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Agenta

Agenta AI Agent
Rating:
(5 / 5 from 3 ratings)

Overview

An open-source LLMOps platform offering prompt engineering, evaluation, and observability tools for building robust LLM applications.

Agenta is an open-source platform designed to assist developers and product teams in building robust AI applications powered by Large Language Models (LLMs). It provides integrated tools for prompt engineering, versioning, evaluation, and observability, all in one place. With Agenta, users can rapidly experiment with prompts, manage prompt versions, evaluate application performance, and monitor usage and quality. The platform supports various LLM workflows, including chain-of-prompts and Retrieval Augmented Generation (RAG), and is compatible with frameworks like Langchain and LlamaIndex. Agenta aims to accelerate the development cycle of LLM applications by facilitating collaboration between developers and non-developers, such as product managers or domain experts.

Product overview

Capabilities, pricing and fit

Agenta is an open-source workspace for building, sharing, running, and improving specialized agents and automations. It combines interactive chat with background schedules and event triggers, connected tools, per-tool permissions, tracing, configuration history, evaluations, and team access.

Information as of August 9, 2026

What it can do

  • Interactive and background agents

    Agents can work with users in chat, be shared with a team, and run on schedules or events from connected applications.[3]

  • Agent controls and integrations

    Workspaces support files, tool permissions and approvals, MCP servers, reusable skills, and integrations with external applications.[3]

  • Tracing and improvement workflow

    Agenta records model and tool calls, token use, estimated costs, errors, and agent configuration versions, with evaluation and side-by-side comparison features.[2], [3]

Where it fits best

  • Teams building agents that work interactively in shared workspaces and also run on schedules or connected-app events.[3]
  • Organizations that need model and harness choice, tool permissions, run traces, configuration version history, and self-hosting options.[1], [3]

Pricing and availability

Agenta Cloud Hobby is free for two team members and 5,000 monthly runs. Pro is $29 per month, Business is $299 per month, and Enterprise is custom; the self-hosted open-source edition is free, while model usage is billed separately by model providers.[2]

Platforms: Agenta Cloud web workspace, Open-source web workspace[1], [2], [3]

Access: Vendor-hosted cloud, Self-hosted with Docker Compose[1], [2], [3]

Important considerations
  • Cloud plans do not include AI model costs; customers connect their own model-provider credentials and pay those providers separately.[2]
  • The free cloud plan is limited to two team members, 5,000 agent runs per month, 20 monthly evaluations, and one week of trace retention.[2]
Sources (3)
  1. Agenta - The open-source workspace for your agentsOfficial site · checked 2026-08-09
  2. Agenta PricingPricing page · checked 2026-08-09
  3. Agenta-AI/agentaGitHub · checked 2026-08-09

Autonomy level

38/100

Our subjective rating of how independently the product carries out its documented tasks, considering the human setup, input, approval and review it needs. This is not a measured success rate.

Reasoning: Agenta demonstrates moderate autonomy as an LLM observability platform that automates monitoring/tracing but requires explicit developer integration (2-line code implementation) and human analysis of collected data. While it auto-instruments frameworks like LangChain/OpenAI and provides automated trace collection, critical functions like prompt man...

Comparisons


Custom Comparisons

Some of the use cases of Agenta:

  • Experimenting with and refining prompts across different LLM models.
  • Managing and versioning prompts to ensure consistency and track changes.
  • Evaluating application performance using predefined or custom evaluators.
  • Collaborating between developers and non-developers on LLM application development.
  • Monitoring and debugging LLM applications with built-in observability tools.

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Popularity level: 65%

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