Visual and code-based data preparation
Join, clean, and transform data with visual recipes or Python, R, and SQL. The Flow documents and versions transformations, with lineage, validation checks, and dataset certification.
An enterprise platform for teams building and governing analytics, ML models, and AI agents.
Dataiku is an enterprise AI platform that brings data preparation, analytics, machine learning, and AI agents into a shared, governed environment. Business experts, analysts, data scientists, and engineers can work with visual tools or code to move from raw data to production workflows.
The platform combines development, orchestration, and oversight: teams can connect enterprise data, build models and agents, deploy them into business processes, and monitor their operation. Policies, approvals, lineage, and risk controls support collaboration within guardrails set by IT.
Join, clean, and transform data with visual recipes or Python, R, and SQL. The Flow documents and versions transformations, with lineage, validation checks, and dataset certification.
Build, validate, and compare models using visual ML, AutoML, or code. Package models for APIs, batch scoring, and production pipelines, with deployment automation and performance monitoring.
Combine prompts, tools, APIs, and models into multi-step agents using visual logic or code frameworks. Agent Hub centralizes creation, collaboration, lifecycle management, and task routing.
Switch LLM providers through a shared layer with centralized routing, quotas, monitoring, and safety controls to manage usage, cost, and risk.
Maintain inventories and approval workflows for AI assets. Track model drift, bias, LLM usage, and agent cost, performance, and risk, including agents operating across other platforms.
Use Dataiku's built-in agentic interface to explore data, build governed AI, and oversee agents through natural-language interaction across the platform.
Analytics teams can prepare data on existing platforms and incorporate quality checks and documentation into repeatable pipelines for trusted business analysis.
Data science and engineering teams can turn experiments into scheduled scoring workflows or APIs, with model registries and approval processes supporting ongoing operations.
Process owners can combine agents, models, business rules, and human review into workflows that carry out a business process end to end.
IT and governance teams can assess agents built across multiple platforms, track their value and risk, and manage their lifecycle from a central location.
Dataiku supports both visual and code-based workflows. Analysts can use visual preparation and ML tools, while developers can use Python, R, SQL, and full-code agent frameworks.
The product page lists Snowflake, Databricks, Redshift, S3, APIs, and enterprise systems as connection options. It also supports compute using SQL, Spark, Kubernetes, and GPUs.
Yes. Dataiku describes third-party agent orchestration across Snowflake Cortex, Databricks, Vertex AI, Bedrock, and other platforms, alongside centralized agent monitoring and lifecycle management.
The website offers a trial signup and a demo request.
Traffic data is for reference only.
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