparison
  • Custom and automated evaluations
  • Production tracing and observability
  • Versioning for prompts and configurations
  • Deployment of LLM apps as APIs
  • Integrations with major LLM providers

Pricing

Model
Freemium
Category
AI Agents
Rating
4.8 / 5 (4)

Use cases

Streamlining LLMOps for Teams

Agenta helps teams move from scattered workflows to structured processes by providing tools for centralized management, collaboration, and evaluation of LLM applications.

Iterating Prompt Design with the Whole Team

The unified playground feature allows teams to compare prompts and models side-by-side, while the ability to create a systematic process for running experiments and tracking results streamlines the development process.

Debugging and Validating LLM Applications

Agenta's features for automated evaluation, integrated feedback from domain experts, and comparison of full traces enable teams to replace guesswork with evidence and make data-driven decisions.

Pros & Cons

Pros

  • Open source and self-hostable
  • Combines prompt playground, evaluation, and observability
  • Supports collaboration between developers and non-technical users
  • Works with multiple LLM providers and frameworks

Cons

  • Requires setup and maintenance if self-hosted
  • Smaller community than some commercial alternatives
  • Learning curve for teams new to LLMOps

Reviews

4.8

Average from 4 ratings.

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Jamal Carter

Jamal Carter

Jan 14, 2026

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on integrations with major LLM providers, and open source and self-hostable caught me off guard. still, I'd recommend giving it a real trial.

HT

Hiroshi Tanaka

Dec 17, 2025

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on versioning for prompts and configurations, and supports collaboration between developers and non-technical users caught me off guard. Smaller community than some commercial alternatives is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Yuki Mori

Yuki Mori

Jul 6, 2025

Use it every day

Honestly didn't expect to like it this much. Integrations with major LLM providers is exactly what I needed, and works with multiple LLM providers and frameworks. but I reach for it almost every day now and it just clicks.

AK

Aisha Khan

Jun 16, 2025

Solid for our team

We rolled this out across the team last quarter and works with multiple LLM providers and frameworks. Deployment of LLM apps as APIs fits neatly into how we already work, and custom and automated evaluations removed a step we used to do by hand. but it has held up under daily use.

Q&A

What is included in the free open-source edition?

The open-source edition includes the core agent workspace: chat, projects, agent configuration, instructions, skills, tools, integrations, MCP servers, files, schedules, event triggers, tracing, evaluations, version history, role-based access control, and SSO. You can create unlimited users, projects, agents, and workflows on your own infrastructure.

Asked by Farah Rahimi · Jan 13, 2026

What is the difference between Agenta Cloud and self-hosted Agenta?

Agenta Cloud is operated by us. We run the application, storage, agent runner, upgrades, and backups. With self-hosted Agenta, you deploy and operate those components in your own infrastructure, connect your own model and integration accounts, and control where your data is stored.

Asked by Ravi Kapoor · Jan 1, 2026

What does trace data retention cover?

Trace data retention controls how long Agenta Cloud keeps technical execution records, including model calls, tool calls, timing, outputs, errors, evaluations, and annotations. Hobby retains trace data for one week, Pro for one month, and Business for three months. Enterprise retention is configurable. Trace data retention does not describe the retention of chats, project files, or persistent agent context. With self-hosted Agenta, you manage trace storage and retention in your own infrastructure.

Asked by Grzegorz Lewandowski · Dec 27, 2025

How can I estimate how many agent runs I need?

Count each message sent to an agent, each annotation, and each invocation started by a schedule or event. For example, one daily scheduled agent uses about 30 or 31 runs per month, one agent triggered every hour uses about 720 to 744 runs per month, and a chat with 20 user messages uses 20 runs.

Asked by Petra Vogel · Dec 25, 2025

Where can I monitor usage?

Open Settings, then Billing to see your current agent-run usage and plan allowance.

Asked by Giulia Conti · Dec 17, 2025

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