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Agenta vs MLflow Prompt Optimization

Agenta

agenta.ai

MLflow Prompt Optimization

mlflow.org

Side by side

FigureAgentaMLflow Prompt Optimization
Price from$29/moFree
Free planYesYes
Free trial——
Open sourceYes—
WebYesYes
APIYesYes
Self-hostedYesYes
Plans published81
Spec score · AI Prompt Generators9.3 (#1)7.9 (#13)
Framework integrationsOfficial integration guides cover Agno, DSPy, Google ADK, LangChain, LangGraph, LlamaIndex, OpenAI Agents SDK, PydanticAI and Vercel AI SDK.The optimization workflow works with LangChain, LangGraph, OpenAI Agent, Pydantic AI, CrewAI, AutoGen, or custom frameworks.
SupportThe Hobby and Pro plans list community support through GitHub Issues, while Business lists priority support and a private Slack Connect channel.The self-hosted open-source option lists community support.

Plans

Agenta

  • HobbyFree
  • Open sourceFree
  • Pro$29 a month
  • Business$299 a month
  • EnterprisePriced on request
  • Enterprise (Cloud)Priced on request
  • Enterprise (self-hosted)Priced on request
  • Enterprise self-hostedPriced on request

Agenta pricing →

MLflow Prompt Optimization

  • MLflow Prompt Optimization (open source)Free

MLflow Prompt Optimization pricing →

In their own words

Agenta

Agenta is an open-source workspace for teams building and automating AI coworkers. Teams can interact with agents in Slack or Telegram, start from templates for engineering, customer support, sales, company knowledge, and operations, and run them on a schedule or in response to events. Its observability tools include traces, logs, errors, version history, evaluations, and token usage with estimated model costs. Agenta connects with services such as Slack, Notion, GitHub, HubSpot, Google Drive, Linear, Zendesk, and Discord, and supports more than 1,000 integrations. Listed model providers include OpenAI, Anthropic, Gemini, Mistral, and others. Cloud Hobby is free and allows two team members and 5,000 runs monthly; runs stop at that limit. Pro costs $29 a month and includes 10,000 runs monthly, with extra runs priced at $5 per additional 10,000. Model-provider charges are separate. Self-hosting is available, with users operating the application, storage, runner, upgrades, and backups in their own infrastructure. A mobile app supports agent conversations, approvals, and workspace management.

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MLflow Prompt Optimization

MLflow Prompt Optimization is an open-source, automated service for improving prompts through evaluation and iteration. It evaluates prompts against supplied data, identifies failure patterns, and generates revised variants. The `mlflow.genai.optimize_prompts` API provides a shared interface for optimization methods including GEPA and Metaprompting. You can provide training data, scorers, custom scorers, and aggregation functions, then save resulting prompts as new Prompt Registry versions. Runs, metrics, and traces support comparison and rollback. The workflow integrates with LangChain, LangGraph, OpenAI Agent, Pydantic AI, CrewAI, AutoGen, and custom frameworks, and works with any LLM provider. It supports API, self-hosted, and web access, with prompt variables, testing, and multiple-model support. GEPA is recommended for clear metrics and quality-critical work; documentation suggests 50–100 labeled examples, or at least 100 records for GEPA. The free Apache 2.0 option can be self-hosted or managed through cloud providers.

Visit mlflow.org