With Rasa, all teams can create better text- and voice-based assistants. Rasa provides infrastructure & tools necessary for high-performing, resilient, proprietary AI assistants - that actually help your customers.
Flexible, customizable conversational AI for natural language understanding, dialogue management, and integrations. Used by developers, conversation teams, and enterprises.
Rasa’s state of the art NLU provides the technology to understand messages, classify intents, and capture key contextual information. Supports multiple languages, multi-intent messages, and both pre-trained and custom entities.
Rasa does dialogue differently. Assistants built with Rasa use machine learning to select the next action in the conversation, allowing you to better handle edge cases while eliminating complex decision trees.
Rasa gives you full visibility into your machine learning models, so you can understand and influence your results. Customize models for your unique data set, with a modular NLU architecture.
Don’t guess what customers want from your assistant—build it. Rasa provides the tools to capture critical feedback from end users and make it actionable, a process known as conversation-driven development. Conversation-driven development takes the guesswork out of figuring out what customers want from your assistant, so you can build assistants that solve problems on the first contact.
Your customers are unique, with unique needs and ways of communicating. Building a proprietary data set that represents your specific user base gives you a powerful competitive advantage. Rasa gives you the tools to build a data set from your assistant’s conversations and channel that data into improved performance and customer satisfaction.
Review conversations between customers and your assistant at scale, and quickly surface the most important interactions. Make informed decisions about your assistant’s development.
Create a training data set perfectly tailored to the way your customers talk. Quickly label user messages and turn them into training data to improve your model.
Rasa gives team members—from data scientists, to designers, to product owners—visibility into your assistant. Easily share your assistant with testers and analyze results.
Unleash innovation, not chaos. Rasa scales horizontally to help you meet new opportunities across your business. With a conversational AI framework that can go anywhere your customers are, Rasa’s flexible architecture extends your assistant across a nearly unlimited range of channels and integrations, on a stack designed to support an enterprise-wide conversational AI strategy.
Rasa powers assistants on multiple customer-facing platforms:
Looking for inspiration? Check out our community showcase →
Rasa includes 10 built-in messaging channels, including Slack, Facebook Messenger, Twilio, and more. Custom channel endpoints allow integration with any service or platform. Engage customers on multiple channels, powered by a single backend assistant.
Serve multiple geographic regions with an NLU engine that works with any written language. Expand to new markets without duplicating work.
Break down silos and avoid repeat work with every new conversational initiative. Rasa is transferable across use cases and business units, so you can re-use skills and apply development work from previous projects to new opportunities.
Ready-built starter pack assistants provide a blueprint for automating use cases like consumer banking and IT helpdesk operations. Starter pack assistants are free to download, completely open source, and come equipped with training data and industry-specific features. Shave weeks off your development time with our robust example assistants.
Our personal banking starter pack helps customers check their spending and earning history, transfer funds, and pay bills. The assistant can seamlessly switch tasks in mid-flow and includes a human handoff feature.
The IT helpdesk starter pack integrates with ServiceNow and automates the process of creating an incident. The assistant is able to pre-fill fields using information extracted from the user’s questions, streamlining the process of submitting a ticket.
SSO, RBAC, and on-prem deployment can be used to ensure compliance with company security policies
Build HIPAA-compliant AI assistants with Rasa Open Source
Keep customer data secure with on-prem or private cloud deployment