Technological tasks
The Tech-tasks module is tasks related to the development, implementation and improvement of new technologies, products and processes. If you have development, implementation and other needs you can post information below.
Brand Pulse
The purpose of the project Development, customization, implementation and provision of access to a scalable SaaS platform based on artificial intelligence for comprehensive monitoring of social networks and mass media, analysis of message tonality. Task description The project includes the creation and maintenance of a system consisting of the following functional units and capabilities: Facebook Instagram, TikTok, Telegram, VK, YouTube, Facebook, X/Twitter, Threads) and online media (via RSS and HTML parsing). AI Analytics (AI Core): Using machine learning models for: * Natural Language Processing (NLP): Language detection, tonality (positive/negative/neutral), and topic classification. * Computer Vision (CV): Detection of logos and brand products in images and videos. * OCR and Transcription: Extract text from images and translate speech into text from audio/video content. Competitor analysis: Comparative analysis of mentions of the Customer's brand and competing brands, including analysis of the Share of Voice, tonality and activity of influencers. Visualization and reporting: Providing a web dashboard for real-time analytics, generating automatic daily summaries and text summaries with insights. Operational notifications: Integration with a Telegram bot to send alerts about critical events (spikes in activity or negativity) and regular reports. Implementation services: Platform adaptation to business requirements, setup, integration, team training and technical support according to SLA.
Decision acceptance deadline
08.01.26 (inclusive)
Preferred systems
Neurotechnology and artificial IntelligenceNumber of applications
4
Development Quality Monitoring Module (Quality Radar)
To develop an analytical module that provides continuous monitoring of the quality of software development at the level of code, modules, services, and teams. The module should automatically collect and analyze data from task and code management systems (Git, Jira, ClickUp, CI/CD, bug tracking systems), including defect history, error recurrence, regression frequency, change density, code complexity, number of post-release edits, and component stability. Based on the combined analysis, the system should identify weak and unstable areas, identify high-risk areas, form quality ratings for components and teams, and provide recommendations on prioritizing technical debt and improving quality.
Decision acceptance deadline
08.01.26 (inclusive)
Preferred systems
Intelligent control systemsNumber of applications
3
Security control, territory patrolling and transport control
Security control and patrolling of the territory A system for monitoring the work of security guards using RFID or iButton tags: • Patrol routes are prescribed in the software; • Each control point is equipped with a label; • The guard is marked with a reader when going around; • If the point is not passed in time, an alarm is triggered. The electronic pass system automatically records every entry and exit of vehicles. The camera detects the number of the car, checks it against the database, and, if there is a permit, opens the barrier. All data — time, driver, purpose of the visit — is saved.
Decision acceptance deadline
08.01.26 (inclusive)
Preferred systems
Industrial SafetyNumber of applications
1
Development of an information and analytical system for optimizing energy consumption of energy-intensive production processes
The aim of the project is to create a software system that improves the energy efficiency of production processes through automated data collection, calculations of key parameters, forecasting energy consumption and issuing recommendations on optimal operating modes of equipment. The system under development should include modules for data integration, machine learning, analysis, and visualization. The system provides calculation of actual energy efficiency indicators, modeling of energy consumption in various modes, automatic generation of recommendations, real-time parameter monitoring and provision of analytical information to the user in a convenient form. The project provides for the implementation of an architecture that includes subsystems for data collection and normalization, forecasting, optimization, calculations, visualization, analytics, reporting and administration. The system should support continuous retraining of models to improve the accuracy of forecasts and the effectiveness of recommendations.
Decision acceptance deadline
07.01.26 (inclusive)
Preferred systems
Information processing and transformationNumber of applications
5
Integration of the core banking system with the national payment system of Uzbekistan
Increase Technology Company implements international fintech projects in Central Asian countries. As part of the expansion of its presence in Uzbekistan, it is necessary to develop and implement the integration of the core banking system with the national payment infrastructure of the country. The task includes analyzing the architecture of Uzbekistan's payment system, working out API integrations, security requirements, compliance with local regulation, as well as designing payment flows for B2C and B2B scenarios.
Decision acceptance deadline
07.01.26 (inclusive)
Preferred systems
Information processing and transformationNumber of applications
3
AI module for personalized chess learning trajectory (Adaptive Chess Coach)
The project is aimed at creating an AI mentor who analyzes a chess player's game data (games, tactical tasks, rating dynamics) and forms an individual training plan. The AI uses recommendation algorithms and learning from historical player data, automatically suggesting tasks, topics, and games that best match the student's current level and goals.
Decision acceptance deadline
07.01.26 (inclusive)
Preferred systems
Neurotechnology and artificial IntelligenceNumber of applications
3
AI analysis of chess players' games and game errors (Smart Game Analyzer)
The module is designed for intelligent analysis of chess players' PGN games on the platform. The system uses machine learning and analysis of large arrays of games to identify typical errors, weak stages of the game (opening, middlegame, endgame), as well as recurring strategic problems. AI generates personalized reports and recommendations for players and coaches.
Decision acceptance deadline
07.01.26 (inclusive)
Preferred systems
Neurotechnology and artificial IntelligenceNumber of applications
2
AI module for the generation and adaptation of training tasks (Adaptive Task Generator)
The project aims to develop an AI module that automatically generates learning tasks and adapts their complexity based on the student's learning history. Module Uses NLP and ML models to analyze errors, successful solutions, and execution speed, forming personalized tasks, hints, and additional exercises. The system learns from the platform's data and continuously improves the quality of recommendations.
Decision acceptance deadline
07.01.26 (inclusive)
Preferred systems
Neurotechnology and artificial IntelligenceNumber of applications
3
AI module for intelligent analysis of students' learning activity (Learning Bottleneck Detector)
The module is designed for intelligent analysis of learning activity on platforms. The system automatically collects data on students' interaction with content (task solving, completion time, attempts, errors, transitions between topics) and uses machine learning methods to identify patterns of difficulties and cognitive overload. AI generates personalized recommendations for students and analytical reports for teachers, identifying problematic topics, ineffective assignments and violations of the logic of learning trajectories.
Decision acceptance deadline
07.01.26 (inclusive)
Preferred systems
Neurotechnology and artificial IntelligenceNumber of applications
2
Development of an algorithm for accelerated reading and streaming indexing of text data for high-load document analysis systems
The aim of the project is to develop and implement an algorithm for accelerated reading of text data and parallel streaming indexing, which significantly reduces document processing time during mass inspections and an increase in the volume of stored data. The project aims to optimize the following steps: • reading files of various formats (DOCX, PDF, TXT, RTF); • converting documents into a unified text representation; • parallel indexing of text blocks without waiting for the document to be fully loaded; • Minimizing disk I/O operations when working with large data bodies. The algorithm involves the use of chunk-based processing, asynchronous read streams, and adaptive allocation of indexing tasks.
Decision acceptance deadline
05.01.26 (inclusive)
Preferred systems
Intelligent control systemsNumber of applications
1
