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Data Science solutions for your success

Artificial intelligence and machine learning technologies become an efficient tools for business nowadays. You can improve workflow, get offers that attract customers, and raise profit margins by using ml or ai applications. Let data-driven decisions lead you to the aim.


Segmented unique trading advantage


Connected Vehicles









Connected Vehicles

Leveraging Data science and Internet of Things (IoT) technologies allows companies to reduce risks and costs related to vehicle investment, its management and telematics.

Drivers' behavior tracking

Embedded vehicle trackers allowed to analyze drivers' behavior and detect any speed changes or violation of safe driving criteria by using machine learning technologies.

Crash Elimination

The system provide crash-free driving and improve car safety. IoT devices allow to monitor the environment and make up for lapses in driver attention.

Logistic optimization

AI-models make delivery more timely and cost-effective. Routes can be planned and optimized according to traffic conditions and other factors.

Saving fleet maintenance costs

Hardware gather detailed data about the state of your fleet and allow to eliminate equipment breakdowns by sending maintenance alerts.

Cutting labor costs

Car tracking devices allow to monitor employee activities (including time spent on breaks), identify unauthorized stops, and evaluate overtime requests.

Seamless integration

Fleet management software can be easily connected with the company’s existing infrastructure.


AI-based business software will provide easy-to-use technologies for your customer and improve operational efficiencies for you.

Proactive fraud detection

With development of technologies there are more opportunities of fraudulent transactions. ML systems provide cyber security gap analysis and protect your data.

AI bot

No crowd and waiting for ages. Bots help to solve customer issues immediately and improve engagement rate.

Predictive analytic

Data Science approach allows financial specialists to identify and react on market changes faster than with convectional methods.

Risk analysis

AI and ML tools are able to analyze huge amounts of data that help to detect anomalies and prevent risks.

Offer personalization

Machine learning algorithms process the data and help to provide offers that attract customers.

Better targeting

Data-driven segmentation allow to create detailed profiles of your audience. That opportunity will help you to find better decisions to drive more targeted campaigns.


With increased competition in the telecom & media industries, this is the time to come up with solutions. ML and AI tools help to build more revenues and stronger customer relationships.

Proactive fraud detection

The machine learning algorithm defines the anomalies and with the help of data visualization techniques present them as alerts in real time.

AI bot

No crowd and waiting for ages. Machine learning chatbot can offer a better 24/7 customer service and improve engagement rate.

Offer personalization

Machine learning algorithms process the data and help to provide offers that attract customers.

Security risk analysis

Machine Learning and Artificial Intelligence technologies provide cybersecurity risk analysis and define the anomalies or suspicious behavior.

Sentiment Analysis

It is an alternative to automatically measure consumer’s engagement. Emotion detection helps to assess the customer positive or negative reaction to the service or product in a real time.

Audience segmentation

The key to success for the telecom is to segment their market . Machine learning technologies allow to predict needs and preferences of each customer group.


Ecommerce sector is one of the biggest consumer of Data Science methods. Don't stand by. Use AI and Machine Learning models to improve your workflow and unveil better customer service capacities.

Logistics optimization

Artificial intelligence is what you need to do the route optimization and reduce the costs and make the shipping process itself faster.

Product Recommendations

By analyzing customer data from omnichannels, ML algorithm identify behavior and purchasing patterns which will help you improve website conversion.

Sales prediction

Predictive AI capabilities allow to analyze past click-through behaviors, product preferences and forecast future sales.

Proactive fraud detection

ML solutions allow to process the repetitive data at rapid speed and prevent fraudulent transactions before they happen.

AI bot

Chatbot is a great way to improve client retention. No more stress, complains, and misunderstanding.

Offer personalization

Using a past behavior and preferences, AI-system will recommend offers that attract customers.


AI and ML are the hottest retail technologies trend among industry players. They integrate business intelligence tools across the entire sales cycle to increasing sales and reduce costs.

Behavioral Tracking via Video Analytics

Use Computer vision algorithms to track customer' insights to modify product placements and create efficient promotions.

Theft Prevention

ML services can alert in real-time security personnel or managers about attempts to hide an item in backpack or jacket by leveraging recognition algorithms.

Logistics optimization

ML shows opportunity to reduce logistics costs by finding patterns in track-and-trace data provided by IoT sensors and devices.

Sales prediction

The aim of sales forecasting is to estimate how buyers will behave in the future based on data of previous behaviors.

In-Store Assistants

Artificial intelligence mobile apps can help customers to find needed items or suggest ones that are probably missing from the list.

Visitors segmentation and offer personalization

Client segmentation allow retailers to perform personalized proposals that are more effective than general approaches. Such approach increases loyalty and customer retention.


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Micro-iterative Approach

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Data Science Environment

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End-to-end Services

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Build a Prototype

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Bespoke Solutions

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Expert Session


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Connected Cars X

The aim was to create solution to analyze drivers' behavior and detect any changes in it with using machine learning technologies. The system also had to provide the ability to collect accurate vehicle performance data while driving. It should allow to provide flexible insurance services rate based on driving style.

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Sports events analysis

The Customer needed to develop a system with using machine learning predictive analytics. The challenge of the system was to detect and analyze goal shot events in soccer broadcast video streaming services.

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Parcel Station

The client wanted to develop a machine learning solution that allows to search parcel' information by a photo of the package tracking number.

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Advanced Driver Assistance System

The challenge was to build a brand new platform with using computer vision system. Along with all the standard management features, this program would help to make driving more safe.

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Audience reaction recognition

The challenge was to create sentiment analysis software to detect and analyze audience reaction using machine learning algorithms.


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Privacy Policy © 2019 COMMETA. All Rights Reserved.

Privacy Policy


This Privacy Policy explains what personal data of yours will be collected and how it will be used and protected by LLC COMMETA (hereinafter referred to as Commeta) when you visit our website at (the ‘Site’), use our related services (‘Services’) by subscribing to our newsletters, and/or download and use any Commeta proprietary applications (the ‘Applications’).

This Privacy Policy outlines how we treat your personal data when you use our Site, Services, and Applications. We recommend you to read this Privacy Policy before using the website and Applications to understand what personal data of yours (personally identifiable information about you) is collected and used by Commeta, how you can control such collection, correction and/or deletion of your personal data and how to get in touch in case of need. Please note, that our website is not directed to children under the age of 16, therefore we do not knowingly collect personal data from children under this age. If you are under 16, then please do not send us any personal information.

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Changes to our Privacy Policy

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