Client: a USA startup in social media sphere.Task: The idea of the project was to create an event-based social network with the focus on locations and easy sharing between users. Users have had an option to create new events and lock them with a password to share only between people they want to. The outstanding feature was the ‘searching for an event’ based on location within the specific radius and your own preferences (categories). It had integration with maps and other social networks (like Facebook and Twitter) to help users navigate and share photos, videos and moments with others.Our company developed a web site and mobile native applications for iOS, Android and Windows Phone. The project was considered as high load, and the architecture was built to meet this requirement.
Technologies used: Amazon AWS, Java, MySQL, AngularJS, Objective-C, C#
Customer: Russian enterprise-passenger transport and freight.
Task: automate the ticket control planning, passenger flow analysis and generate live reports.
Description: The RELEX team designed and implemented the entire database schema and the system architecture. The application has 3 modules: ticket control system, passenger flow analysis and a database application.
The plan ticket control. Generates route ratings based on primary raw data and aggregates route checking, ticket collectors schedule and tasks for each ticket collector.
Passenger flow analysis. Analyzes the passenger flow via a subsystem that determines a vehicle location at a station and calculates the number of entering passengers.
Database Application. The end application handles large amounts of data: 3 to 7,5 million records per day. As a result, several tables (over 2 billion records each) are processed concurrently in the online database, and with the accumulation of history these numbers will grow.
Customer: world’s leading anti-spam service provider.
Task: The Customer requested our team to enhance and support its product
Solution: The RELEX team designed and developed the low level (kernel) of the incoming e-mail analysis system. Based on the kernel was created a new email scanner. To improve the filtering quality, the following functions were implemented in the system:
- Message language auto-detection (without impairing the performance),
- Natural language parsing
- Collecting statistics based on the parser results.
These functional modules became the basis for an artificial intelligence system and containers for storing and accessing the accumulated statistics. Our team successfully resolved the task of filtering messages in Eastern languages (Chinese, Korean, Japanese etc.). The final application, besides the high email filtering quality and additional services, can process over 500 messages per second with full content analysis in the integrated target system.It also uses traditional methods of spam traffic limitation, like filtering the incoming TCP/IP traffic by the incoming IP address, which helps narrowing down the channel for unknown or suspicious traffic sources.Along with spam filtering, the system can identify messages of some specific categories, such as phishing, mail/safe-list and bounce/backscatter auto-generated.