Dataiku and Slalom Join Forces to Bring AI to All

North American partnership combines Dataiku’s market-leading platform with Slalom’s human-centric consulting approach to AI business transformation

Dataiku, the platform for Everyday AI, announced a partnership with global consulting firm Slalom. Through the agreement, enterprise organizations will receive a cutting-edge platform from Dataiku to manage and govern projects, and a business partner in Slalom to guide AI and MLOps adoption and strategy.

“There is a natural alignment between Dataiku’s Everyday AI mission and Slalom’s human-centric approach to business transformation,” said Brian Power, Global Vice President, Consulting and System Integrator Partners at Dataiku. “We look forward to seeing the amazing things our customers are able to do by combining our market-leading platform with Slalom’s capabilities and localized services.”

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Together, Dataiku and Slalom will allow enterprise organizations to democratize the use of AI and MLOps, helping to improve decision-making, speed and efficiency while creating new opportunities for employees to innovate and think creatively. Slalom combines the vast experience of a global systems integrator with a local operating model, providing its customers with the benefits of community-based service alongside its world-class expertise.

“Technology enables solutions, but people deliver innovation and set the standard for growth,” said Tony Ko, Managing Director, Global Data, Analytics and AI at Slalom. “This is why Slalom goes beyond implementation — driving the training, adoption, and change management that allows customers to harness the capabilities of Dataiku’s Everyday AI platform.”

Through this partnership, Dataiku and Slalom will work closely with leading enterprise organizations across North America. These customers, in industries such as financial services, healthcare, pharmaceuticals, and retail and CPG, will tap into the combined platform and services to better plan and forecast, predict customer churn, develop recommendation engines, detect fraud and implement data governance, among many other use cases.

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