Predictive and recommendation systems, natural language processing
Download presentationData segmentation, identification of patterns, search for anomalies
Download presentationDevelopment of predictive systems for customer churn, consumer behavior, equipment breakdowns and load forecasting, sales conversion, demand and insurance event forecasting, trifc prediction, road accidents, etc.
Personalized offers based on customer preferences, loyalty programs, recommendation systems, and decision-making assistance systems
Systems based on computer vision technologies, video analytics, recognition, classification, detection and segmentation of objects and images
Systems based on natural language processing technologies, large language models, local ChatGPT, structured information extraction
Our solutions and developments
Solutions based on artificial intelligence, machine learning, computer vision, natural language processing and data analysis technologies
The main directions of development:
The company is based on the international machine learning laboratory of ITMO University and is developing in the field of implementing machine learning technologies, computer vision, natural language processing and data analysis to solve various business problems. In recent years, many projects have been implemented for the largest Russian and foreign companies, including Norilsk Nickel, Megafon, Evraz, Sinara-Transport Machines, Gazprom Neft. This allowed us to accumulate vast experience and expertise, create a product line and become a leading company in the field of artificial intelligence technology implementation.
MoreToday, machine Learning is widely used in many sectors of the digital economy, such as industry, retail, autonomous vehicles and driver assistance systems, unmanned aerial vehicles, high-tech agriculture, healthcare, and many others.
Machine learning enables retailers to automate processes that previously had to be done manually. You can automatically receive notifications of stock out of stock or other customer requirements that are not met by creating an analytics system directly at the point of sale. Monitoring staff work, counting visitors, optimizing work schedules, analyzing the effectiveness of promotions and many other applications can be solved by machine learning technology.
Inventory analysis, automated sorting and tracking systems, scanners for reading barcodes and checking product compliance with the order. Automated pass and control systems, as well as systems for forecasting demand and supply volumes based on machine learning.
Modern high-tech production requires special approaches to quality control of manufactured products, as well as optimization of technological processes. Machine vision has made a real technological breakthrough and significantly expanded the capabilities of flaw detection in industry, and brought it to a new level. Now technologies allow monitoring quality not only after the manufacture of a product or product, but also directly during the production process. Other possibilities of using computer vision, such as, for example, the analysis of the granulometric composition of raw materials can significantly optimize the production process.
Control of staff work, traffic of visitors, control of access control, optimization of work schedule, safety and health systems and many other applications.
Monitoring the work of personnel, violations by employees of regulations and labor discipline, detection of traffic of visitors, violation of public safety and order, and many other applications.
The introduction of computer vision technologies together with global positioning systems allows for precision farming, which can significantly increase the yield and efficiency of agriculture. Monitoring agricultural fields from satellite images and unmanned aerial vehicles, determining the maturity of the crop allows you to make predictions of the amount of production.
The use of computer vision for medical imaging is used in computer diagnostics to plan personal therapy, medical care, and improve decision making. Computer vision systems help the doctor make a diagnosis because there may be small details in the image that the doctor may not notice, but such details can be recognized by the system with a high degree of accuracy. In addition, the image can be compared with thousands of other similar images in the medical system database, and the result of the comparison is used for a more accurate diagnosis by the medical professional.
Optimization of road traffic, operation of traffic lights, detection of violations of traffic rules (traffic rules), recognition of vehicle characteristics (number, type, brand, color, etc.)
Optimization of advertising campaigns, look-alike audience (LAL), forecasting views, clicks, reviews, likes and other characteristics of publications
The introduction of artificial intelligence (AI) technologies allows you to increase productivity, optimize and automate various processes insurance companies, as well as improve the quality of customer service. Systems based on machine learning algorithms, natural language processing and data analysis can significantly reduce risks, the likelihood of fraud, give high-quality forecasts, automate and speed up the process of obtaining data for making various decisions Thanks to such systems, the speed of processing applications increases, as well as the level of personalization of insurance products. Artificial intelligence technologies are used, among other things, for better customer segmentation and identifying break-even customers and as a tool to attract audiences interested in new technologies
A wide range of services for data analysis, development of intelligent systems based on machine learning and computer vision
Explore data, identify hidden patterns and anomalies in the data. Segmentation and clustering of data.
Development of analytical systems based on machine learning and computer vision.
Testing hypotheses, conducting scientific research, developing new algorithms.
Analysis and study of the prospects for the implementation of intelligent algorithms for solving business problems.
Ready-made solutions based on computer vision algorithms that need to be retrained using customer data.
Adaptation of artificial intelligence algorithms to tensor processors
For any questions and suggestions, feel free to contact us
Solution Examples
Распознавание параметров объектов
Большие языковые модели (LLM), ChatGPT
Распознавание надписей, номеров, qr-кодов
Прогнозирование поломок, наработки на отказ
Классификация веб-сайтов
Распознавание дефектов поверхностей
Прогнозирование оттока и удержание клиентов
Прогнозирование конверсии продаж
Генерация доменных имен и логотипов
Typical solutions and products developed by the company More
The parts classification system based on computer vision algorithms allows you to automatically determine the type of part, its article, characteristics, as well as highlight defective parts
System for detecting defects on various surfaces, foreign inclusions, print quality, etc.
Face, silhouette, age recognition system
Recognition of numbers, markings, QR-codes, free-form inscriptions
Determination of the quantity, type, brand, speed, color and dimensions of the vehicle
Determining the distances and sizes of objects
Control of presence in hazardous areas, violation of zone boundaries, control of personal protective equipment (helmet, mask, overalls, safety rope, glasses, gloves, device), fire and smoke
Determination in the database of a segment of customers prone to churn
Forecasting sales conversions, optimizing product markups
The system allows you, like chattpt, to find information in a local document database, segment and summarize texts
Интеллектуальное включение рекламы в видео-контент
Система трекинга объектов по видео множества камер
Анализ времени нахождения объекта в зоне, подсчет, классификация и трекинг объектов по заданным параметрам
Intelligent system for analyzing the urban environment More
Самый современный стек технологий
Python, PyTorch, MMDetection, MMSegmentation, Ultralytics (YOLOv8), Transformers (Hugging Face), OpenCV SAIL (TPU - Sophon Artificial Intelligent Library)
Bloom, transformers, tokenizers, datasets, nltk, spacy, pythia GPT, GPT-Neo, GPT-J, BERT, LLAMA, Reformer, Alignment-а (RLHF, ect)
Scikit-learn, Keras, ARIMA, 1D convolutional NN, LSTM, Attention-based, CatBoost/ Light GBM/ XGBoos
Analysis of business requirements and identification of main business goals.
Business requirements analysis and problem statement.
Collection, preparation and preprocessing of data on which the models will be built.
Development and training of algorithms and construction of machine vision models.
Testing, verification of metrics and compliance with business requirements and goals.
Deployment of a full-fledged system, monitoring and support of the solution.
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Russia, Saint Petersburg, Birzhevaya liniya, 16
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