An “Economic Brain” for Russian Industry
The II-Kantorovich (AI-Kantorovich) integrated planning system, developed by the Kristall rosta (Crystal of Growth) Foundation together with HiveMind AI, has completed pilot testing and been deployed at Russian companies. Project results have demonstrated the effectiveness of the national platform in tackling complex production and logistics planning challenges.
Today, artificial intelligence is most often associated with generative models and large language models. In modern manufacturing, however, what often matters most is the ability to find optimal solutions amid numerous constraints and interdependencies. II-Kantorovich was created to tackle exactly these challenges.
Nobel-Winning Ideas Go Digital
The Kristall rosta Foundation initiated the project and developed its underlying concept. A Russian investment institution and shareholder value partner, the foundation acts as a driver of digital transformation in the real economy. It directly finances Russian high-tech technologies and works closely with government agencies, including the Russian Finance Ministry, as well as leaders in manufacturing and the IT sector.
HiveMind AI provided the technological and mathematical foundation, drawing on its experience in building AI-based optimization models. The system extends the ideas of Nobel laureate Leonid Kantorovich, which underpin modern advanced planning and scheduling (APS) systems and sophisticated planning modules, by applying current AI and machine-learning technologies.
Sovereign Planning Code
II-Kantorovich is a Russian alternative to foreign systems such as Aspen PIMS and DPO, Honeywell RPM, SAP APO and SAP IBP, as well as other platforms for volume, scheduling and integrated production and logistics planning. At its core is mixed-integer linear programming, or MILP, the mathematical approach used by leading APS systems worldwide. Unlike most of those systems, which address localized problems at an individual plant, production site or within a logistics function, II-Kantorovich builds a unified digital model that simultaneously accounts for production capacity, raw-material constraints, logistics, warehouses, economics, contracts and delivery schedules. The system can operate at a single plant or across multiple sites, synchronizing production, logistics and economics within a single optimization cycle.
To quickly reconfigure supply chains, manage infrastructure constraints and minimize costs, the system uses generative AI and LLMs to improve the quality of unstructured data. Machine-learning algorithms trained on previous scenarios speed up calculations. Hierarchical modeling, meanwhile, allows the system to scale from a single plant to an entire industry. Mathematical optimization is combined with predictive analytics and industry-specific factors. In practice, that makes it possible to address strategic questions by identifying bottlenecks and assessing infrastructure investments – for example, determining whether building a new rail terminal or upgrading existing tracks would be more effective. The system can therefore model how infrastructure decisions would affect both an individual business and the broader industry.
Math That Saves Billions
Pilot projects have been completed in oil refining, consumer-goods manufacturing, road construction and logistics. In some projects, companies cut response times for changing conditions by as much as 50% and reduced the labor required for planning processes by up to 75%, while substantially improving the feasibility of their plans.
One application of II-Kantorovich involved optimizing deliveries for one of Russia’s three largest oil corporations. The system connected planning across three refineries, oil depots and sales outlets while accounting for five modes of transportation, more than 300 logistics links and 60 product types. Calculations that previously took two to three days and were performed manually now take two to four hours, while replanning is nearly instantaneous. The result is less railcar downtime, lower logistics costs and reliable execution of shipment plans. At another refinery processing more than 7 million metric tons of crude oil annually, the system optimized planning around Russia’s refundable excise tax mechanism, increasing returns from that mechanism by more than 15%.
For DSK Avtoban JSC, one of Russia’s largest road-construction groups, the system developed an optimal plan for allocating materials between quarries and construction sites, cutting transportation costs by 5% and reducing calculation time from several days to seconds. At a manufacturing facility operated by Faberlic, one of the country’s largest cosmetics companies, II-Kantorovich calculated an annual plan covering 110 product types and balanced equipment utilization. For Geltek Group, a leader in the medical and cosmetics industries, the platform creates a step-by-step production schedule for workshops to minimize the time spent reconfiguring production lines. Calculating this complex schedule takes just two to three minutes. That allows the company to give customers reliable order completion dates while uncovering hidden opportunities to reduce operating costs.
From the Factory Floor to the Arctic Ice
The Kristall rosta Foundation and HiveMind AI see II-Kantorovich as the foundation for a sovereign standard in integrated planning. Their near-term plans include moving to dynamic AI-driven planning and scaling the system into new sectors, including the gas and mining industries.
In parallel, the platform is moving into macro-infrastructure management. Together with VIS Group, the foundation is assembling a portfolio of infrastructure projects worth up to 1 trillion rubles (about $12.3 billion). Under a decision by Russia’s Maritime Board, II-Kantorovich will set the management standard for highly complex freight flows as part of the comprehensive project to develop the Trans-Arctic Transport Corridor.
Over time, the system is therefore expected to evolve from optimizing individual companies into an integrated environment for managing entire industries and global transportation arteries, giving Russian businesses and the government a reliable foundation for proactive economic growth.
