Dataiku company profile: valuation, funding & revenue

This Dataiku company profile covers the company's valuation, revenue, funding rounds, investors and history. Dataiku works in data and AI software, with a focus on enterprise AI and analytics platform. It was founded in 2013 and is headquartered in New York, New York, United States. Its latest valuation on record is US$3.7 billion (December 2022). Every figure links to a public source, and anything the company hasn't disclosed is marked as such.

Revenue

Funding history

Dataiku timeline

Key dates from the sources on this page, oldest first. Metric snapshots are listed after the funding events.

• 2013 — Dataiku is founded in New York by Florian Douetteau (CEO), Clément Stenac, Thomas Cabrol and Marc Batty.
• Aug 2021 — Series E: US$400M, valuing the company at US$4.6B. Investors: Tiger Global (lead).
• Dec 2022 — Series F: US$200M, valuing the company at US$3.7B. Investors: Wellington Management (lead).
• December 2022 — Total funding: About US$850 million.

Investors

Overview

Dataiku makes a platform that helps large organisations build and run data analytics, machine learning and generative AI projects. Its software brings together data preparation, visual and code-based analysis, model building, deployment, monitoring and governance in one place, so that data scientists, analysts, engineers and business users can collaborate. In recent years Dataiku has focused on helping enterprises use generative AI safely through its LLM Mesh, a layer that lets companies connect to many AI model providers while controlling costs, security and compliance.

Florian Douetteau, the CEO, Clément Stenac, Thomas Cabrol and Marc Batty founded Dataiku in Paris in 2013. The founders had worked on search, analytics and data science at French technology companies. Dataiku later moved its headquarters to New York while keeping a large presence in Paris and offices worldwide, and it is one of France's best-known enterprise software companies.

Products

• Data preparation: visual and code-based tools to clean, combine and transform data from many sources.
• Analytics and machine learning: AutoML, notebooks and visual model building for predictive analytics.
• MLOps: deploying, monitoring and retraining models in production.
• LLM Mesh: a gateway that connects enterprise applications to many large language model providers with controls for cost, privacy, security and auditing.
• AI agents: tools for building and governing generative AI applications and agents.
• Governance: oversight of all AI projects, including documentation and risk assessments for regulations such as the EU AI Act.

Funding

Dataiku raised from investors including FirstMark Capital, Battery Ventures, ICONIQ Growth, CapitalG, Insight Partners and Snowflake Ventures. In August 2021 it raised a US$400 million Series E at a US$4.6 billion valuation, led by Tiger Global. In December 2022 it raised a US$200 million Series F at a US$3.7 billion valuation, led by Wellington Management, a lower valuation than in 2021, reflecting the reset in software markets. Total funding is about US$850 million. We haven't found a newer priced round.

Business model

Dataiku sells enterprise subscriptions, typically priced by users and deployment scale, to large companies in financial services, pharmaceuticals, retail, manufacturing and other industries. Contracts are often large and multi-year. The company doesn't publish revenue, so we show it as not disclosed.

Competition

Dataiku competes with data and AI platforms such as Databricks and Snowflake, which have expanded into machine learning and AI tools; with cloud providers' AI platforms such as Amazon SageMaker, Google Vertex AI and Microsoft Azure Machine Learning; with analytics tools such as Alteryx and SAS; and with newer generative AI platforms. Its differentiation is its focus on collaboration across technical and business users and on governance for regulated enterprises.

Dataiku at a glance

Dataiku is a New York-headquartered enterprise AI company founded in Paris in 2013 by Florian Douetteau, Clément Stenac, Thomas Cabrol and Marc Batty. Its platform covers data preparation, machine learning, generative AI and governance. It raised US$400 million at US$4.6 billion in 2021 and US$200 million at US$3.7 billion in December 2022, led by Wellington Management.

Timeline

• 2013: founded in Paris.
• 2015–2019: expands to the US and raises Series B through D.
• 2019: becomes a unicorn with investment from CapitalG.
• August 2021: raises US$400 million at US$4.6 billion.
• December 2022: raises US$200 million at US$3.7 billion.
• 2023–2025: launches LLM Mesh and generative AI and agent tools.

Why governance matters for enterprise AI

Large organisations often run hundreds of AI and analytics projects across departments. Without central oversight, they risk duplicated work, inconsistent data, uncontrolled costs and models that breach regulations or produce biased results. Banks, insurers and pharmaceutical companies in particular must document how models work and prove they are fair and reliable. Platforms with built-in governance help these organisations scale AI while meeting regulatory and internal standards, a need that has grown with generative AI and new rules such as the EU AI Act.

The LLM Mesh approach

Many enterprises want to use several AI models: some from OpenAI, Anthropic or Google, some open models run privately, and some fine-tuned for specific tasks. Connecting each application directly to each provider creates complexity and risk. A gateway like LLM Mesh sits in between, routing requests, enforcing policies, filtering sensitive data and tracking costs. This lets companies switch providers without rewriting applications.

Who uses Dataiku

Dataiku's customers are mainly large enterprises, including banks, insurers, pharmaceutical and life sciences companies, retailers and manufacturers, where both data scientists and business analysts work on AI projects.

Risks

• Platform competition: Databricks, Snowflake and cloud providers bundle AI tools with data platforms.
• Valuation reset: its last round was below its 2021 valuation.
• Fast-changing AI market: generative AI tools evolve quickly, requiring constant product investment.

Questions for enterprise buyers

• How does the platform connect to your data platforms and AI providers?
• How are governance, auditing and regulatory documentation handled?
• Can both technical and business users work productively in it?

Valuation context

Dataiku's valuation fell from US$4.6 billion in 2021 to US$3.7 billion in 2022, one of the more visible down rounds among enterprise AI companies. Since then, investor enthusiasm for AI has risen sharply, but platform companies face pressure from data clouds and model providers. A future round or IPO would reveal how investors value its governance-focused approach.

Valuation and the AI boom

Generative AI has renewed interest in enterprise AI platforms, but much investment has flowed to model developers and infrastructure rather than platforms like Dataiku. How it captures generative AI spending will shape its next valuation.

Its partnerships with major data clouds and model providers will be important to that effort.

Latest developments (October 2026)

Reuters reported in October 2025 that Dataiku had hired Morgan Stanley and Citigroup to prepare for a possible US IPO as soon as the first half of 2026, according to a summary on Wikipedia. We found no completed listing or new priced round by October 2026, so its 2022 valuation of US$3.7 billion remains the latest sourced figure. Third-party estimates put its recurring revenue above US$340 million in late 2025.

What to watch

Watch for a new funding round or IPO plans, generative AI adoption among customers, partnerships with data platforms and competition with Databricks. Our guide to the largest European startups covers other European-founded companies.

Takeaways

Large enterprises can manage analytics and AI projects with strong governance. Founders can see how European companies scale by moving headquarters to the US. Investors should note its last round was a down round.

Sources

Every figure on this page comes from the public sources below. Where sources disagreed, we used the company's own announcement or a primary news report. Private-company data changes; check the date beside each figure.

1. Tech.eu
2. Orrick