Rasa

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Category:AI Agent Development Frameworks

Overview

Open-source conversational AI framework with Pro & Studio tools to build secure, production-grade chat and voice assistants.

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Best For Professions:

conversational ai engineers ml engineers solution architects cx leaders chatbot developers platform engineers

Rasa is an open-source conversational AI framework for building contextual assistants in text and voice. Teams use Rasa Open Source for NLU, dialogue, and channel connectors, and scale with Rasa Pro and Rasa Studio for enterprise features like governance, analytics, and a no-code UI. The platform supports on-prem or cloud deployment, integrates with messaging/voice channels and backends, and emphasizes data control, reliability, and extensibility for production CX use cases.

Autonomy level

54%

Reasoning: Rasa demonstrates moderate autonomy as a conversational AI framework. The agent can autonomously understand user intent through NLU, extract entities from conversations, manage dialogue flows using trained policies, maintain conversation context through its tracker system, and execute custom Python actions including API calls and database queries. ...

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Some of the use cases of Rasa:

Building multilingual chat and voice assistants with full data control.
Integrating assistants with channels like Slack, Twilio, and custom UIs.
Managing enterprise deployments with governance and observability via Rasa Pro.
Designing assistants visually with Rasa Studio and CALM-based flows.
Running on-premises or in private cloud for compliance-sensitive workloads.

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Pricing model:

freemium

Code access:

open-source

Popularity level: 75%