Rasa

Who should use Rasa

Rasa is aimed at developers, data scientists, and product teams that need full control over conversational AI. Whether you are building a customer‑service chatbot, a voice‑first home assistant, or an internal help‑desk, Rasa gives you the tools to design, train, and iterate on context‑aware dialogue models.

Core capabilities

The framework combines natural‑language understanding, dialogue management, and custom action execution. It supports a wide range of messaging platforms—including Slack, Facebook Messenger, Telegram, and Microsoft Bot Framework—as well as voice platforms such as Alexa and Google Home. Rasa’s machine‑learning pipelines let you train models on your own data, preserving privacy and enabling domain‑specific behavior. Extensible plugins and a rich SDK let you add custom logic, integrate APIs, or connect to any channel you can code.

Deploying your assistant

Rasa can be run locally, inside a virtual environment managed by Poetry, or packaged as a Docker image (rasa:localdev). Documentation, community forums, and a Jira‑backed issue tracker provide support throughout development. The open‑source codebase encourages contributions, and a commercial platform is available for enterprise‑grade support if needed.