I built a small Data + AI project to help grocery stores reduce stockouts and food waste
I recently built a small project called Grocery Data Intelligence as part of the DAIS 2026 Community Virtual Contest.
The idea came from a simple real-world problem. Grocery stores deal with two common issues every day. Some fast-moving products go out of stock when customers need them, and some fresh products expire before they are sold. One creates missed sales, and the other creates food waste.
I wanted to see how a simple Data + AI solution can help store teams move from data to decisions and then to actions.
I used Databricks Free Edition to build a lakehouse flow with Bronze, Silver, and Gold layers. The data includes stores, products, inventory, and 5000 demo sales records. The Gold layer calculates things like average daily sales, days of supply, stockout risk, waste risk, and recommended actions.
The app also has an Ask Data + AI feature where a store user can ask questions like what should I reorder today or which products may go to waste. The app maps those questions to trusted Databricks-backed views and returns simple answers, charts, supporting data, and recommended actions like reorder, monitor, promote, discount, or donate.
I also added an inventory story page to explain the situation in simple business language, because I feel analytics becomes more useful when people can understand what action to take next.
This is still a demo project, but it helped me learn how data engineering, analytics, AI-style experiences, and storytelling can work together in a practical way.
I would love to hear feedback from data engineers, analytics folks, and anyone who has worked with retail or inventory data.
App: https://grocerydataintelligence.com/
Demo video: https://youtu.be/rU1ceOf51_A
Databricks Community post: https://community.databricks.com/t5/community-articles/grocery-data-intelligence-smart-grocery-planning-with-data-ai/m-p/157102#M1182