# Automate replenishment with MMF, Databricks Genie, and Amazon Quick

DevFeed: [Automate replenishment with MMF, Databricks Genie, and Amazon Quick](<https://devfeed.tech/articles/automate-replenishment-with-mmf-databricks-genie-and-amazon-quick-21547.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/machine-learning/automate-replenishment-with-mmf-databricks-genie-and-amazon-quick/>)

Author: Venkatavaradhan Viswanathan

Published: 2026-09-14T15:42:06Z

Content type: article

Language: en

Sources: [Artificial Intelligence](<https://devfeed.tech/sources/artificial-intelligence.md>)

Topics: [databricks](<https://devfeed.tech/topics/databricks.md>), [Amazon S3 Tables](<https://devfeed.tech/topics/amazon-s3-tables.md>), [Amazon S3](<https://devfeed.tech/topics/amazon-s3.md>), [Automation](<https://devfeed.tech/topics/automation.md>), [foundation-models](<https://devfeed.tech/topics/foundation-models.md>), [API](<https://devfeed.tech/topics/api.md>)

Tags: [advanced-300](<https://devfeed.tech/tags/advanced-300.md>), [amazon-quick-suite](<https://devfeed.tech/tags/amazon-quick-suite.md>), [amazon-s3](<https://devfeed.tech/tags/amazon-s3.md>), [amazon-s3-tables](<https://devfeed.tech/tags/amazon-s3-tables.md>), [api](<https://devfeed.tech/tags/api.md>), [automation](<https://devfeed.tech/tags/automation.md>), [databricks](<https://devfeed.tech/tags/databricks.md>), [foundation-models](<https://devfeed.tech/tags/foundation-models.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [retail](<https://devfeed.tech/tags/retail.md>), [technical-how-to](<https://devfeed.tech/tags/technical-how-to.md>)

## AI overview

This technical walkthrough presents an unattended replenishment workflow for retail. Databricks Many Model Forecasting uses Chronos-2 to predict seven-day demand for each SKU, Databricks Genie detects demand surges, and Amazon Quick reconciles those surges with supplier availability in Amazon S3 Tables. The workflow places routine purchase orders through a Supplier Order API and escalates cases without a suitable single supplier for human review.

## Source excerpt

Foundation models made catalog-wide demand forecasting easy; the hard part is now acting on the forecast. This post builds a closed detect-decide-act loop on Databricks and Amazon Quick that reconciles demand surges against live supplier availability and places replenishment orders unattended, escalating to a human only when no supplier can cover a surge.