Dataiku Reveals Deeper Integration with Generative AI in Dataiku 12 Release

Dataiku, the platform for Everyday AI, is unveiling Dataiku 12, offering transformative new features designed to help organizations confidently harness AI in their advanced analytics initiatives with enhanced transparency and strengthened governance.

"As we advance further into the era of AI, delivering trust via transparency and governance is now essential for any business aiming to stay at the forefront of innovation. Dataiku 12 directly addresses this need,” said Florian Douetteau, co-founder and CEO at Dataiku. “We’re empowering companies to confidently explore the vast potential of AI, while providing robust mechanisms for oversight and risk management. This fusion of power and control is the key to unlocking the full potential of AI in the most responsible way possible."

Dataiku 12 addresses the challenges of deploying AI while providing total confidence, control, and trust in AI outputs. The new features include:

  • OpenAI GPT Integration: Dataiku allows business users to incorporate OpenAI's GPT models into data projects by extending datasets and performing tasks using a visual interface and natural language prompts, all while maintaining transparency and trust in project outputs.
  • Causal Machine Learning (ML): Causal predictions ensure that correlation is not confused with causation, when doing so would be harmful to the business or other stakeholders. Dataiku democratizes these capabilities ensuring that anyone building ML models can understand the “why” behind their results.
  • Universal Feature Importance: Some ML models offer limited explanations for decisions, undermining trust with stakeholders. Dataiku centralizes model explainability, so teams have a consistent way to explain models that builds confidence and trust with business users.
  • Model Overrides: A core principle of AI safety is maintaining human oversight. In some cases, predictive models don’t have the best or safest answer, so Dataiku allows experts to create strict rules to enforce model outcomes for known cases, based on real-world experience.
  • Model Risk Project Views: With AI projects across teams at different stages of development, it is difficult to manage risks and allocate resources. Dataiku allows business and analytics leaders to easily spot and mitigate risks in AI projects, increasing trust in project outputs.
  • Transparent Automated Feature Generation: Feature engineering can be a "black box" in the AI modeling process, increasing perceived risk. Dataiku gives people transparency and control over this ML technique, helping to understand where new features originate.

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