CONTEXT: The Metadata and AI Summit

AI agents are quickly emerging as the next layer of enterprise technology, promising to transform how organizations interact with and act on their data. But like every layer before, their success hinges on a strong foundation: trusted, contextualized data.

In this fireside chat, João (Joe) Moura, CEO of CrewAI, will share his perspective on where enterprise AI agents stand in 2025, the most exciting developments shaping their trajectory, and the role of MCP in scaling agentic systems. Together, we’ll explore the promise and challenges of agents working with enterprise data—and why context platforms like DataHub are essential to moving from experiments to production. Attendees will walk away with a clearer view of how to harness agentic AI responsibly and effectively, built on the bedrock of context.

What happens when one of the world’s top artists turns his focus to technology and venture capital? In this fireside chat, Alex Pall—half of The Chainsmokers and founder of Mantis VC—joins Shirshanka Das to explore how AI is transforming creativity, business, and culture. 

Drawing on his unique vantage point as both a Grammy-nominated musician and active investor, Alex will share how AI is reshaping the creative process, the importance of metadata in ensuring responsible data use, and where he sees the most exciting opportunities for AI-driven startups. Attendees will walk away with a fresh perspective on the intersection of artistry, data, and innovation.

Key Takeaways:

• How AI is augmenting, not replacing, human creativity in music, media, and beyond

• Why metadata is critical for attribution, rights management, and responsible AI adoption

• Lessons from building a global creative brand that apply to launching and scaling AI startups.

• Where investors like Mantis VC see the next wave of AI-native companies emerging

Foursquare’s new Geospatial Intelligence Platform revealed a key insight: many data scientists want to use location data in their ML workflows without needing deep geospatial expertise. To meet this need, Foursquare built the FSQ Spatial H3 Hub—a governed data marketplace powered by DataHub’s enterprise metadata capabilities.

Shirshanka and Vikram will discuss how metadata enables Foursquare to make geospatial datasets accessible, secure, and enterprise-ready, while supporting modern workflows across Spark, Python, and DuckDB.

Key Takeaways:

• How metadata management unlocks governed data marketplaces

• Ways to practically combine Iceberg catalogs with Spark, Python, and DuckDB

• Why lineage, versioning, and governance are critical for enterprise ML adoption

• Lessons from launching with 20+ open datasets to power machine learning at scale 

How do you align thousands of people around a shared metadata strategy? 

In this session, Mikhael Mazu shares his journey to establish a federated metadata operating model, shifting culture from confusion to clarity. Join this talk to learn practical steps for treating metadata as a strategic asset, laying the foundation for compliance, business transformation, and AI-driven innovation.

BCBS 239 continues to challenge financial institutions to prove the quality, traceability, and governance of their data. But firms are learning that compliance isn’t just about checking boxes — it’s about building sustainable processes that balance regulatory expectations with real-world cost and complexity.

Key takeaways:

• Lineage Strategy: Choosing the right level of data lineage (domain, dataset, or element-level) and navigating the tradeoffs of cost vs. regulatory satisfaction.

• Operationalizing Compliance: Turning auditor requests into repeatable workflows by embedding lineage, controls, and integrations into day-to-day operations.

• Future Outlook: Using compliance as a foundation for efficiency, resiliency, and AI-readiness, rather than treating it as a one-off requirement.

Attendees will gain practical insights from peers who have lived through the journey — from early roadmaps to regulator conversations — and leave with a clear sense of how to scale compliance in a way that’s both credible to auditors and valuable to the business.

Where does your data really come from — and where does it go? In this session, Srikanth Devidi from Robinhood shares how they built end-to-end lineage across batch, streaming, and BI systems.

Learn how lineage unlocks faster discovery, better quality, and stronger governance,  plus actionable first steps you can take to bring visibility to your own data supply chain.

Key takeaways:

• How to map lineage for your highest-risk pipelines first (e.g., PII or revenue data)

• Put names to flows: Assign a “lineage steward” to each critical pipeline so someone is accountable when things break

• How to understand the impact of making changes to your data

• How to triage and debug the operational data issues - stale, missing, and duplicated data

• Position lineage as a tool for faster discovery and better productivity, not just a compliance checkbox, to drive internal buy-in and adoption

Breaking changes can slow analysis, frustrate stakeholders, and erode trust. In this fireside chat, Maggie Hays sits down to uncover practical approaches that teams can leverage immediately to prevent failures.

She’ll explore how to anticipate downstream impact, strengthen communication across teams, and unlock quick wins that make shipping data updates less risky, and a lot less painful.

AI agents promise to let anyone “talk to data,”  but trust and accuracy are the real tests. 

This session examines how organizations are utilizing natural-language interfaces, powered by metadata, to enable non-technical users to find, understand, and use data with full confidence.

Key takeaways:

• How to build trust in AI-generated queries

• Why metadata is the foundation for accurate answers

• Quick wins to reduce ad-hoc requests and speed up insights

• One quick win: How to enable self-service for members to get the answers they need from the data