Rasa Open Source Conversational AI Platform for Custom Chatbots
Rasa is a conversational AI platform that helps developers and teams build AI agents, chatbots and voice assistants with CALM, extending LLMs with structured flows and deterministic logic.
- Best for
- Customer Support Automation
- Key capability
- Natural Language Understanding
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Sign in or create a free accountWhat is Rasa?
Rasa is a conversational AI platform for building AI agents, chatbots and voice assistants with CALM (Conversational AI with Language Models), which pairs large language models with flows that define business logic. Developers can start with the pro-code Rasa Pro framework and add the no-code Rasa Studio interface for conversational AI teams. Rasa supports on-prem and private cloud deployment, giving enterprises control over their conversational AI.
Key features of Rasa
Rasa offers CALM dialogue understanding and management, language-agnostic natural language understanding, enterprise search, a custom actions server, REST and WebSocket channel connectors, Kubernetes deployment support and end-to-end testing.
Natural Language Understanding
Accurately classify user intents and extract entities from text inputs using machine learning models.
Dialogue Management
Manage multi-turn conversations with context-aware dialogue policies and state tracking.
Custom Actions
Execute custom backend logic and API calls during conversations to provide dynamic responses.
Open Source and Extensible
Built on open principles and inspired by its open-source roots, Rasa provides full access to prompts, policies, and the underlying codebase.
Multi-Channel Integration
Connect chatbots to platforms like Slack, Facebook Messenger, Microsoft Teams, and voice assistants.
Pros and cons of Rasa
Pros
- Full access to prompts, policies, and the underlying codebase
- Highly customizable and extensible
- Strong community and enterprise support
- Supports complex multi-turn conversations
- On-premise deployment for data privacy
Cons
- Requires programming knowledge to implement
- Steeper learning curve compared to no-code platforms
- Limited out-of-the-box integrations without custom development
Key use cases for Rasa
Customer Support Automation
Build AI-powered chatbots to automate customer service interactions, reducing response times and operational costs.
Virtual Assistants
Create intelligent virtual assistants that understand natural language and perform tasks such as booking, scheduling, and information retrieval.
Enterprise Chatbots
Develop custom chatbots tailored to specific business workflows and integrate them with existing enterprise systems.
Voice Assistant Development
Design voice-enabled assistants by integrating Rasa with speech-to-text and text-to-speech technologies.
Conversational AI Research
Use Rasa for experimenting with dialogue management and natural language understanding models.
How Rasa works
- 1
Install and Set Up
Prototype an agent in your browser without installing Rasa, or install Rasa locally and create a project.
- 2
Define Intents and Entities
Create training data by labeling user inputs with intents and entities to teach the model language understanding.
- 3
Design Dialogue Flows
Use Rasa’s dialogue management to define how the assistant should respond based on conversation context.
- 4
Train the Model
Train the NLU and dialogue models using your annotated data to enable accurate understanding and responses.
- 5
Integrate and Deploy
Connect your assistant to messaging platforms or voice channels and deploy it for real user interactions.
Who is using Rasa
Rasa pricing
Developer Edition
Free
Free Rasa license that can be used locally or in production: one bot per company, with up to 1000 external conversations/month or 100 internal conversations/month, and free community support in the forum.
Enterprise
Contact sales
For enterprises deploying conversational AI at scale: full access to Rasa Platform and Premium Support, with pre-built enterprise security features.
Plans and prices are as published by the vendor and can change. Check the official site before you buy. Open the pricing page (opens in a new tab)
Frequently asked questions about Rasa
Yes, the Rasa Developer Edition is free and gives you access to Rasa with CALM, within usage limits. Enterprise plans are available through sales.
Rasa is primarily built with Python and requires Python knowledge to customize and extend.
Yes, Rasa supports on-premise deployment, giving full control over data and infrastructure.
Rasa can be integrated with speech-to-text and text-to-speech services to build voice-enabled assistants.
This tool is designed to help users accomplish its core tasks more efficiently. It is typically used by individuals or teams looking to improve productivity and workflow.
Some tools offer a free plan or trial with limited features. Availability can vary, so confirm on the official website.
It depends on your specific needs and how you plan to use the tool. The official website and documentation are the best sources for the latest details.
Integration support depends on the tool and its available connectors or API. Check the official documentation or integrations page to confirm what is supported.
Conclusion
Agents are built on CALM, which uses large language models to understand a conversation while flows define the business logic an agent follows. Developers can work code-first, defining flows in YAML and connecting actions and tools, while Rasa Studio offers a no-code visual workspace for the same agent. Custom actions execute backend logic and API calls during conversations.
Deployment can stay on the team’s own infrastructure, a private cloud or fully offline environments. Customer support automation and enterprise chatbots integrated with existing business systems are typical use cases. The free Developer Edition allows one bot per company with a monthly conversation limit, while Enterprise adds full platform access and premium support.
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