Russian Post Opens a New Phase of AI in Postal Logistics
Russian Post has taken a major step toward digital maturity by deploying an intelligent logistics modeling system based on the Teraplan platform.
Russian Post has launched a system that reshapes how one of the country’s largest logistics networks is managed. The Teraplan platform automates core processes: it consolidates data on shipment flows between sorting hubs, builds optimal routes across multiple transport modes, models network change scenarios, and performs complex logistics calculations under heavy load – up to 30 million operations per day.
For customers, the system is expected to deliver more predictable delivery times, reduce unnecessary routing through intermediate hubs, and improve service quality, particularly in remote regions. For Russian Post, it lowers operating costs and strengthens control over a vast network. For the Russian IT sector, the project stands out as a large-scale application of applied AI and mathematical optimization in critical infrastructure.
From Deployment to a Solution Ecosystem
The rollout of Teraplan marks not an endpoint but a transition from testing to full-scale industrial use. The next phase focuses on deeper integration and expanded functionality – including alignment with the Unified Logistics Platform, integration with multimodal transport systems, and the introduction of real-time predictive management of disruptions.
The project aligns with Russian Post’s broader digital transformation strategy and import substitution agenda. In practice, it is part of a wider overhaul of the company’s IT landscape, where domestic solutions progressively replace foreign systems and come together in a unified technology ecosystem.
Toward Intelligent Logistics
The deployment reflects several years of work in digital transformation and AI adoption in logistics. The starting point came in 2024, when the company began testing AI for route modeling. That same year, it announced a large-scale program for 2024–2026 aimed at automating routine operations and optimizing routing.
In parallel, other digital transformation initiatives advanced in 2024–2025. The Unified Logistics Platform was developed, sorting systems were upgraded, and import substitution projects were rolled out. A key milestone came in 2025, when IT holding T1 and the Teraplan developer announced a strategic partnership. Their goal is to bring optimization solutions to market across multiple industries.
AI as a Tool for Managing the Real Economy
The deployment of Teraplan highlights several broader trends. First, the Russian applied AI market is reaching a new level of maturity. The focus is shifting away from demonstration tools such as chatbots toward optimization systems embedded in physical infrastructure that directly manage critical economic processes.
AI is becoming a practical operational tool for managing transport flows, routes, delivery times, and costs. At the same time, a stable collaboration model is taking shape: a large infrastructure operator working with a domestic developer and an integrator. This model is well positioned to support new projects across multiple sectors.
Outlook
Demand for Russian-developed modeling and optimization platforms is expected to grow, not only in logistics but also in manufacturing, retail, and transport. Partnerships between large customers, domestic developers, and integrators are likely to strengthen. Integration of AI systems with broader digital infrastructure – from sorting systems to predictive analytics and disruption management – is also expected to continue.
If Russian Post demonstrates measurable results, such as reduced planning time, lower costs, and improved delivery performance, the project could become one of the clearest examples of successful applied AI deployment in the Russian economy.
