Dataiku

Dataiku is a software company that enables organizations to manage their data science, machine learning, and production-grade artificial intelligence (AI) applications through a single platform. Guided by the concept of “Everyday AI,” the company aims to encourage both technical and non-technical users to work with data in the same environment. Founded in 2013, Dataiku now serves more than 700 enterprise customers across various industries worldwide. The company is headquartered in New York and operates offices in 13 different countries.

Founding

Dataiku was founded by Florian Douetteau, Clément Sténac, and Marc Batty. Florian Douetteau also serves as CEO. The executive team includes Clément Sténac as CTO, Adam Towns as CFO, Phil Coady as CRO, Carole Offredo as CMO, and Lynne Oldham as CPO. The board of directors includes representatives from various investors in the technology and finance sectors. Dataiku receives support from investors such as Battery Ventures, CapitalG, FirstMark, ICONIQ, Alven Capital, Dawn Capital, and Tiger Global.

Technology and Product Features

Dataiku adopts the “Universal AI Platform” approach, unifying data preparation, model development, machine learning, production AI, data governance, and collaboration on a single platform. The platform supports both no-code and code-first workflows and is compatible with languages and frameworks such as Python, R, SQL, Spark, and MLflow.

Users can track data processing steps through visual flows, build automation scenarios using pre-built components, and develop their own plugins. Dataiku integrates with projects of varying scales through built-in GPU support, Kubernetes integration, and infrastructure compatible with multiple cloud providers.

XOps Architecture and Workflows

Dataiku offers an XOps architecture that supports operational cohesion across multiple domains including DataOps, MLOps, LLMOps, and AgentOps. Processes such as model training, retraining, drift detection, and explainability reporting can be automatically managed. In LLM-based projects, security and governance features such as prompt validation, metric evaluation, and content filtering are integrated directly into the platform.

AI Agents

As of 2025, Dataiku has introduced the “AI Agents with Dataiku” feature to centrally create and manage AI agents. This system provides both a visual no-code agent development interface and full code-based developer options within the same environment. Agents can be deployed integrated with enterprise systems, powered by generative AI, analytical, and predictive models. Additionally, Dataiku works with models accessed via API from providers such as OpenAI, Anthropic, and Mistral, as well as locally hosted open-source models through its underlying infrastructure called LLM Mesh. Critical elements such as security, content filtering, and cost management are controlled through the Safe Guard and Cost Guard components.

Use Cases

Dataiku delivers customized AI solutions across numerous industries. In finance, banking, and insurance, it is used for customer acquisition, fraud detection, reporting automation, and risk management. In healthcare and pharmaceuticals, it supports clinical trials, production optimization, and patient engagement. In manufacturing, it is widely applied in quality control, predictive maintenance, and supply-demand forecasting. Significant use cases also exist in telecommunications, retail, and energy sectors.

Dataiku simplifies data preparation through more than 100 built-in data transformers, automated data profiling, and visual and code-based recipes. It offers native integration with numerous data sources including AWS S3, Azure Blob, Snowflake, Databricks, Google Cloud, Salesforce, and SAP. A comprehensive plugin ecosystem also enables users to create their own custom extensions.

The platform is enhanced with new infrastructure components such as LLM Mesh, Safe Guard, and Quality Guard to reduce operational complexity in AI projects and adapt rapidly to evolving model technologies. This approach allows organizations to maintain security and cost control while enabling flexible selection among different generative AI models.

Security and Compliance Features

The platform is equipped with features for data governance including a data dictionary, data quality rules, data lineage, authorization, and version control. Through the AI Govern module, approval processes, risk assessments, and compliance evaluations for all AI projects can be centrally managed. This structure has been specifically developed to prepare organizations for regulations such as the European Union AI Act.

Customers

As of 2025, Dataiku serves more than 700 enterprise customers, including multinational corporations such as General Electric, Sephora, Regeneron, BNP Paribas, Toyota, Michelin, Zurich Insurance, SLB, LG Chem, Ørsted, and Novartis. The platform is managed by over 1,000 employees worldwide and operates offices across Europe and Asia, in addition to its U.S. headquarters.

Academic and Social Responsibility Programs

Through its ikig.ai initiative, Dataiku supports nonprofit organizations with AI-powered projects. It also aims to promote AI literacy in education by providing free licenses and training resources to academic institutions. The Dataiku AI Lab conducts research to advance the field of data science.

In addition, Dataiku seeks to increase societal impact through community-based education initiatives, academic programs, and partnerships with civil society to ensure that AI is used in a more inclusive, sustainable, and accountable manner. In line with this, the “Everyday AI” vision is intended to extend beyond technical experts to all decision-makers and business units.