The introduction of artificial intelligence and machine learning technologies is becoming a key factor in business competitiveness. Companies are looking to use data to predict, automate processes, and improve decision-making. However, without a properly built infrastructure, the implementation of AI/ML solutions becomes complex, costly and does not give the expected result.

Many organizations lack a single platform for working with data, training models, and implementing them into business processes. Data is stored in different systems, model development processes are not standardized, and implementation of solutions requires significant effort. This slows down the launch of projects and limits the scaling of AI initiatives.

Consulting on building an AI/ML infrastructure allows you to create a technological basis for effective work with data and the implementation of intelligent solutions. We help companies build a scalable and manageable platform that provides a full cycle of working with AI - from collecting and preparing data to introducing models into industrial operation.

The project includes an analysis of the current IT landscape, data sources and business challenges. Infrastructure requirements are determined, including data volumes, computing resources, and performance requirements.

Based on the analysis, the architecture of the AI/ML platform is developed, including data storage and processing systems, tools for developing models, learning environments and deployment mechanisms (MLOps). Automation processes are being introduced to speed up the development and implementation of models.

Particular attention is paid to the integration of AI solutions with existing company systems (ERP, CRM, BI), as well as issues of security, access control and data quality control.

We are also introducing model monitoring tools to monitor their efficiency and correctness in real time.