Enoteca World AI Powered Wine & Spirits Label Scanner Mobile App
95%
Label Recognition Accuracy
2x
Faster Bottle Identification vs Manual Search
About the Client and Project
The client is an Italy-based entrepreneur with a deep passion for wine, spirits, and simplifying the way people discover what they’re drinking.
With firsthand experience of how confusing the wine and spirits market can be hundreds of labels, multiple languages, and zero context at the point of purchase the client approached TryDigital with a focused vision: build a mobile app that identifies any bottle instantly, from any angle, for anyone.The result is Enoteca World a live, AI-powered Flutter app available on Google Play, serving wine and spirits enthusiasts across Europe and beyond.
Industry
Food & Beverage Tech
Project Duration
3 months
Team Size
8
Client Location
Italy
Engagement Model
Fixed Budget
Our Process
1.
Conceptualization
Market understanding Localization
2.
Design
User flow Designing
3.
Development
Azure server
4.
Deployment
New York City
Challenges
1. AI Recognition & Accuracy
- Building an AI model capable of recognizing wine and spirits labels from both front and back of the bottle with high accuracy under real-world lighting conditions.
- Training the recognition engine to handle labels across multiple languages, regions, and bottle formats without returning incorrect or incomplete results.
- Ensuring the AI could identify products even when the primary label was damaged, partially hidden, or non-standard.
- Balancing recognition speed with accuracy — delivering results in under 3 seconds without sacrificing reliability.
2. User Experience
- Wine and spirits consumers expect instant, frictionless results especially in real-world settings like restaurants, wine shops, and supermarkets. The app had to work fast with zero learning curve, no tutorials required.
- The UI had to feel simple and clean while handling complex AI processes running in the background making a technically sophisticated app feel effortless to any type of user.
3. Security and Data Privacy
- Building an AI-powered app that processes camera input and communicates with external APIs meant security could not be an afterthought it had to be built in from day one.
- The app's reliance on real time image processing and third party beverage databases introduced multiple potential vulnerabilities. Every data exchange between the app and external services had to be protected against interception, misuse, and unauthorized access.
- Since Enoteca World operates across different regions and markets, the app had to handle cross-border data flows responsibly with no user data collected, no personal information stored, and all data encrypted in transit meeting the expectations of privacy conscious users in Europe and beyond.
- The decision to collect zero user data was deliberate and non-negotiable. It eliminated privacy risk entirely while building immediate trust with users a conscious tradeoff that shaped the app's architecture from the ground up.
Client Goals
After a thorough understanding of the requirements, we decided
to build a smart AI-powered mobile app that would:
- Allow users to instantly identify any wine or spirits bottle by simply pointing their phone camera at the label
- Enable accurate recognition from both front and back labels eliminating the need for a perfect or fully visible bottle
- Deliver detailed product information in real time including origin, type, producer, and beverage category
- Support a wide range of alcoholic beverages across global markets with multilingual label handling
- Provide a fast, intuitive experience with zero learning curve built for real-world use in restaurants, shops, and homes
Technology Stack
- Mobile Framework: Flutter (Dart) for cross-platform iOS and Android development from a single codebase
- AI & Recognition: Computer Vision model for real-time image-based label recognition front and back label support
- Database: MongoDB for flexible document-based storage, PostgreSQL for relational data modeling
- Data Analytics: Python with libraries like Pandas, NumPy, sci-kit-learn for predictive modeling, Apache Spark for large-scale data processing
- Cloud Hosting: Kubernetes for container orchestration, AWS (Amazon Web Services)
- Security: OAuth 2.0 for authentication and authorization, SSL/TLS for secure communication, OWASP guidelines for application security best practices
Results
The client’s adoption of the cloud application improved customer experience and drove significant operational efficiency improvements.
- The application garnered high praise from our customer’s clients, who are among the world’s foremost global brands.
- Streamlined the planning process for internal teams, slashing workload by over 35%.
- Noteworthy 5% increase in ROI for customers who adopted engine-recommended plans within just six months of system implementation.
95%
Label Recognition Accuracy
2x
Faster Bottle Identification vs Manual Search
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