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helping enterprises become AI-native organizations

From Databricks’ Data + AI Summit to Day-to-Day: How the Latest Announcements Impact Real Deployments – Live Webinar

We just got back from the Data + AI Summit in San Francisco. More than 30,000 people showed up, making it the biggest edition yet.

JUL

8

Wednesday

event time

CET


About the Webinar

We just got back from the Data + AI Summit in San Francisco. More than 30,000 people showed up, making it the biggest edition yet. Every vendor on the show floor was shouting “AI” at full volume, but underneath the noise, Databricks was busy doing something different: laying the pipes for an entire new category to run on. Think less fireworks, more foundation pouring.

Our two main takeaways from the week organize around four ideas: Context, Control, Choice, and Cost. Together they sketch out the playbook Databricks is writing for what comes after the chatbot phase of AI, the agentic era, where software doesn’t just answer questions but actually goes and does things.

What You Will Learn

By the end of this 30-minute session, you’ll understand:

  • How Unity AI Gateway works less like a simple gatekeeper and more like air traffic control for agents, both inside and outside Databricks, directing traffic instead of just checking IDs at the door.
  • How Genie Ontology, Genie One, and Omnigent tackle the problem of giving AI systems the right context and options, a bit like handing someone a well-organized map instead of a pile of loose directions. Omnigent in particular is an open-source harness built for what the team is calling “tokenmaxxing,” squeezing the most useful output out of every token spent.
  • How OpenSharing rewrites the rules for Delta Sharing, moving past plain tables to let organizations share entire AI assets. It also opens the door to Apache Iceberg clients and on-prem storage, more like dismantling a fence between yards than just adding a new gate.
  • How Genie App Builder and Genie ZeroOps push app development and operations out to the edges of the organization instead of keeping them centralized, similar to letting branch offices make their own calls instead of routing everything through headquarters.
  • How new Lakebase features bring managed support for agentic memory, and how Lakehouse RT delivers true millisecond, real-time latency, the difference between a system that remembers what just happened and one that’s still catching up.


Webinar Agenda

  • Welcome and introductions
  • Summit recap walked through the four pillars: Context, Control, Choice, Cost
  • Genie Ontology, OpenSharing, and the shift toward a more open data ecosystem
  • Genie Demo
  • What this actually means for your roadmap
  • Live Q&A


Who Should Attend

  • Data and AI leaders who want the Summit distilled into what’s actually usable, skipping the keynote theatrics.
  • Data engineers and architects sizing up Unity AI Gateway, Lakebase, or Lakehouse RT for projects already on the table.
  • Platform teams thinking through how to govern a growing number of AI agents without losing track of who’s doing what.
  • Anyone building on Databricks who wants a second opinion on which announcements matter and which are just noise.


Join us for this 30-minute live session on July 8 at 2 PM CEST and find out more about the latest developments from the 2026 Databricks Data + AI Summit.

Reserve your free seat now.

/speakers

Alexandru Puiu

CTO & Data Architect

Alexandru Puiu is the CTO of mindit.io, with over 8 years of experience in building tech communities, driving cloud migrations, and ensuring security best practices. He specializes in Business Intelligence, managing large-scale ETL processes and Azure migrations, alongside expertise in software development with Java, Python, and cloud technologies.

Zhanna Pchela

Delivery Solution Architect at Databricks

Zhanna is a Delivery Solutions Architect at Databricks with 15+ years of experience across different areas of data, including data architecture, governance, analytics, and cloud platforms. She has built modern data platforms, designed scalable architectures, and led teams through complex data transformation initiatives.

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