Join us for the final session of Industry Month as you learn to transform commercial real estate portfolio management with Databricks AI! In this BrickTalks session, see how Databricks AI turns complex lease PDFs into structured, decision-ready data in seconds. BrickTalks are live, expert-led sessions where Databricks product leaders share real-world architectures, demos, and practical use cases for building data and AI solutions.

Thursday, April 19

• 9:00 AM PT

• 12:00 PM ET

• 4:00 PM London

• 9:30 PM Bengaluru

Details

Asset management analysts are constantly asked high-stakes questions on tight deadlines: “What’s our rollover exposure by sub-market?” “Where are we over-concentrated by tenant credit?” “How do these leases change fund-level cash flow?” Meanwhile, data and reporting teams are stuck stitching together inconsistent lease data from PDFs, side letters, and amendments into something usable. Manual extraction doesn’t scale, and every new question means another ad-hoc data wrangle.

In this BrickTalk, we’ll show how an AI-powered Lease Extraction Platform on Databricks turns those leases into a governed, analyst-ready dataset that both teams can trust. You’ll see how to:

• Automate lease abstraction into a proper data model – extract landlord/tenant info, key financial terms, options, clauses, and risk factors into a consistent schema that data teams can own and extend.

• Standardize portfolio risk and exposure views – enable analysts to calculate tenant credit and concentration risk, rollover exposure, and scenario views without rebuilding logic every quarter.

• Operationalize a single lease data layer – give BI/reporting teams a governed source of truth that feeds dashboards for PMs, ICs, and leadership

We’ll walk through an end-to-end reference architecture using Databricks Information Extraction Agents, Model Serving, Databricks Apps, Unity Catalog, and AI/BI dashboards. You’ll leave with a practical blueprint for:

• Cutting lease-related analysis cycles from days to hours

• Reducing brittle, one-off pipelines in favor of a reusable lease data model

• Empowering analysts and data teams to scale portfolio insights as your AUM and asset count grow