Dataiku announced the launch of the Platform for AI Success, a strategic evolution of its enterprise AI platform designed to take enterprise AI from pilots into trusted and measurable business performance.
With the launch, Dataiku is setting a new standard with three first-to-market products: Dataiku Agent Management for cross-platform agent governance and business impact validation; Dataiku Cobuild for AI-assisted agent building in a visual, inspectable environment; and Dataiku Reasoning Systems for industry-specific decision intelligence delivered by teams of agents. Together, the new offerings redefine how enterprises build, connect, control, and scale AI systems.
The launch will be showcased at the Gartner Data & Analytics Summit in Orlando, March 9–11, Booth 401, where Dataiku will demonstrate how organizations can move beyond pilots to accountable, performance-based AI at enterprise scale.
“To achieve true AI success, enterprises face a critical conundrum,” said Florian Douetteau, co-founder and CEO of Dataiku. “Without bringing everyone into the building process, AI initiatives won’t be relevant or accepted; without orchestrating complex, modern technologies, AI will be too naive to have a meaningful impact; and without governing AI at every single step, it will never move beyond the proof-of-concept phase. We built our platform specifically to solve this exact roadblock.”
A Single Orchestration Layer for All Enterprise AI
AI is spreading across clouds, models, agents, and applications faster than most organizations can control it. In multi-vendor environments, fragmentation leads to duplicated work, inconsistent performance, governance blind spots, and rising operational risk. Without a unifying control layer, enterprises struggle to prove impact, manage cost, or defend decisions made by AI systems.
The Platform for AI Success provides that missing layer. It connects data platforms, enterprise systems, foundation models, and third-party agent frameworks in one governed environment. Dataiku integrates with all of them and depends on none. This allows organizations to preserve the freedom to use the best technology for each use case, avoid vendor lock-in, and maintain centralized oversight of AI performance across the enterprise.
Within a single platform, teams can build, validate, deploy, monitor, and manage AI systems with embedded governance and measurable business accountability.
The platform unifies three essential dimensions of enterprise AI:
- People: enabling domain experts, analysts, and engineers to contribute safely and productively at scale.
- Orchestration: coordinating data, models, agents, and decision logic into enterprise-grade systems.
- Governance: embedding visibility, validation, and performance measurement from design through ongoing operations.
New Capabilities Powering the Platform for AI Success
To support this evolution, Dataiku is introducing major new products:
Dataiku Agent Management: Measuring Business Value, Not Just Agent Uptime
As agents spread across enterprise systems, most monitoring tools are limited to observing whether they are running, with no ability to determine if they are actually delivering value.
An agent can be technically healthy while still failing the business — a blind spot that is increasingly common in organizations worldwide.
Designed as a standalone product, Dataiku Agent Management provides cross-platform visibility, governance, and business-impact measurement for every agent in operation, regardless of the system where it was created or runs. It evaluates agents against defined business KPIs, flags performance drift or cost concerns, and triggers governance workflows based on risk threshold and regulatory requirements.
Organizations can finally answer the questions that matter: What is running? What decisions are being made? What is my risk exposure? And, is this agent actually worth keeping in production?
Dataiku Agent Management Early Access Program is available today.
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Dataiku Reasoning Systems: Governed Orchestration Across Data, Models, and Agents
More than automation, Dataiku Reasoning Systems are coordinated, governed decision environments designed to scale institutional expertise into operational intelligence.
They unify data, models, agents, business rules, and human-defined decision logic into a single operational environment. Rather than deploying standalone agents for discrete tasks, enterprises can orchestrate governed decision systems that reflect how their business actually operates, embedding company and industry-standard reasoning directly into workflows while maintaining transparency and oversight.
The Dataiku Reasoning System for Manufacturing Operations is available now, with Supply Chain and Financial Risk scheduled for release later in 2026.
Dataiku Cobuild: Business-Friendly AI Pipeline and Agent Generator
Launching in June 2026, Cobuild allows users to describe a business objective in natural language and generate a complete AI project within Dataiku’s visual interface, including pipelines, models, agents, and applications as governed, traceable workflows.
Unlike AI coding assistants or “vibe coding” that produce opaque scripts, Cobuild creates a structured visual flow that users can review step by step, validate assumptions, and approve before deployment. Cobuild translates business intent into executable logic, while Dataiku’s execution engine handles environment configuration, resource provisioning, and deployment in a controlled, repeatable way.
The result is AI-assisted development with full transparency and control.
From AI Activity to AI Performance
The Platform for AI Success reflects a broader market shift. For companies around the world, competitive advantage no longer comes from access to models alone. Rather, it is the ability to coordinate AI systems across enterprise environments, empower business experts to contribute, and embed governance from design through ongoing operations.
“No amount of prompt engineering replaces structured orchestration,” said Clément Stenac, co-founder and CTO of Dataiku. “Real enterprise decisions require data feeding models, models informing agents, and agents controlled by a necessary combination of explicit business rules and human oversight. That coordination layer is missing in most deployments, so the Platform for AI Success is designed to fill that void.”
By positioning itself as the independent orchestration layer across infrastructure and vendors, Dataiku aims to help enterprises scale AI responsibly while maintaining agility in their technology choices.
