A leader in foodtech, Foodlabs, sought to create an app providing personalized meal recommendations, leveraging users’ dietary preferences, health objectives, and medical data. The task required integrating diverse data sets into a cohesive model to drive a sophisticated recommender system—a challenge that proved too complex for several contracted developers. The founder, lacking the necessary technical expertise, was unable to progress the project independently.

Technocrati approached the problem by initially developing simplified data models and employing linear optimization to quickly demonstrate the feasibility of the recommendations within the project's constraints. Our team then advanced the project by deploying a dedicated Python-based recommender microservice and creating a comprehensive food and recipe database, optimized for personalization including dietary restrictions like allergies.
In the project's next phase, we developed a cross-platform mobile application using Dart/Flutter and built a backend that integrates with grocery chains and medical labs, creating a seamless flow of information. Recognizing the need for sustainability and growth, Technocrati recruited and onboarded an eight-member in-house development team, to whom we smoothly transitioned the development work.

The collaboration resulted in the launch of a fully functional AI-driven app in just three months. Establishing an in-house technical team has ensured ongoing business continuity and scalability. This strategic move prepares Foodlabs for future growth and adaptations in the fast-evolving foodtech industry.

This project underscores Technocrati's capability to address complex technical challenges with practical, efficient solutions. By focusing on strategic planning and the integration of specialized technology, we facilitated the swift realization of Foodlabs’ vision. This case exemplifies our commitment to delivering expertly crafted, innovative solutions that empower clients to achieve and extend their business objectives.