MLOps Tooling: NLU Automation and Optimization Demo

As the adoption of Conversational AI bots increases, how to improve bot accuracy and performance, leading to better overall customer experiences is a challenge for most businesses. This time-consuming, often manual process typically involves exporting bot data, analyzing, identifying areas of improvement and manually uploading the changes. As we look at ways to optimize this process, MLOps opens up the opportunity for a more comprehensive approach of continuous improvement using both design and operational improvements that enhance bot performance and help overcome the challenges of training AI models.

In this 3-minute demo video, learn how to improve bot performance and accuracy with automated machine learning (unsupervised learning). In our suite of AI Insights tools, our automated machine learning tool provides you with a view into an existing bot’s performance, offers recommendations for improvements and provides an updated score that reflects bot accuracy after the improvements are applied.  In this self-service, containerized trial you will be able to analyze, review and identify recommended changes, within minutes with no configuration or integration required.< In this experience:

  1. Upload an existing bot for an analysis and accuracy score.
  2. Review the suggested changes for improved training and treatment of confusion.
  3. Export recommendations for model improvement.
  4. If you choose, meet with ServisBOT to integrate to your CI/CD process to automate changes and prevent regression

If you are interested in test driving this new experience using a sample bot or your own bot, visit our trial sign-up page

Seriously. Let's Talk.

Activate BOT Animations Request A Demo

Close this Window