Session

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

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Overview

ExperienceIn Person
TrackData Sharing & Collaboration
IndustryEnterprise Technology, Retail & Consumer Goods
TechnologiesData Marketplace, Databricks Apps
Skill LevelBeginner

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

Speaker placeholderIMAGE COMING SOON

Akram Chetibi

/Director, Product Management
Databricks

Tia Chang

/Product Manager
Databricks