Introduction
Dataiku is a New York-headquartered software company that provides a platform for teams to build, deploy, and govern data science, machine learning, and generative AI projects. Founded in Paris in 2013, the company grew alongside the broader shift from ad hoc data science experiments to structured, production-grade AI operations inside large enterprises.
What the company does
Dataiku’s platform gives enterprise teams a shared environment to prepare data, build and test machine learning models, and, increasingly, design and manage AI agents. It supports a range of skill levels through visual, low-code, and full-code interfaces, so data scientists, analysts, and less technical business users can collaborate on the same project rather than handing work between disconnected tools. The platform connects to major cloud providers, data warehouses, and large language model vendors rather than locking customers into a single technology stack, and adds a governance layer that tracks how each model or agent was built, tested, and deployed.
Who it serves
Dataiku sells primarily to large enterprises with established data science and analytics functions, including manufacturing, financial services, healthcare, and consumer goods companies. Customers cited by the company include Johnson & Johnson, Toyota, General Electric, and BNP Paribas, reflecting a customer base centered on regulated or operationally complex organizations that need centralized governance over how models and AI agents are built and used.
Company background
Florian Douetteau co-founded Dataiku in Paris in 2013 together with Clément Stenac, Thomas Cabrol, and Marc Batty, after working on data and search problems at earlier technology companies, including the search engine startup Exalead. Douetteau has served as CEO throughout the company’s growth. Dataiku later moved its headquarters to New York while retaining a substantial engineering presence in France, and has raised total funding exceeding $846 million across multiple rounds, including a 2021 Series E at a $4.6 billion valuation and a 2022 Series F that valued the company at $3.7 billion following a broader pullback in software valuations. In October 2025, Reuters reported that Dataiku had hired Morgan Stanley and Citigroup to prepare for a U.S. initial public offering, with the company surpassing $300 million in annualized recurring revenue around the same time and serving more than 700 enterprise customers.
Product and AI capabilities
Dataiku’s platform spans the full lifecycle of an AI project: data preparation and pipelines, model training and evaluation, deployment and monitoring, and, more recently, the design and governance of generative AI agents. In 2026, the company introduced its “Platform for AI Success” positioning alongside three new capabilities: Dataiku Agent Management for governing agents built on different underlying technologies, Dataiku Reasoning Systems for industry-specific decision-making, and Dataiku Cobuild, an AI-assisted tool that lets business teams describe an objective in natural language and generate a governed, inspectable AI project. The platform integrates with model providers including OpenAI, Anthropic, Google Gemini, and AWS Bedrock, letting customers avoid depending on a single AI vendor.
Key developments
Dataiku hired Morgan Stanley and Citigroup in October 2025 to begin preparing for a U.S. initial public offering, according to Reuters, around the same period the company said it had surpassed $300 million in annualized recurring revenue. In March 2026, Dataiku launched its “Platform for AI Success” positioning, introducing Dataiku Agent Management and Dataiku Reasoning Systems, and in June 2026 it released Dataiku Cobuild, a natural-language AI project builder, to general availability.
Why it matters
Dataiku represents the governed middle layer between raw data infrastructure and production AI systems — a category that matters more, not less, as enterprises move from experimenting with generative AI to running agents against sensitive company data. Its pending move toward a public listing would also make it one of the few enterprise AI-platform vendors with a long operating history to test public markets during the current AI investment cycle.
Sector context
Within enterprise software, Dataiku’s focus on governance and multi-vendor model support distinguishes it from platform vendors like C3 AI, which packages more industry-specific applications on top of its own stack, and from workplace assistants such as Glean, which focus on search and retrieval rather than the full model-building lifecycle. It also differs from automation-first vendors like UiPath, which extends existing workflow automation with AI rather than serving as the primary environment where models and agents are built. As more enterprises look to deploy AI agents without losing oversight of how those agents behave, Dataiku’s emphasis on auditability and traceability has become a more central part of its pitch than it was earlier in the company’s history.
Sources and references
This profile is based on Dataiku’s official company and product pages, its own press releases describing 2025 and 2026 product launches, and independent reporting from Reuters on the company’s IPO preparations. Financial figures such as funding totals and valuation are drawn from public reporting and should be verified against Dataiku’s own disclosures where a formal filing becomes available.