## Empowering Business Data Teams

Prophecy and Databricks bring together AI-powered development and enterprise-scale governance so business users can build, govern, and deploy data pipelines faster and with full confidence.

### Self-service productivity

Build pipelines visually on Databricks with Prophecy’s AI-powered canvas. Move faster, make decisions sooner, and cut costs by reducing backlog and cross-team friction.

### Governed native experience

Start from Partner Connect with full Unity Catalog integration. Get single sign-on, consistent governance, and native Databricks code that runs at scale and follows platform best practices.

### Path to production

Skip rework. Business users no longer rely on desktop prep tools that slow production. Prophecy pipelines are production-ready SQL or Spark code- tested, performant, and deployed through existing CI/CD workflows.

## Architected for Collaboration on Databricks

### Prophecy Studio

Prophecy Studio empowers every user to be productive.

**AI agents:** They take on an increasing share of data work, collaborating with users to build visual pipelines, reading requirements, and generating regulatory documents - all on the same formats as the user.

**Right interface:** Visual pipelines are the natural format for both users and AI agents. They’re easy to understand, edit, and extend.

**Code foundation:** Visual pipelines mirror underlying code, bringing software engineering best practices and smooth deployment to all users.

### Prophecy Automate

Traditional data engineering stacks fail to deliver a smooth experience in both development and production. Automate fixes that.

**Ingest and write:** Business users often read data from sources like SharePoint and write to Tableau or Power BI. Automate provides an intuitive interface and integrates directly with the visual pipeline canvas.

**Schedule and observe:** Pipelines can fail in production. Instead of deciphering stack traces, business users see their visual pipeline with the failing operator highlighted, the broken data surfaced, and an AI-suggested fix.

**Transform at scale:** Automate runs transformations natively on Databricks as optimized, high-performance code.