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Iterate faster, together

Unlock a powerful set of APIs and an intuitive user interface, along with our extensive customer success program

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Production Container Deployment

  • Run the Rasa Stack and Platform on-premise or in your private cloud with ready-to-deploy Docker containers and orchestration
  • Install everything with ease and scale it to your needs

Closing The Loop

  • See the logs of all user dialogues with analytics and help developers debug the failed ones faster by sending them extensive details to investigate
  • Improve directly from user dialogues with active learning and get automatic suggestions for what to add to your training data

Data Sync

  • Persist all training data in a database along with source and annotation metadata, with automatic 2-way sync with the user interface.
  • Access the latest version of your training data programmatically (API) from a single source of truth to train and experiment on any machine
  • Integrate your own backend services to push to and pull data from our Data API

Train Together

  • Label new or edit existing training data individually or in bulk for NLU as a team with just a few clicks in an intuitive visual interface
  • Try out the bot yourself in the chat interface or send it to your team members for further testing

Model Analytics

  • Train a new model, see how well your model performs and understand where it fails through an interactive confusion matrix
  • Keep your models consistent through versioning and pick the best one to run in production

Case Study

HIPAA compliant natural language understanding for a digital health assistant, allowing users to get their top health questions resolved while their data is secure

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Tia, a San Francisco-based healthcare startup, allows its users to answer health questions via natural language. The conversation happens within their own app, which has been downloaded thousands of times.


Being in the healthcare space, HIPAA compliance is very important. For this reason, Tia would have had to build their own natural language understanding AI. However, developing this from scratch takes months and requires specific AI and Machine Learning talent.


Tia decided to build their conversational natural language understanding on the Rasa Stack, which is actively used by thousands of developers worldwide. Extending this with the Rasa Platform for faster NLU training, Tia was able to set up in a few days what would have taken months. Adding more training data from real users makes the system more robust over time and increases the quality.

Next Step

Extension to a wider audience and the implementation of more skills to support even more requests.

A demo of the Rasa integration

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