Dataiku
Dataiku / dataiku.com
Enterprise AI and ML platform for collaborative data science, providing visual and code-based tools for building, deploying, and monitoring ML models and AI applications across teams.
Pricing
Free
Free plan
No
Category
Developer Tools
Platforms
1
Free plan
No
API access
Yes
Open source
No
Platforms
1
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What is Dataiku?
Dataiku is an enterprise AI platform designed for collaboration between data scientists, ML engineers, business analysts, and data engineers within a shared visual and code-based environment. Unlike tools focused on individual practitioners, Dataiku's strength is orchestrating the collaboration between different roles that enterprise ML projects require.
The visual flow builder allows users to build data preparation and ML pipelines by connecting steps graphically, making the project structure visible to all stakeholders rather than buried in code files only data scientists can read. Code users can extend any visual step with Python or R, while less technical users can configure steps through the visual interface.
AutoML capabilities allow creating predictive models through the visual interface without writing ML code, which helps business analysts contribute to ML projects without full data science expertise. The resulting models are production-ready and can be deployed and monitored directly from the platform.
LLM capabilities added through the LLM Mesh allow building generative AI applications — RAG pipelines, document processing, AI assistants — on top of models from OpenAI, Anthropic, Azure OpenAI, and local models, within the same governance framework as traditional ML.
Dataiku is strong in heavily regulated industries including financial services, healthcare, and manufacturing where governance, lineage, and audit capabilities are essential alongside ML development.
How Dataiku works
Dataiku runs as ml platform software built around data and text workflows. Users typically start with a prompt, upload, or connected data source, and the underlying model handles the heavy lifting before returning a result you can refine or export. It's available on web, with API access for teams that want to embed it into their own products.
Watch Dataiku in action
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What makes it worth shortlisting
The capabilities that matter most for teams evaluating Dataiku.
Visual flow builder
Graphical ML pipeline representation showing all steps from data ingestion through model deployment, making project structure visible to technical and business stakeholders.
Cross-role collaboration
Shared environment where data scientists, ML engineers, business analysts, and data engineers collaborate on the same project with appropriate tool interfaces for each role.
LLM Mesh
Unified layer for building GenAI applications using LLMs from multiple providers within the same project governance, lineage, and monitoring framework as traditional ML.
Best use cases
Who should use it
Pros
- Visual flow builder makes ML project structure visible to all stakeholders including non-data scientists
- Cross-role collaboration between data scientists, analysts, and engineers within one platform
- Strong governance and lineage features for regulated industry ML requirements
- LLM Mesh allows GenAI application building within the same governance framework as traditional ML
Cons
- No public pricing requires sales engagement
- Learning curve for technical data scientists who prefer code-first tools
- More expensive than pure code tools for teams that only need technical ML capabilities
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Is it worth the price?
No public pricing. Enterprise subscription with custom pricing. Free trial available. Community edition available.
Model
Subscription
Starting price
Free
Free trial
Yes
Tools like Dataiku
Databricks is stronger for large-scale data and LLM fine-tuning. Alteryx is a direct competitor for visual analytics and ML. DataRobot focuses more narrowly on AutoML for business teams. SAS Viya is the legacy regulated industry ML platform.
Dataiku vs IBM watsonx
A side-by-side look at the closest alternative in this category.
Dataiku
Dataiku
IBM watsonx
IBM
No public pricing. Enterprise subscription with custom pricing. Free trial available. Community edition available.
watsonx.ai free trial available. watsonx.ai usage-based from $0.50/CUH. Enterprise custom pricing. IBM Cloud account required.
SOC 2 Type II. ISO 27001. GDPR compliant. On-premise deployment for data sovereignty. Enterprise data handling agreements.
IBM enterprise security. SOC 2 Type II. ISO 27001. GDPR compliant. FedRAMP authorised. HIPAA eligible. Data residency options across IBM Cloud regions.
Review Dataiku's data handling policy. Cloud deployments process data on Dataiku's infrastructure. On-premise and private cloud options available for data sovereignty.
watsonx processes enterprise data within IBM security boundary. Data residency options allow data to remain within specific geographies. Enterprise includes data handling agreements.
- Visual flow builder makes ML project structure visible to all stakeholders including non-data scientists
- Cross-role collaboration between data scientists, analysts, and engineers within one platform
- Strong governance and lineage features for regulated industry ML requirements
- LLM Mesh allows GenAI application building within the same governance framework as traditional ML
- AI governance tooling is distinctive for regulated industries facing EU AI Act compliance
- Three-part platform addresses AI build, data, and governance in one vendor relationship
- IBM enterprise security across FedRAMP, HIPAA, and GDPR
- Strong for organisations with existing IBM infrastructure
- No public pricing requires sales engagement
- Learning curve for technical data scientists who prefer code-first tools
- More expensive than pure code tools for teams that only need technical ML capabilities
- Less model variety and ecosystem than OpenAI, Anthropic, or AWS Bedrock
- Higher cost and complexity than simpler AI API alternatives
- IBM reputation may not excite developers used to faster-moving AI platforms
Technical & deployment info
Key facts about model providers, platforms, and team support.
Model Provider
OpenAI, Anthropic, Azure OpenAI, Agnostic
Platforms
Web
Deployment
SaaS, On-premise
Integrations
AWS, Azure, GCP, Snowflake, Databricks, Tableau, Power BI, API
Team Collaboration
Yes
Launch Year
2013
Security & privacy
Compliance signals and data-handling notes as reported by the vendor.
SOC 2 Type II. ISO 27001. GDPR compliant. On-premise deployment for data sovereignty. Enterprise data handling agreements.
Review Dataiku's data handling policy. Cloud deployments process data on Dataiku's infrastructure. On-premise and private cloud options available for data sovereignty.
What users are saying
Verified reviews from signed-in users, stored in the backend and averaged into this tool's rating.
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Common questions about Dataiku
Editorial Verdict
Should you use Dataiku?
Dataiku is the best enterprise AI platform for organisations that need ML collaboration between technical and non-technical roles with strong governance for regulated industries.
Last verified July 24, 2026.