The platform for Everyday AI, Dataiku has announced breakthroughs in generative AI enterprise applications, safety, and tooling, pushing beyond traditional chatbot functions to unlock the potential for meaningful, real-world enterprise applications.

“We’ve seen hundreds of our customers exploring how to better leverage generative AI. Most have started to compile a list of potential use cases and evaluate them through the prism of feasibility, business impact, and risks,” Dataiku co-founder and CEO, Florian Douetteau said.

“We’ve distilled the top use cases which are real, actionable, and repeatable today, on our platform. The companies that succeed at this today are going to be out of reach of their competitors a year from now. This is the moment when the future winners are decided. It’s exciting for Dataiku to be part of it.”

Dataiku’s newly released Generative AI Use Case Collection is a leap forward in applying generative AI in the enterprise. Dataiku has built an initial batch of 16 generative AI use cases that apply this technology to real business needs. This new approach will allow enterprises to move out of an artisanal approach of building custom generative AI projects and into the industrial-scale development and deployment of these use cases.

Examples include Predictive Maintenance Data Explorer with automated generation of insights into the performance of factory machines, LLM-Enhanced Next Best Offer for the automated generation of promotional emails, including product recommendations, and IT Support Advisor with assistants that query complex policy documents and contracts.

With the arrival of policy proposals seeking to protect both workers and consumers from potential harms of AI, Dataiku is announcing its RAFT Framework (Reliable, Accountable, Fair, and Transparent) for generative AI use cases. The framework provides actionable steps that enterprises can take to be ready for future regulation. Taking into account enterprise realities and input of experts in public policy, digital ethics, and AI bias, the framework balances the need to move quickly while doing so safely and responsibly. 

“Popular imagination is hung up on a naive and limited vision of Generative AI’s potential. Simply put, you are not going to transform the way that an enterprise performs through one-off questions and answers to a chatbot. Real applications will see Generative AI being woven into a company’s data and machine learning workflows,” Dataiku co-founder and chief technology officer, Clément Stenac said.