WORK → SNACK FUND HK

Snack Fund HK: revolutionizing nutritional analytics with AI-powered scanning

We built a proof-of-concept platform for Snack Fund to automate nutritional data extraction for the snack industry. By leveraging computer vision and advanced AI, we enabled B2B clients to instantly digitize nutrition labels via camera and barcode scanning, creating a robust, searchable database of food analytics that turns manual data entry into actionable business intelligence.

CLIENT PROJECTAIFOOD TECHB2B ANALYTICS

ROLE

Product strategy, AI/ML engineering, computer vision, full-stack development

TIMELINE

1 month

STACK

React Native · Python (computer vision) · TensorFlow · PostgreSQL

MARKET

Food tech & B2B analytics

THE CHALLENGE

Manual bottlenecks in nutritional data management

For the snack industry, gathering granular nutritional data is a heavy manual process. Companies rely on slow, manual entry to populate their databases, leading to inaccuracies and lost time. Snack Fund needed a way to accelerate this — a B2B-ready proof of concept that could demonstrate how AI could automate data capture and provide high-value analytical insight for their clients.

THE SOLUTION

An AI-driven intelligent scanning engine

We developed a platform that serves as an intelligent intake system for nutritional data. We combined real-time computer vision and barcode scanning with a backend database engine, so users simply scan a snack package to extract complex label data — instantly digitizing the content and making it searchable for B2B analysis.

WHAT WE BUILT

Automated intelligence for snack data

AI nutrition scanner

A sophisticated computer vision pipeline that processes camera feeds and barcodes to accurately identify products and extract nutrition label data in real time.

Intelligent snack database

A centralized, structured repository of nutritional information designed for scalability and B2B data querying.

Automated data extraction

Machine learning models that minimize human intervention by automatically parsing text-heavy nutrition labels into structured data formats.

B2B analytics portal

An insights dashboard where corporate clients query, compare and analyze snack data to support product development and market research.

THE RESULT

From manual entry to automated insights

Instant

digitization

Manual label entry eliminated by AI-powered scanning

High

extraction precision

An automated ML pipeline ensuring reliable nutritional data capture

PoC

production-ready

Core B2B value proven through a functional, high-performance prototype

Searchable

snack database

Raw label data turned into usable insight for B2B decision-making

Snack Fund needed a way to prove that AI could solve the industry's data entry bottleneck. Neologism delivered a PoC that not only worked but showed exactly how we can scale insights for our B2B partners.

David Wong

FOUNDER, SNACK FUND HK

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