Dataiku

Dataiku is an enterprise AI and analytics platform that combines data preparation, machine learning, generative AI, and agent development in shared visual and code-based workflows for technical and business teams.

1. Data and analytics workflows: teams can prepare and transform data with visual recipes or code in Python, R, and SQL, then build analytics, machine learning models, dashboards, and applications within the same Dataiku Flow.
2. AI and agent development: Dataiku supports visual and code-based agents, while Agent Hub centralizes agent access, creation, sharing, and multi-agent interaction. Cobuild turns plain-language requirements into inspectable Dataiku projects containing data pipelines, machine learning models, agents, and applications.
3. Implementation checks: buyers should assess data connections, compute architecture, deployment topology, LLM and model-provider access, permissions, licensing, and how business and technical teams will collaborate across development and production environments.
4. Operational governance: Dataiku Govern provides centralized registries, governance workflows, policy checks, approvals, and sign-offs for data and AI initiatives. Deployment policies can also warn about or prevent deployment of unapproved project bundles and model versions.

Dataiku is particularly relevant to organizations that want visual and code-based teams working in the same governed environment across analytics, machine learning, generative AI, and production agent workflows.