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Reksoft is a machine learning company, which services for the implementation of this kind of software, as well as support for the existing system and consulting. Having experience and knowledge in the development of computer programs since 1991, we have been offering IT solutions to help firms solve business problems using accurate forecasts, root cause studies, intelligent analysis of big data, etc.

What means ML

Machine learning (ML) is a type of artificial intelligence (AI) that allows programs to study patterns based on findings and subsequently better them thanks to the experience gained. It is at the heart of what makes a system smart. The ability to decide how to act by analyzing data distinguishes this approach from other forms of automation.

There are two types of machine learning:

  • Training with a teacher. When a ML model is learned on the available input and corresponding output data. The program trains to compare information. And then it begins to predict the output for new input data.
  • Training without a teacher. When the model is taught only on input data. And it learns to find hidden relationships or group them.

ML includes a set of methods that can predict outcome, and are aimed at gradually improving the performance of a given goal. Machine learning uses different of mathematical, statistical, and computational techniques for developing algorithms that can solve problems by looking for patterns in a variety of inputs. The decision is calculated not according to a clear formula, but according to the established dependence of the results on a specific set of features and their values.


Machine learning is based on the latest search engines, real-time data science, digital security and software development for artificial intelligence. Such systems investigate how users access corporate information and classify their behavior. ML helps to maintain a security software that detects and prevents violations in real time. The Reksoft team will aid you use this to improve your business. We’ll analyze the state of the software and advise technical solutions to problems, build individual machine learning models and integrate them into the program’s ecosystem.

Therefore, ML is used in various applied areas for diagnostics, forecasting, recognition, decision-making.

Our experts create and train a machine learning product that can make accurate predictions, and then evaluate the model’s performance when working with new data. Such ML may be used for:

  • Supply management. It includes demand forecasting, planning and managing inventory, identifying quality issues in in-line production, controlling supplier relationships.
  • Rising of production efficiency. It means automatic recognition of manufacturing defects, prediction and optimization of energy consumption, root cause analysis of manufacturing loss.
  • Prevention purposes. It implies predicting the remaining useful life of devices and mechanisms, reports on abnormal behavior and analysis of causes and providing recommendations to be taken to avoid possible failures.
  • Client analytics. It includes analysis and forecasting of customer behavior, recommendations for products and services of artificial intelligence.
  • Natural language processing. It means sentiment analysis, security authentication, chatbots, speech-to-text and spam filtering.
  • Computer vision. It includes analysis of medical images. Biometric verification. Tracking customers in retail stores. Recognition and classification of objects in road traffic. Autonomous vehicles.

We adhere to an iterative process and help apply machine learning techniques to solve business problems. Data engineers collect, transform, and analyze information, using it to achieve ultimate goals.


We will help create data processing systems based on user image recognition and machine learning, which can profit enterprises reducing maintenance and equipment costs. And it’ll bring business long-term financial benefits.

The use of machine learning solutions provides significant advantages:

  • Facilitates and increases the productivity of the company’s personnel by automating routine tasks by computer vision and natural language processing.
  • Improves the quality of customer service thanks to neural networks development, chatbots based on artificial intelligence and virtual assistants that simplify communication in real time.
  • Accelerates the sales process through accurate analysis of opportunities and better prioritization of potential clients.
  • Reduces equipment technical support costs through predictive monitoring and prophylactic maintenance.

Mechanizes of ML increase production efficiency by forecasting demand and volumes, optimizing work processes and predictive modeling of goods quality.


We use best practices and designs to provide the foundation for fast, structured technology solutions. Considering the specifics and needs of your business, Reksoft’s machine learning services include:

Analysis. This means identifying the goals that the firm wants to achieve using machine learning and studying the existing environment. Experts develop a strategy and a roadmap for ML, select the best technologies.

Data preparation. This includes exploratory analysis of existing sources of information, collection, cleaning and structuring. Experts define the criteria for a machine learning layout.

Web development and implementation of ML models. This includes exploring, refining, testing and evaluating of it. Experts will fine-tune the parameters to acceptable results and deploy the ML apps.

Making report. This includes delivering machine learning results in a consistent format. If necessary, experts integrate ML into the user self-service application.

Support and maintenance of machine learning apps. This implies continuous monitoring, tuning algorithms for greater accuracy, and adding new data for deeper understanding.

Reksoft’s developers can create machine learning models as a needed to address emerging business and information analytics issues.

Our outsourcing specialists will help you design software that allows you to implement continuously repeatable cycles of training, testing, deployment, monitoring and operation of ML products. This is especially important for digital transformation large-scale work.