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.
Разработка отказоустойчивой IT-инфраструктуры с автоматическим переключением между дата-центрами
Цель проекта: Разработать и внедрить отказоустойчивую серверную инфраструктуру для международного мобильного приложения Kid Security, обеспечивающую бесперебойную работу сервиса при авариях, кибератаках или полной недоступности одного из дата-центров.
Decision acceptance deadline
30.10.26 (inclusive)
Preferred systems
Decentralized generationNumber of applications
1
Разработка подсистемы расширенных ИИ-запросов (GenAI чат-бот) и Интеграции с Единой платформой недропользования (ЕПН) как развитие проекта «Разработка подсистем для обработки геологической информации с использованием технологий искусственного интеллекта, а также хранения оцифрованных геологических данных».
Назначение проекта заключается в разработке Подсистемы расширенных ИИ-запросов (GenAI чат-бота) и интеграции с Единой платформой недропользования (ЕПН), обеспечивающих поиск, получение и использование структурированных геологических данных посредством технологий искусственного интеллекта и интеграционного взаимодействия с государственными информационными системами.дог
Decision acceptance deadline
28.10.26 (inclusive)
Preferred systems
Processing and storage of Big DataNumber of applications
0
Smart Factory Automation Program
Smart Factory Automation Program — программа поиска и внедрения автоматизированных решений для производственных и логистических процессов завода. Цель проекта — совместно со стартапами и технологическими компаниями выявить повторяемые операции и внутризаводские перемещения, которые могут быть автоматизированы, разработать и протестировать практические решения, а затем масштабировать подтвердившие эффективность решения на другие процессы завода. Приоритетные направления: автоматизация внутризаводской логистики — AGV/AMR и другие решения для перемещения материалов, тары, комплектующих и расходных материалов; автоматизация операций качества и rework — автоматизированная обработка, контроль и доработка продукции; компьютерное зрение, датчики и другие технологии для повышения стабильности и эффективности процессов.
Decision acceptance deadline
19.10.26 (inclusive)
Preferred systems
Robotics components and sensoricsNumber of applications
9
Linking completed physical volumes to BIM according to estimates and acts with tracing to finite elements
To investigate the recognition of estimates and acts of completed work and the comparison of their lines with the final BIM elements by area, type of work and volume. Create a prototype with two-way tracing: document and its version → line → type of work → Element ID and model version. For each relationship, save the quantity, unit of measurement, completion status, and matching basis. Select related elements in 3D by line of the document, and show the source lines and counted volumes by element. Maintain "many to many" connections, partial implementation, and the history of adjustments to documents and models.
Decision acceptance deadline
07.10.26 (inclusive)
Preferred systems
Neurotechnology and artificial IntelligenceNumber of applications
15
Digitizing the knowledge base into requirements and a graph of connections using AI
To investigate the extraction of verifiable requirements from standards, regulations, tables and diagrams. Create a prototype registry with the ID, source, version, owner, scope, and verification method. AI should offer links to standard solutions and dependent requirements, identify contradictions; publication of requirements and links is carried out after verification by an expert.
Decision acceptance deadline
07.10.26 (inclusive)
Preferred systems
Neurotechnology and artificial IntelligenceNumber of applications
18
Verification of design solutions according to corporate standards using AI
To investigate which requirements of corporate standards can be verified by geometry, parameters, and relationships of BIM objects. Create a prototype in which the AI interprets the requirement, and the approved rules perform verification. For a comment, show the standard clause, the affected elements and the proof; if there is a shortage of data, give the appropriate status.
Decision acceptance deadline
07.10.26 (inclusive)
Preferred systems
Neurotechnology and artificial IntelligenceNumber of applications
11
Development and implementation of the "Digital Worker" digital platform
Development and implementation of new scientifically based methods and algorithms using advanced artificial intelligence technologies to automatically assess the condition of staff before starting a shift based on the analysis of biomedical monitoring data and the employee's digital profile to: • Ensure a transparent, anti-fraud and automated medical examination process. • Preventing unacceptable work assignments based on objective medical and behavioral data. • Reducing the risks of occupational injuries and deaths from cardiac and other acute conditions. • Reducing the time required for medical examinations and registration of orders. • Implementation of advanced artificial intelligence technologies based on generative LLM models with RAG architecture, decision-making systems based on AI agents, and predictive analytics based on machine learning (ML).
Decision acceptance deadline
18.09.26 (inclusive)
Preferred systems
Labor protection, industrial safety, environmental protection and production operationsNumber of applications
10
Development of a predictive equipment maintenance system based on telemetry and machine learning
To develop a hardware and software complex that collects data from industrial equipment, detects early signs of node degradation and predicts failures before they occur, shifting maintenance from scheduled to state-oriented. System composition: Data collection. Modules for removing telemetry from vibration, temperature, current, pressure and RPM sensors; connection to existing automation systems using industrial protocols; data buffering in case of loss of communication and reloading after recovery. Storage and processing. A time series server with a high recording frequency, normalization and purification of signals, binding readings to a specific piece of equipment and operating mode. The analytical core. Models for detecting anomalies and predicting the remaining resource of nodes, trained on historical operational data and recorded failures. Gradual retraining as data accumulates in a particular enterprise. Service management. Automatic generation of repair requests indicating the node, the nature of the deviation and the recommended time; accounting for the repair history; calculation of the need for spare parts based on the forecast. Interfaces. A web-based equipment fleet status panel with a color indication of risk, a card for each unit with graphs of indicators, mobile access for staff at the site, and notifications of critical deviations.
Decision acceptance deadline
05.08.26 (inclusive)
Preferred systems
Intelligent control systemsNumber of applications
7
Development and implementation of the Digital Employee digital platform
Development and implementation of new scientifically based methods and algorithms using advanced artificial intelligence technologies to automatically assess the condition of staff before starting a shift based on the analysis of biomedical monitoring data and the employee's digital profile to: • Ensure a transparent, anti-fraud and automated medical examination process. • Preventing unacceptable work assignments based on objective medical and behavioral data. • Reducing the risks of occupational injuries and deaths from cardiac and other acute conditions. • Reducing the time required for medical examinations and registration of orders. • Implementation of advanced artificial intelligence technologies based on generative LLM models with RAG architecture, decision-making systems based on AI agents, and predictive analytics based on machine learning (ML).
Decision acceptance deadline
16.04.26 (inclusive)
Preferred systems
Labor protection, industrial safety, environmental protection and production operationsNumber of applications
5
To carry out research and development work on the development of an intelligent dispatching system at the Zhomart and Zhilandy mines of Kazakhmys Corporation LLP
Development of an intelligent dispatching system at the Zhomart and Zhilandy mines of Kazakhmys Corporation LLP
Decision acceptance deadline
14.04.26 (inclusive)
Preferred systems
Industrial SafetyNumber of applications
7
