Enterprises and individual users are now able to utilize AI capabilities from Dataiku’s latest features, that is partly Cobuild on Snowflake; a solution aiming to help them translate their natural language commands into production workflows to help in designing and training AI applications. This new announcement reaffirms both companies’ partnership and is a reaction to the increasing demand from enterprises for explainable, scalable and governed AI solutions.
The development of Cobuild on Snowflake happens in the wake of the increased enterprise interest in generative AI solutions and agentic AI platforms. Nonetheless, enterprises continue facing problems with visibility, governance, compliance, and management despite their reliance on AI coding assistants in speeding up the process of software development. Enterprises are hesitant to adopt code generated through AI due to the need to ensure that such code has been validated and managed.
According to Dataiku, Cobuild applies the power of Snowflake Cortex AI together with the orchestration capabilities of Dataiku to turn business objectives into workflows related to data preparation, machine learning, AI agents, and enterprise applications. Business users, analysts, and technical experts can collaborate within a single platform without sacrificing inspection and production-readiness of the workflows.
Florian Douetteau, co-founder and CEO of Dataiku, said, “Consumer AI tools can make code appear instantly, but enterprises cannot afford to unleash opaque, unvalidated workflows into environments where accuracy, compliance, safety, and cost control matter. With Cobuild on Snowflake, organizations can bring the speed of AI-assisted development into a governed process with visual workflows that teams can inspect, validate, and improve before production.”
The platform is designed to help enterprises reduce complexity in AI deployment by combining Snowflake’s AI Data Cloud infrastructure with Dataiku’s orchestration and governance framework. Instead of relying on disconnected tools or black-box AI systems, enterprises can create workflows that remain transparent and manageable throughout development and deployment stages.
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Baris Gultekin, VP of AI at Snowflake, said, “Snowflake Cortex AI brings leading models directly to governed enterprise data, so organizations can build and run AI where their business context already lives. With Dataiku’s Cobuild, customers can accelerate how business intent is translated into visual, governed workflows that can be inspected, optimized, and operationalized at scale. That combination matters as enterprises move AI into production and need accurate systems that they can trust.”
The Cobuild functionality on Snowflake is another manifestation of a larger trend in enterprise adoption of artificial intelligence, in which AI governance and AI orchestration are just as vital as model performance itself. With companies adopting AI on a broader scale across their organizations, visibility into work processes, AI agents, and data pipelines becomes essential.
According to Dataiku’s recent announcement, the new offering comes under the company’s “Platform for AI Success,” which emphasizes the integration of people, orchestration, and governance to operationalize enterprise AI efforts at scale. As part of the recent developments, Dataiku unveiled several new capabilities focused on enterprise AI management earlier in the year, ranging from AI agent governance and reasoning systems to others. The new partnership brings Dataiku’s platform directly to the Snowflake ecosystem.
Given the nature of the partnership, there are high hopes for the collaboration between Snowflake and Dataiku as it will likely benefit those enterprises that operate within highly-regulated industries such as financial services, healthcare, manufacturing, and telecommunications. In those industries, it is crucial for businesses to have tools capable of creating AI workflows that comply with the requirements of explainability, governance, and operationalization.
With a growing number of enterprises transitioning from testing AI solutions to putting them into action and making them part of a business process, one can easily notice an emerging trend within the industry. Companies do not prioritize models’ generation anymore. Instead, their priority lies in governance, orchestration, and aligning AI with enterprise needs.
