Dataiku
Dataiku helps enterprises build and deploy AI and ML models responsibly at scale.
Dataiku is a centralized AI and data analytics platform that enables organizations to develop, deploy, and manage machine learning models and AI applications at scale. It serves enterprise teams across data science, analytics, and AI governance with tools for data preparation, model building, and responsible AI deployment. The platform bridges the gap between data experts and business users, providing a controlled environment for analytics and AI without requiring deep technical expertise. Customers like Unilever, Morgan Stanley, and J&J use it for use cases ranging from predictive maintenance to supply chain optimization.
Problem solved
Organizations struggle to move from basic analytics to enterprise-grade AI deployment while maintaining governance, security, and cross-team collaboration.
Target customer
Fortune 500 and mid-market enterprises with 500+ employees looking to democratize data science and AI across teams; companies in financial services, consumer goods, healthcare, and manufacturing.
Founders
F
Florian Douetteau
CEO & Co-founder
Master's in Mathematics and Computer Science from École Normale Supérieure; former VP of R&D at Exalead (sold to Dassault Systèmes for $150M) and CTO at IsCool Entertainment.
C
Clément Stenac
CTO & Co-founder
Former head of product development at Exalead, leading design and implementation of web-scale search engine software.
T
Thomas Cabrol
Co-founder
M
Marc Batty
Co-founder
Funding history
Series A
$3.6M
January 2015
Led by Serena Capital, Alven Capital
Series B
$14M
October 2016
Led by FirstMark Capital
Series B
$28M
September 2017
Led by Battery Ventures
· Historic investors
Series C
$101M
December 2018
Led by ICONIQ Capital
· Alven Capital, Battery Ventures, Dawn Capital, FirstMark Capital
Secondary
Unknown
December 2019
Led by CapitalG (Alphabet)
Series D
$100M
August 2020
Led by Stripes, Tiger Global Management
· Battery Ventures, CapitalG, Dawn Capital, FirstMark Capital, ICONIQ
Series E
$400M
August 2021
Led by Tiger Global Management
Series F
$200M
December 2022
Led by Wellington Management
Total raised:
$1.04B
Pricing
Custom enterprise pricing. Starts at $3,000-$4,000 per month for single users; 10-user licenses at $25,000/year; 100-user licenses at $150,000/year. Mid-market and enterprise deployments often reach six figures annually. Annual commitments required; contact sales for specific quote.
Notable customers
Unilever, GE, FOX News Group, Morgan Stanley, UBS, Walmart, Johnson & Johnson, BNP Paribas, Accor, LVMH, Engie
Tech stack
React (JavaScript frameworks)
jQuery (JavaScript libraries)
Bootstrap (UI frameworks)
Algolia (Search engines)
PHP (Programming languages)
MySQL (Databases)
Font Awesome (Font scripts)
Google Font API (Font scripts)
Typekit (Font scripts)
jsDelivr (CDN)
Google Analytics (Analytics)
Hotjar (Analytics)
Intercom (Live chat)
Linkedin Insight Tag (Analytics)
Matomo Analytics (Analytics)
Segment (Customer data platform)
AdRoll (Advertising)
Babel
WordPress (Blogs)
Yoast SEO (SEO)
HubSpot (Marketing automation)
Website
Competitors
Databricks
Focused on unified data and AI platform with stronger emphasis on data engineering; raised $1.6B making it well-funded but less established in end-to-end AI governance.
DataRobot
Specialized in automated machine learning with strong AutoML capabilities; narrower focus on model building vs. Dataiku's broader data-to-AI lifecycle approach.
Matillion
Primarily a data integration and ETL tool; lacks the comprehensive AI/ML development and deployment capabilities that Dataiku provides.
Altair
Broader analytics and simulation platform; less specialized in enterprise AI governance and responsible AI practices than Dataiku.
Why this matters: Dataiku achieved unicorn status in 2019 and has raised over $1B across 8 rounds, making it one of the best-funded AI/ML platforms globally. Its success reflects strong enterprise demand for responsible, governed AI platforms that democratize data science across organizations.
Best for: Enterprise organizations with 500+ employees that need to scale data science and AI across teams while maintaining governance, security, and responsible AI practices.
Use cases
Predictive Maintenance in Manufacturing
Manufacturing companies use Dataiku to build ML models that predict equipment failures before they happen, reducing downtime and maintenance costs. The platform's governance tools ensure models meet quality and compliance standards across production facilities.
Supply Chain Optimization
Enterprise supply chains leverage Dataiku to analyze historical data, forecast demand, and optimize logistics routes. The centralized platform allows cross-functional teams (supply, planning, finance) to collaborate on models without needing deep data science expertise.
Marketing Campaign Personalization
Consumer brands use Dataiku to segment customers, predict churn, and personalize marketing campaigns at scale. The platform enables marketers and data teams to iterate on models faster without waiting for data science handoffs.
Quality Control in Precision Engineering
High-precision manufacturers deploy Dataiku-built computer vision models to detect defects in real-time production. The platform's monitoring and governance features ensure models stay accurate and compliant over time.
Alternatives
Databricks
Choose Databricks if you prioritize unified data engineering and real-time analytics; choose Dataiku if you need stronger AI governance and end-to-end responsible AI capabilities.
DataRobot
Choose DataRobot for automated machine learning with minimal setup; choose Dataiku if you need more control, flexibility, and enterprise-grade governance across the full data-to-AI lifecycle.
H2O.ai
Choose H2O for open-source flexibility and developer-focused tools; choose Dataiku for a more comprehensive, enterprise-ready platform with stronger governance and cross-functional collaboration features.
FAQ
What does Dataiku do? +
Dataiku is an enterprise AI and data analytics platform that helps organizations build, deploy, and manage machine learning models and AI applications at scale. It provides tools for data preparation, ML model development, AI governance, and responsible deployment, serving as a bridge between data experts and business teams.
How much does Dataiku cost? +
Dataiku uses custom enterprise pricing starting at $3,000-$4,000 per month for individual users. A 10-user license costs $25,000/year, while 100-user licenses are $150,000/year. Mid-market and enterprise deployments often reach six figures annually. Contact sales for a customized quote based on your deployment needs and support level.
What are alternatives to Dataiku? +
Key alternatives include Databricks (unified data and AI platform), DataRobot (automated machine learning), Matillion (data integration/ETL), Altair (analytics and simulation), and H2O.ai (open-source ML). Dataiku differentiates with stronger governance, responsible AI practices, and cross-functional collaboration features.
Who uses Dataiku? +
Dataiku serves 750+ customers including 150+ Fortune 500 enterprises across financial services, consumer goods, healthcare, and manufacturing. Notable customers include Unilever, Morgan Stanley, UBS, Walmart, Johnson & Johnson, BNP Paribas, and GE.
How does Dataiku compare to Databricks? +
Databricks excels at unified data engineering and real-time analytics with a strong data lakehouse approach. Dataiku provides a more comprehensive end-to-end platform with stronger emphasis on AI governance, responsible AI practices, and democratizing AI across non-technical teams. Choose Databricks for data engineering; choose Dataiku for full data-to-AI lifecycle with governance.
Tags
machine learning
AI governance
data science
enterprise AI
predictive modeling
responsible AI
data analytics
model deployment
MLOps
data preparation