Dataiku, The Universal AI Platform™, recently announced the launch of AI Agents with Dataiku. This new set of capabilities is designed to create and control AI agents at scale, delivering a new class of AI applications powered by analytics, predictive models, and agents. Here are the details;
Dataiku has witnessed rapid acceleration of GenAI and AI agent adoption over the past year. Over 20% of customers now use Dataiku to integrate GenAI into their business and data workflows, with multiple projects per customer exceeding 1,000 active use cases.
As companies continue their rush to deploy agents, many create clumsy architectures where agents operate without proper IT control, vary in quality and relevance, and are sprawled ungoverned across teams. Dataiku solves this by augmenting The Universal AI Platform with agents as true enterprise systems — grounded in trusted data, embedded in operational workflows, connected to all AI inputs, and governed with the same rigor as any business-critical asset.
“AI is raw power — and it’s time for companies to take control. Companies are on the verge of repurposing two decades of enterprise applications built on systems like Snowflake, Workday, and SAP with a new layer of AI-native applications. These applications demand a combination of analytics, models, and agents that only Dataiku can deliver,” explained Florian Douetteau, co-founder and CEO of Dataiku.
“As companies mature from exploring to operationalizing agents, they’ll quickly realize the need to centralize their creation for proper governance instead of letting them sprawl, continuously optimize their performance instead of letting them stale, and fully orchestrate them through existing IT assets instead of raising technical debt. We’re building the required capabilities now in The Universal AI Platform for this emerging market need,” Douetteau added.
Centralized Agent Creation for Full Governance
Companies are already beginning to feel the pain of agentic initiatives everywhere in the organization without rationalization or control. Dataiku supports the central creation of agents with visual agent, a no-code option ideal for non-technical business users, and code agent, a full-code option ideal for developers — both available in the same platform, with key capabilities to ensure governance:
Managed Agent Tools for guaranteeing quality and validation of tools used by agents.
GenAI Registry for strategic oversight, with agentic use cases centrally reviewed, business value assessed, and risks evaluated.
Sign-offs for risk monitoring, with validation workflows off before moving to production.
Dataiku LLM Mesh Architecture for Secured Agentic Orchestration
Agentic ecosystems pose growing security and governance risks, especially as models evolve rapidly, and costs remain difficult to monitor. IT teams are caught between building and maintaining their own guardrails, locking into a single vendor, or allowing open experimentation — each path introducing its own risks to scale and control.
Dataiku provides a robust set of capabilities for IT to orchestrate agents at scale. These capabilities include:
The Dataiku LLM Meshtomanage model access across all providers, either for proprietary models (OpenAI, Anthropic, Mistral), through cloud services (Bedrock, Azure, Gemini), or via open source models like Llama and DeepSeek through self-hosting.
Dataiku Safe Guard to flexibly define and apply guardrails.
Agent Connect to centralize agent access across the organization from a single interface, for either dispatching requests to a single agent or having multiple agents working in concert to solve users’ requests.
Observability and Performance Monitoring for Continuous Agent Optimization
AI agents are brittle and dynamic systems: they can generate unexpected errors, and their performance can degrade over time. Companies adopting agents need to move to a mindset of continuous optimization, where agent testing and performance monitoring is routine. Dataiku provides a deep set of capabilities for agent observability and performance monitoring, including:
Trace Explorer for full transparency into agent decision-making, input/output flows, and debugging.
Quality Guard to evaluate and monitor agent performance continuously with LLM-as-a-judge, evaluation sets, and golden datasets.
Cost Guard for real-time usage tracking, budget enforcement, and internal rebilling.
Connect Your Agents to Your Business
With a uniquely agnostic approach to agentic AI, Dataiku supports all major cloud environments, model providers, and data platforms, including Snowflake, Databricks, Microsoft, AWS, Google, and more — allowing agents to run wherever enterprise data and analytics already live. Because agent development is embedded inside Dataiku’s broader Universal AI Platform, customers can fully integrate agents into existing data pipelines, MLOps workflows, and model governance processes, eliminating duplication and delivering higher ROI.
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