Predictive Analytics Platform Highlights Risks and Business Sore Spots Before They Escalate
Russia has introduced a new tool for advanced forecasting. The Institute of Artificial Intelligence and Digital Sciences at the Faculty of Computer Science of HSE University (Moscow) has unveiled Predict Core, a unified predictive analytics engine designed to build forecasting models.
According to its developers, the platform changes how organizations work with data. Instead of relying on retrospective reporting, companies can develop a habit of using forecasts that also explain how specific projections and figures were generated.
The Need for Better Analytics Has Been Building
Today, many companies still make decisions only after events have already occurred, effectively reacting to outcomes rather than anticipating them. Another common problem is reliance on past management experience even when underlying conditions have changed. In a market characterized by rapid shifts and persistent uncertainty, those approaches are increasingly inadequate. Analytics itself presents additional challenges. Different analysts often calculate metrics in different ways, leading to conflicting numbers. Another issue is that results are produced without explaining how they were obtained, leaving much of the organization unable to understand where conclusions came from. A third problem is that reports describe only what has already happened. A fourth is that analytical reporting is often produced irregularly.
Predict Core, developed by HSE University experts, is designed to address those issues. It can be deployed either as a cloud service or installed directly on a customer’s infrastructure in an on-premises configuration. The platform connects to a client’s internal data as well as relevant external sources and learns from both operational data and information about the surrounding environment. According to its creators, the system can identify anomalies at an early stage. For example, it can detect disruptions in sales performance or shifts in product demand. That gives senior management visibility into emerging issues before they develop into significant losses. Every forecast is reproducible, with each run preserving a snapshot of the data and parameters used.
Different Roles, Different Views
Predict Core is built around a unified analytics engine that connects to property management systems (PMS), enterprise resource planning platforms (ERP), customer relationship management software (CRM), point-of-sale systems, web analytics tools, and external data sources covering weather, events, holidays, and macroeconomic indicators. Organizations can create user profiles and assign functionality and access rights based on each employee’s role and responsibilities. An analyst, for example, configures forecasting runs by selecting data sources, target variables, forecast horizons, and reporting frequency. A manager sees workload metrics, anomalies, and forecast accuracy indicators. Executives receive consolidated information at the level of detail they require. The platform is intended for organizations that maintain historical operational records through databases or accounting systems. Predict Core is already being used by professionals in the hospitality sector.
Importantly, the platform’s components are Russian-developed, with no reliance on foreign cloud services or software licenses.
Better Service Through Better Forecasting
The development of Predict Core by Russian professionals reflects a broader shift from traditional business intelligence reporting - automatically updated dashboards and reports - toward systems that not only describe past performance but also help forecast future developments.
Demand for such solutions is growing. In the second quarter of 2025, the share of Russian companies using AI for business tasks rose to 43%. Over time, broader adoption of these systems could improve product and service availability for consumers, streamline logistics, and enhance service quality across hospitality, retail, transportation, and other industries.
The development of platforms like Predict Core is also significant for the country's long-term technological development. Russian predictive analytics platforms reduce business dependence on foreign digital solutions, support technological sovereignty, and help build expertise in the industrial application of AI.
Predict Core’s export prospects will depend on industry-specific expertise, model quality, forecast explainability, and the platform’s ability to integrate with international enterprise systems.
