A selection of the AI work we have delivered for enterprises and startup teams: assistants inside retail, HR and finance operations, computer vision on production lines and in the field, demand forecasting and large-scale data platforms.
Food images and content scanned for the CarrefourSA assistant
Food and ingredient records run through ML models
Food-culture entries behind the Little Lunches models
Accuracy reached by the demand forecasting model
Figures are taken from the project descriptions published on 4alabs.io.
Programmes delivered inside large organisations — retail, manufacturing, agriculture and shared service centres. Each one went into a live process, not a pilot folder.
A digital food, health and nutrition assistant added to the CarrefourSA mobile application as an LLM-based AI model.
A mobile application that gives the sales team fast, accurate access to detailed product information extracted from PDF documentation.
Product demand forecast from historical and external data, on a daily and store-by-store basis, to improve stock planning and cut cost.
A chatbot that gives store managers instant answers about their own store instead of a manual pass through reports.
A virtual HR assistant that answers employee and manager questions and takes the repetitive load off the HR team.
A finance chatbot connected to the reporting stack, so teams reach key figures without waiting on an analyst.
A sentiment analysis system that reads customer feedback from every channel and turns it into something departments can act on.
An AI support layer for agents during and after the call: transcription, summary, sentiment and the action items that follow.
Automated visual inspection that compares the physical product against its digital design and flags the deviation.
A vision system that reads ripeness level and early disease symptoms in agricultural produce from field and greenhouse cameras.
A platform that collects, processes and serves large-scale data from across the organisation as the foundation for analytics and AI.
Products where AI is not a feature but the whole proposition — built with small teams and taken to market.
A personal shopping expert that combines AI with a human touch. It reads interests and shopping habits and prepares recommendations that fit the lifestyle of the person you are buying for.
The cloud environments of Korean makeup brands in Türkiye run on an ML and LLM-based infrastructure inside Superonline data centres. Logs and metrics from Prometheus, Datadog and New Relic are evaluated by the model and passed to IT staff as readable summaries.
A healthy food and meal planning app for children and families, and the most widely used digital food assistant of its kind in the United States. ML models trained on 780 thousand American and South American food cultures are served through an LLM chatbot experience.
An interaction bot that joins live broadcasts on social media, follows the stream, reads comments and replies in the comments. It can also work as a moderator.
Tell us the process. We come back with the closest thing we have already built and a measurable plan for yours.
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