Session
From Classic ML to Agentic Predictions
Overview
| Experience | In Person |
|---|---|
| Track | Artificial Intelligence & Agents |
| Industry | Enterprise Technology |
| Technologies | Delta Sharing, Agent Bricks |
| Skill Level | Advanced |
How DealSumm evolved from one-shot model outputs to an orchestrated system that retrieves evidence, reasons with structure, and verifies every claim - without burning compute.If you have ever built ML for contract analytics, you know the pattern: you ship a model that looks great on a benchmark, then reality shows up. One client has a different template. Another uses a jurisdiction-specific term. A third buries the key clause in an amendment scanned in 2008.At DealSumm, our goal is not just prediction - it is turning messy commercial lease documents into trustworthy, referenced data that teams can review, analyze, and act on inside a single AI-ready platform.The problem is that lease abstraction is not a single prediction problem. It is a chain of dependent mini-decisions: find the right clause, interpret it in context, map it into a client schema, and then prove you did not hallucinate.
Session Speakers
Jonathan Bauman
/CTO
DealSumm