At HIVELAB, we are building a comprehensive intelligent food supply model — a system that unites every stage of the value chain, from large-scale distribution to the consumer's refrigerator. Every component of this system is developed and tested in our field laboratory — the MinaMart supermarket.
To restructure the food supply process by building a holistic, data-driven, and self-optimizing ecosystem.
MinaMart Supermarket
We help people get quality products on time and at a fair price. Our technologies make shopping more convenient and choices more informed.
We create tools for precise demand analysis, assortment optimization, and cost reduction. This helps businesses grow and offer better service to customers.
Our research and solutions simplify the mechanism of delivering food products to store shelves and customers' refrigerators.
Our solutions support the development of a sustainable food system. We help forecast market needs, ensure food security, and improve industry efficiency.
We begin by building a high-resolution retail map, continuously updated by autonomous AI agents working with supplier databases, e-commerce APIs, and open market data.
01
We collect, normalize, and cross-reference information about products, suppliers, assortment, prices, and availability, identifying gaps, redundancies, and anomalies in demand and distribution.
02
We perform market clustering: analyzing consumer behavior and market trends to forecast demand and optimize assortment.
03
We obtain a set of derived market characteristics and generate intelligent recommendations to improve supply chain efficiency and reduce waste.
An electronic statistics and analytics system for food products and catering.
We use both open-source data and business data — supply and demand, consumer preferences, and more
automatic price adjustment based on demand, shelf life, competitors, and time of day.
AI predicts sales volumes for each SKU considering seasonality, holidays, weather, and local events.
recommendations on which products to remove or add based on sales data and purchasing habits.
The Golden Catalog is the central semantic core of the retail ecosystem — a unified and constantly evolving representation of all food products and consumer goods, their attributes, relationships, and market behavior.
In Hive Lab's architecture, the Golden Catalog functions as a formal theoryas well as the working foundation on which intelligent retail systems are built.
This representation transforms the catalog from a static database into a living semantic model — extensible, self-consistent, and compatible with other retail systems
E - product entities (items, attributes, brands, units of measurement);
F - operations (aggregation, synonym matching, category inheritance, temporal price functions);
R - relations (equivalence, substitution, price-time dependency)
tracking product movement and signaling approaching expiry dates to enable timely markdown or relocation.
cameras and sensors analyze the color, shape, and moisture of fruits, meat, or fish, determining when they need replacement.
Learn product composition, whether it's suitable for children or your dietary approach, and find the average price in the country
The store-level catalog is a projection of the Golden Catalog onto a specific operational and geographical context. It maintains the theoretical integrity of the parent ontology while adapting to practical constraints:
Golden Catalog defines both the assortment logic and pricing policy, forming the structural foundation for every commercial decision.
Thus, each store becomes a localized instance of a global information system, semantically synchronized with the universal model and adapted to its own market conditions.
We automate the receipt of goods and invoices from suppliers, instantly aligning every incoming document with our Golden Catalog to maintain semantic consistency and track prices across the entire chain.
By synchronizing supplier data within a unified ontology, we lay the foundation for intelligent distribution systemscapable of autonomous coordination, adaptive supplier selection, and real-time procurement decisions.
predicting when and how many products to order to minimize surplus and shortages.
the system detects empty shelf spaces via cameras and sends a signal to staff/robot.
The system analyzes traffic, weather, and courier availability → builds optimal routes, and the customer receives an accurate arrival time
When the infrastructure is ready, we will integrate an AI-powered voice assistant — a natural language interface between human life and the intelligent retail network.
The assistant helps customers intuitively and efficiently replenish supplies, connecting the consumer's fridge directly to the live supply logic.
creates a list by dishes and shows where they are located in the store.
You get exactly what you need — products, promotions
The food retail program represents a full-cycle reorganization of the food supply chain — a continuous adaptive pipeline where theory, data, and human behavior merge into a single intelligent process.
Through MinaMart we test and refine this model in real-world conditions, shaping not disruption, but ecological evolution of existing systems toward transparency, efficiency, and balance. HiveLab - designing the algebra of everyday commerce.
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Golden Catalog also serves as the semantic core for continuous expansion of the food analysis system. Its structure provides a natural foundation for knowledge extension and interaction throughout the entire product lifecycle.
Thanks to this semantic expansion, Golden Catalog becomes not just a data model, but a generative intellectual layer: a unified algebraic continuum linking the processes of preparation, distribution, and perception of food products.