AI-powered efficiency and resilience for modern manufacturing
SoDa helps manufacturers unlock efficiency, ensure supply chain resilience, and improve decision-making with AI-driven platforms and analytics. Beyond technology, SoDa also provides consulting guidance, our experts with backgrounds in industrial operations and consulting understand production complexity, procurement challenges, and cost pressures.
Optimize production lines with real-time performance analytics.
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Anticipate maintenance needs with predictive AI, reducing unplanned downtime.
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Improve product quality with automated defect detection and root-cause analysis.
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Increase supply chain resilience with end-to-end visibility and supplier risk monitoring.
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Enhance cost control and procurement efficiency with AI-driven insights.
From Data to Operational Excellence
SoDa transforms production and supply chain data into actionable intelligence, helping manufacturers reduce costs, improve quality, and achieve operational excellence
Production & Performance Reporting
Reporting on various aspects of the company's activities: control of the execution of the production program, analysis of the proportion of defects, prediction of equipment failures, analysis of energy consumption, etc.
End-to-End Data & AI for Manufacturing
We offer solutions that include the creation of BI systems for monitoring and analyzing production processes, the development of data warehouses for centralized information storage, and the implementation of artificial intelligence-based tools. These technologies make it possible to automate control over key stages of production, optimize resource use, and improve the accuracy of forecasting demand and equipment utilization.
Tailored for Industry Reliability & Speed
We understand the specifics of the industrial sector and know how important reliability, data processing speed and integration with existing infrastructure are. Our solutions enable enterprises to improve supply chain management, reduce the likelihood of unplanned downtime by predicting equipment failures, and make more informed management decisions based on up-to-date analytics.