Beyond Data: AI-First Collaboration with Apps, Genie Sharing, and MCP in Marketplace

Overview
| Experience | In Person |
|---|---|
| Track | Data Sharing & Collaboration |
| Industry | Enterprise Technology, Retail & Consumer Goods |
| Technologies | Data Marketplace, Databricks Apps |
| Skill Level | Beginner |
Data sharing got us this far. The next leap is sharing the intelligence on top of that data: the agents, applications, and AI experiences your partners and customers actually want. With Databricks Marketplace, the ecosystem is expanding from raw datasets to a full set of AI-first collaboration primitives: Genie Spaces, third-party applications, and MCP servers, all governed, and all running in the consumer's own environment.
In this session, we'll demonstrate three new ways to collaborate across organizational boundaries:
Genie Sharing: a first-of-its-kind privacy-safe agentic collaboration tool. Hand a partner a curated natural-language interface to your data instead of raw tables. Provider IP (instructions, benchmarks, knowledge store) stays hidden, while output is governed by aggregation-only columns, row limits, and query quotas. Recipients can even blend in their own data without exposing it back to the provider.
3P Apps in Marketplace: plug-and-play applications running entirely in the consumer's workspace, from financial forecasting to manufacturing analytics. No data leaves your boundary.
MCP servers in Marketplace: turn Marketplace assets (tables, notebooks, volumes, Apps) into agentic tools that Genie, Agent Bricks, or any external LLM can call as governed UC objects.
Key Highlights
- AI-First Ecosystem: A curated library of Genie Spaces, Apps, and MCP tools, natively integrated with your governed data.
- Privacy-Safe by Default: Genie Sharing gives external recipients an agentic experience without exposing raw rows or proprietary logic; Apps run in-place to eliminate exfiltration risk.
- Speed to Value: Move from discovery to production in days, for data, agents, and applications alike.
Session Speakers
Akram Chetibi
/Director, Product Management
Databricks
Tia Chang
/Product Manager
Databricks