AI solutions case studies demonstrate machine learning deployed into real operational environments - from intelligent queue management that reduced cashier idle time by 57.66% at a major retailer, to AI-powered road inspection that cut CO2 emissions by 90% across 21,000+ km, to MLOps infrastructure for grid intelligence startups, to voice-to-text systems that let paramedics document hands-free during emergencies.
Automated Visual Inspection
Automated visual inspection system for the Baltic States' largest sportswear manufacturer, solving fabric quality control problems that manual inspection could not handle at production speed.
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Real-Time Defect Detection
Automated defect detection system for Europe's second-largest hardwood flooring manufacturer, solving quality control problems that manual inspection could not handle at scale.
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Near-Zero Defect Rate
Developed an automated visual inspection system for furniture manufacturing that scans every board in real-time, detecting defects against CAD specifications.
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Autonomous Threat Detection
Developed AI object detection algorithms enabling autonomous identification of buried and surface-level explosive threats for Broswarm's drone platform.
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57.66% Idle Time Reduction
Deployed intelligent queue management at one of Central and Eastern Europe's largest retailers, reducing cashier idle time by 57.66% and preventing 237 queue incidents.
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93-100% Detection Accuracy
Deployed AI-powered PPE detection at one of the Baltic region's largest food manufacturers, achieving 93-100% accuracy across plants and logistics centers.
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Real-Time Object Detection
Developed onboard machine vision algorithms for KrattWorks, enabling autonomous object detection for aerial surveillance in defense and emergency response.
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180× Faster Processing
AI solution that reconstructs 3D anatomical models from CT scans in under 60 seconds - replacing a 3-hour manual workflow for Europe's leading orthopedic implant manufacturer.
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12,000+ Human Hours Invested
Transformed a grid intelligence startup's ML operations from notebook-based experimentation to a production-grade MLOps practice for utility infrastructure.
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