Session
One Stack for Retail AI: From Transactional Planning to Agentic Intelligence on Databricks
Overview
| Experience | In Person |
|---|---|
| Track | Artificial Intelligence & Agents |
| Industry | Retail & Consumer Goods |
| Technologies | AI/BI, Databricks SQL, Lakebase |
| Skill Level | Advanced |
Retail AI platforms are no longer just analytics or ML systems—they must power real-time planning, massive-scale AI, and intelligent decisioning on a single foundation. In this session, we share how our Retail AI SaaS product is built entirely on Databricks’ unified platform.What We Do Uniquely on DatabricksWe run classic AI (forecasting, optimization) and GenAI + Agentic workflows together in a single Databricks stack, eliminating fragmentation between ML pipelines, planning logic, and intelligent decision automation.Our hyperlocal forecasting USP (unique model per SKU–Store via ensemble selection) is possible only because Databricks enables massive distributed ML at low cost, scaling to millions of combinations without infrastructure sprawl.Hierarchical forecasting across store > city > region > national levels, combined with genetic optimization for inventory and replenishment, runs at production scale using Spark’s distributed compute and optimized execution engine.
Session Speakers
Santhosh Ramanuja
/VP Partnership
Algonomy
Abhishek Sonkusare
/Head of Engineering
Algonomy