AI Accelerators Library

This accelerator shows how users can quickly and seamlessly enable LLMOPs or Observability in their existing Generative AI Solutions without the need of code refactoring.

This accelerator aims to provide instructions on how to build this type of system using DataRobot's generative AI solution framework. The accelerator shows how you can build a pipeline to create a knowledge base with only trusted research papers, and build a conversational agent that can answer questions from medical professionals.

Deep dive into the utilization of zero-shot text classification for error analysis in machine learning models.

Use Generative AI and Prompt Engineering to consume cluster insights and create cluster labels for DataRobot clusters.

Use Predictive AI models in tandem with Generative AI models and overcome the limitation of guardrails around automating summarization/segmentation of sentiment text.

Integrate LLM based agents like ChatGPT with DataRobot prediction explanations to quickly implement effective customer communication in AI based workflows.