The product is designed to build information models representing technological processes and equipment as a set of objects and relationships between them. It helps to significantly simplify data management processes, ensures work with large volumes of information, accelerates decision-making processes and improves communication between departments.
To work with the product, an information model of the subject area is created. This model is built on the principle of "from simple to complex" based on the object-oriented approach.

1. First, a catalog of objects is created. They represent the components of the process (for example, pumps of different designs and purposes, valves, etc.).
2. Then, information models-prototypes of technological processes and equipment are created from such objects.
3. After determining the values of the properties of elementary objects, final information models of technological processes and equipment are formed from these prototypes, which is one of the results of the product's operation.

The properties of information model objects are managed using the principles of an object-oriented approach, i.e. using inheritance, nesting, visibility areas, etc. The types of object properties can be both simple (number, text, etc.) and complex (object matrices, dependent properties). The values of object properties can be changed both manually and via API from other information systems. The product has a powerful report designer, which simplifies the process of obtaining information from a hierarchical data model in the form of standard reports that are required by departments and information systems of the enterprise.
Thus, the product PL: information model allows creating information models of technological processes and equipment for virtually any enterprise and implementing integration with its existing information systems.

PL: monitoring is a simple and convenient tool for obtaining operational data and a clear idea of users’ equipment performance. It is an ideal solution for analyzing industrial enterprise data, process lines, operating modes, and calculating KPIs.

The product allows user to analyze KPIs of several geographically distributed enterprises in real time on one diagram, as well as analyze KPIs within the perimeter of one enterprise in offline mode.

PL: monitoring contains a convenient editor for mnemonic diagrams, reports, graphs, and diagrams (block diagrams). Corresponding drivers have been developed for interaction with several standard storages of historical industrial data. It is also possible to develop a driver for collecting data from specific data sources.

PL: diagnostics is a software product for diagnosing processes and equipment and alerting about problems. This product helps to increase the efficiency of work, thus reducing costs and increasing productivity.

The product contains powerful tools for diagnosing various parameters of technological processes and equipment. It allows collecting data from various sources, including OPC servers, enterprise information systems, and open sources. The data is displayed in real time using graphs, charts, dashboards, etc.

PL: diagnostics helps to automatically detect changes in various parameters, identify limit violations, make forecasts, link various factors, provide access to advanced statistical models, and set up notification rules for detected changes.

PL: analytics helps analyze the performance indicators of technological processes, as well as disseminate best practices between different enterprises and production sites. This helps reduce risks, improve quality and increase efficiency.

The product allows users to evaluate the flow of technological processes in real time and/or based on historical data. It allows users to create mathematical models by means of various methods of multi-variable analysis (MVA), using historical data of the enterprise, thus improving the operation of technological processes. This is a unique tool to analyze the operation of technological processes on purpose to improve production efficiency. Such analysis helps to identify bottlenecks in technological processes, improve controllability and disseminate various strategies.