AI agents built to scale in the enterprise
Build, run, and govern AI agents powered by your enterprise data, analytics, and business logic with the control and transparency enterprises require.
Everything you need to deliver AI agents at enterprise scale
Manage the full AI agent lifecycle from creation to continuous quality assurance in one enterprise system with built in control over cost, quality, and risk.
From idea to production without reinventing the wheel
Design, deploy, and operationalize AI agents end-to-end combining rapid creation, full-code flexibility, and reusable, governed assets that scale across the enterprise.
Visual agent creation
Translate enterprise requirements and business logic into production-ready agents using a visual interface with enterprise control built in.
Reusable, governed agent assets
Accelerate delivery with shared prompts, tools, templates, and agents standardized, approved, and reusable across teams and use cases.
Company-wide agent impact
Deploy agents across functions and workflows, so teams innovate within clear guardrails.
The control plane for all your agents
Centralize agent creation, orchestration, and oversight in one system so teams move faster without losing visibility or control.
Rapid agent delivery at scale
Move from prototype to production in one environment, with built-in testing, iteration, and lifecycle management that supports enterprise deployment.
Agents for enterprise decisions
Bring agents, tools, data, models, and knowledge together in a shared workspace to deliver decision agents aligned to real business processes.
Orchestrate third-party agents and systems
Integrate external agents, tools, and enterprise systems into governed agentic workflows without fragmenting architecture or accountability.
Governance and control across the agent lifecycle
Apply enterprise standards, manage LLM cost and risk, and continuously assure agent quality with governance built in, not bolted on.
Full visibility into agent behavior
Track agent usage, actions, and outcomes in one place maintaining accountability, auditability, and trust.
Control cost and safety
Enforce guardrails across LLM usage with centralized routing, quotas, and cost controls preventing runaway spend and unmanaged risk.
Assure business-grade quality
Define quality expectations upfront and continuously evaluate agents in production to ensure reliable, explainable outcomes.
Frequently asked questions
Dataiku provides an enterprise AI agent platform designed for secure, governed, and scalable deployment. Organizations can build, deploy, and orchestrate multi-agent workflows with centralized governance, approved LLM integrations through the LLM Mesh, and full lifecycle monitoring — ensuring agents operate safely in regulated environments.
Yes. Dataiku supports both no-code AI agent builders for business teams and full-code development for technical users. Teams can customize agent logic, orchestration, tools, integrations, and data access to fit unique enterprise workflows — whether building conversational AI, RAG applications, or autonomous task execution systems.
Dataiku includes built-in governance across the full agent lifecycle through centralized LLM routing and model management (LLM Mesh), role-based access controls and approvals, guardrails for prompts, tools, and data access, audit trails and monitoring dashboards, AI safety and compliance frameworks. This makes it a strong choice for enterprises seeking governed AI agent orchestration with full compliance controls.
Agents connect to approved enterprise data sources through governed access policies. The LLM Mesh enforces controlled use of data, tools, and models, ensuring privacy, relevance, and regulatory compliance while enabling context-aware AI workflows.
Dataiku provides centralized LLM usage management, including: model routing optimization, quotas and budget controls, usage tracking across agents and teams, spend visibility dashboards. This allows enterprises to proactively manage GenAI costs while scaling multi-agent deployments.
Built-in testing, evaluation, and monitoring capabilities allow continuous validation of agent outputs. Organizations can run automated evaluations, monitor drift and performance degradation, enforce quality assurance workflows, and mprove reliability as business needs evolve.