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DirectoryAI & ML PlatformsAI Governance & SafetyDataiku

Dataiku

About Dataiku

Dataiku provides a platform that brings analytics, models, and AI agents together in a single governed system. The platform orchestrates models, agents, rules, and human review into governed workflows. It allows business experts and engineers to build models, AI, and agents in one place. It tracks agent cost, performance, and risk in one place. It unifies visual ML, AutoML, and full-code development in one governed environment.

Used for

  • Building structured, multi-step agents using visual logic blocks or full-code frameworks
  • Joining, cleaning, and transforming data using visual recipes or Python, R, and SQL
  • Generating preparation steps, SQL queries, and Flow creation plans using natural language
  • Monitoring model drift, bias, LLM usage, cost, and performance across the lifecycle
  • Managing agents across Snowflake Cortex, Databricks, Vertex AI, Bedrock, and more

Who it is for

  • Used in financial services and banking.

From Dataiku's own website, read 2026-10-23. How we build listings.

How to evaluate AI Governance & Safety

This is how the CIOPages Research Team evaluates this category. It is not an assessment of Dataiku. It comes from our AI Governance & Responsible AI buyer guide.

25%
AI Inventory & Lifecycle Governance
Automated discovery and a registry of every model, LLM/prompt, agent, and embedded-AI feature (including shadow and third-party AI); risk tiering by use case; intake-to-retirement workflow with approvals, deployment gates, and named owners; versioning and change control
25%
Regulatory Mapping & Compliance Evidence
Out-of-the-box, maintained policy packs for the EU AI Act, NIST AI RMF, ISO 42001, SR 11-7, and sector rules (e.g. NYC LL144); control mapping and gap analysis; one underlying assessment that satisfies many frameworks; audit-ready, exportable evidence and model cards
20%
Model Monitoring & Explainability
Production monitoring for drift, performance decay, and data quality; bias and fairness testing across protected groups; explainability (e.g. SHAP / feature attribution) for tabular and NLP models; the depth of this domain is what separates observability tools from pure GRC
15%
GenAI & Agentic Oversight
LLM evaluation and guardrails (hallucination, toxicity, PII leakage, prompt-injection and jailbreak defense); agent discovery, runtime policy enforcement, and a logged trail of agent actions and the authority behind them; red-teaming and continuous evaluation of agent traces
10%
Integration & ML-Stack Fit
Connectors to your model platforms (SageMaker, Vertex AI, Databricks, Dataiku, MLflow, Bedrock), CI/CD and registries; API and policy-as-code coverage; identity (SSO/RBAC); fit with existing GRC and data-security tooling rather than yet another silo
5%
Human-in-the-Loop & Accountability
Cross-functional workflows that reach risk, legal, and business owners (not just data scientists); reviewer sign-off and attestations; issue and exception tracking; reporting that a board or regulator can read, with a defensible audit trail

CIOPages put this listing together from public sources. It’s information, not an endorsement. How we build listings. Work here? Claim this listing or .

Quick Facts

www.dataiku.com
CategoryAI & ML Platforms
SubcategoryAI Governance & Safety

We publish a detail only when we can point at the page it came from. Know when Dataiku was founded or where it is based? Send it to us, free.

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