What Built On Databricks Means

A Built On Databricks product is an application, service, or solution in which Databricks forms the core intelligence layer powering the customer experience. These offerings allow partners to deliver data-rich, AI-enhanced functionality directly to their customers, often forming the foundation of entirely new product lines or premium features.

Built On Databricks solutions typically include some or all of the following characteristics:

Databricks provides the core analytics and AI engine, powering data processing, feature computation, machine learning, model serving, and agentic AI behavior.
Partners extend data and AI capabilities to their customers, enabling insights, automation, and intelligent decision-making within their applications or workflows.
Data, models, or notebooks may be shared securely and collaboratively with customers using Delta Sharing, Clean Rooms, or workspace-to-workspace sharing—without copying or moving data.
Applications leverage Databricks’ multi-cloud foundation, allowing partners to serve customers across cloud environments and meet them where their data already resides.
The user-facing experience is delivered through a custom application or persona-driven interface, while Databricks provides the secure, scalable, and governed backend capabilities.
AI-native functionality is accelerated through platform features, including vector search, fine-tuning, real-time model serving, and orchestration patterns for agents.

In short, Built On Databricks means using the Lakehouse Platform as the intelligence backbone of a product—empowering partners to deliver differentiated, data-driven and AI-enabled capabilities directly to their customers at enterprise scale.