Real-Time Retail Intelligence: Building E-Commerce Recommendations with Lakebase and AI Search on Databricks
Summary
A complete reference architecture is now available for building a real-time, multi-stage e-commerce recommendation engine on Databricks using AI Search for candidate retrieval, Lakebase for online feature serving, and Model Serving for low-latency inference. By unifying batch precomputation and real-time scoring on a single governed platform, this design replaces fragmented ML stacks to eliminate glue code and deliver end-to-end lineage from raw clickstream to production predictions.
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