Dataiku 11 unveils enhanced toolset to scale AI

Dataiku has released Dataiku 11, a critical update to the company’s data science and AI platform that enables organizations to deliver on the promise of Everyday AI.

This comprehensive release adds new capabilities for expert teams to deliver more value at scale, enables tech-savvy workers to take on more expansive challenges, makes it easier for non-technical workers to engage with AI, and strengthens AI Governance to ensure projects are robust, transparent and ready for success at scale.

“Expert data scientists, data engineers, and ML engineers are some of the most valuable and sought-after jobs today,” said Clément Stenac, CTO and a co-founder of Dataiku. “Yet all too often, talented data scientists spend most of their time on low-value logistics like setting up and maintaining environments, preparing data, and putting projects into production. With extensive automation built into Dataiku 11, we’re helping companies eliminate the frustrating busywork so companies can make more of their AI investment quickly and ultimately create a culture of AI to transform industries.”

Dataiku 11 builds on the company’s recent market momentum, which saw it surpass $150 million in annual recurring revenue and hire tech finance veteran Adam Towns as CFO. The company now serves over 500 enterprises worldwide, assisting leaders ranging from Boeing to Unilever in streamlining workflows, preventing customer churn, and improving financial performance.

Empowering the Expert Technical Community

In Dataiku 11, tech experts now have more tools at their disposal to do more and deliver more value from AI projects. Highlights from the release include:

• Built-in tooling for advanced users that reduces technical overhead and increases day-to-day efficiency when crafting custom code, performing model experiments, or sourcing high-quality datasets. 
• An end-to-end, visual path for computer vision tasks so that advanced and novice data scientists alike can tackle complex object detection and image classification use cases, from data preparation through to developing and deploying deep learning models. 
• A collaborative, managed framework for image annotation removes the need for teams to use outside tools or services for data labeling, ensuring tight alignment between subject matter experts, labelers, and modelers.

Collaborating With Your Skilled Workforce

Dataiku 11 also empowers non-coders, such as subject matter experts, citizen data scientists, and knowledge workers, with simple, no-code tools that enable any employee to leverage the power of AI to advance the business. Among the new tools are:

• Visual time series forecasting enables professionals to create robust business forecasting models without coding. 
• A centralized feature store and new sharing workflows make it easier for teams to safely reuse work, speeding projects responsibly.
• Powerful what-if accelerators help teams evaluate the best path to optimize business outcomes. For example, what changes could a manufacturer make to factory conditions in order to achieve the maximum production yield? Or for a bank, what adjustments to a consumer’s financial profile would lead to the lowest predicted probability of their defaulting on a loan?