Technology stack
- Python
- OCR
- CNN
- RNN / LSTM
- Scikit-learn
About the project
FORM wanted to replace manual menu review with a faster, more scalable intelligence workflow for beverage brands. We developed a document-intelligence system that analyzes menus, extracts relevant text and structure, and forwards cleaner data into downstream reporting and analytics processes.
The challenge
Manual research across restaurant and bar menus was time-intensive, inconsistent, and difficult to scale. The client needed a dependable way to process visual menu content, identify useful signals, and turn scattered inputs into structured information that sales and BI teams could actually use.
Our solution
We built a machine-learning pipeline that combines OCR, segmentation, and deep-learning models to read menus, identify sections and product information, and transform image-based inputs into analyzable datasets. The system was designed to support beverage intelligence workflows where speed, accuracy, and repeatability matter more than one-off review.
Results & impact
The platform expanded usable market intelligence from menu data, reduced manual processing effort, and gave business teams faster access to structured signals for beverage placement, pricing, and sales analysis.