Frequently asked questions
Agenta is an open-source LLMOps platform designed to assist AI teams in building and deploying reliable large language model applications. It addresses common challenges faced by teams, such as the unpredictability of LLMs and the lack of structured processes. With Agenta, developers and subject matter experts can collaborate effectively by experimenting with prompts, running evaluations, and debugging production issues. The platform centralizes the LLM development workflow, allowing users to compare prompts and models, automate evaluations, and trace requests to identify failure points, ultimately enhancing the efficiency of AI development.
Agenta offers several key features that streamline the LLMOps process. These include the ability to experiment by comparing prompts and models side by side, track version history, and debug using real production data. It also provides automated evaluations to replace guesswork, integrates LLM-as-a-judge, and allows users to create custom evaluators. Additionally, Agenta enables users to observe and trace every request to identify failure points, turning any trace into a test with one click, and monitoring production with live evaluations.
Agenta is beneficial for AI teams, including developers and subject matter experts, who are involved in the deployment and management of large language models. It is particularly useful for teams looking to improve collaboration, streamline their workflows, and enhance the reliability of their LLM applications. By providing tools for experimentation, evaluation, and observation, Agenta helps teams overcome common challenges in LLMOps.