Rasa is an open-source conversational AI platform for building contextual chatbots and intelligent agents.
Supercharge your conversational AI with Relevance AI's no-code agent builder to create powerful AI Agents that can understand, respond, and take action.
Rasa provides powerful natural language understanding and dialogue management. Relevance AI enhances this with no-code AI Agents that can handle complex conversations and automate sophisticated workflows at scale.
Contextual Understanding
The agent can comprehend user intent and context for more relevant interactions.
Dynamic Dialogue Orchestration
It can manage complex conversation flows, adapting to user responses in real-time.
Intelligent Personalization
It leverages user data to provide tailored responses and recommendations.
Relevance AI gives you access to Rasa's conversational AI capabilities through intelligent AI Agents within your automated workflows.
What you’ll need
You don't need to be a developer to set up this integration. Follow this simple guide to get started:
- A Rasa chatbot project
- A Relevance AI account with API access
- Authentication credentials (you'll connect using API keys—no sensitive info stored manually)
Security & Reliability
The integration leverages secure OAuth authentication to connect with your Rasa chatbot API, handling all HTTP methods seamlessly in the background. Relevance AI manages request formatting, authorization headers, and API paths automatically—eliminating common integration hurdles.
Built-in request validation and response handling ensure reliable communication between your workflows and Rasa's conversational AI platform.
No training on your data
Your data remains private and is never utilized for model training purposes.
Security first
We never store anything we don’t need to. The inputs or outputs of your tools are never stored.
Best Practices for Non-Technical Users
To get the most out of the Rasa + Relevance AI integration without writing code:
- Configure Rasa endpoints: Set up proper API endpoints and authentication tokens in your Rasa configuration.
- Structure conversations: Design clear conversation flows and intents before integration.
- Use OAuth carefully: Ensure proper authorization scopes are set when connecting Rasa accounts.
- Monitor responses: Test API responses with small payloads before implementing complex flows.
- Handle errors gracefully: Implement proper error handling and fallback responses for failed requests.
