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
Solutions and systems based on machine vision, video analytics, image recognition, photo and video streams
Solutions and systems based on natural language synthesis and recognition, automation of call centers
Typical solutions and products developed by the company
Counting transport and passenger traffic
Recognition of numbers, markings, QR-codes, free-form inscriptions
Determination of type, shape, speed, color and geometry of objects
Determining the distances and sizes of objects
Control of being in hazardous areas, violation of zone boundaries, fires and smoke
Determination in the database of a segment of customers prone to churn
Forecasting sales conversions, optimizing product markups
Highlighting keywords, tags, sentiments of text, analysis of the meaning and intonation of texts
We develop and implement machine learning modules in information systems for solving applied business problems
Some of the challenges that companies face:
The company is based on the international laboratory of machine learning at ITMO University and develops in the field of machine learning algorithms, computer vision and data analysis for solving various business problems. In recent years, many projects have been implemented for the largest enterprises in Russia, including Yandex, Mail.ru Group, Norilsk Nickel, Megafon, NMLK, Evraz, Sinara-Transport Machines, Gazprom Neft. This allowed us to accumulate sufficient experience and become a leading company in the implementation of machine learning algorithms, computer vision and data analysis.
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Today, 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.
On the basis of artificial intelligence, side traffic warning systems, autopilots, and autonomous vehicles are being built.
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.
Calculations that require graphics and tensor processors.
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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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