Visual data accumulates faster than humans can process it: production line images, document scans, security footage, customer-submitted photos. Vision has historically lived in research labs or expensive specialized hardware. Cloud and edge advances have moved it into the operational layer of regulated industries that depend on visual workflows.
Computer Vision Solutions automate the analysis of that data with the precision of production demands. Total Sync engineers custom vision systems for real-world conditions, regulatory environments, and the operational scale where general-purpose tools fall short of what production needs.
Custom computer vision systems trained on your visual data and deployed for your operational environment. We handle variable lighting, occlusion, edge deployment requirements, and the regulatory standards that come with regulated industries. Models deploy at the edge for sub-100ms inference or in the cloud for batch processing, depending on what your operations require. Model training uses your labeled data combined with augmentation techniques that improve robustness to lighting, angle, and condition variations encountered in real deployment.
Custom model training on your specific visual data and use cases.
Edge or cloud deployment based on latency and bandwidth requirements.
Real-time inference at industrial scale (millions of images per day).
Multi-modal document understanding spanning text, tables, and layouts.
Video analytics with object tracking and behavior detection.
Biometric authentication systems for secure access scenarios.
Continuous accuracy monitoring and retraining pipelines.
Automate the analysis of visual data with the precision of production demands.
Manufacturing quality inspection on production lines, detecting defects at industrial speeds before products ship.
Document processing and intelligent data extraction at scale, turning unstructured scans into structured, queryable data.
Retail shelf analytics for stock levels and planogram compliance, using in-store cameras to monitor inventory in real-time.
Audits the visual data, operational environment, latency requirements, and regulatory constraints.
Covers model architecture, training data strategy, deployment topology, and integration design.
Includes model training, validation against production conditions, and phased rollout.
Integrates the vision system with downstream decisions and handles capability expansion.
Post-launch, model accuracy is monitored against production conditions, triggering retraining on drift signals. Typical timeline runs 8 to 14 weeks.
Manual visual review introducing delays, inconsistency, and operational bottlenecks.
Real-time visual decisioning at an industrial scale with consistent accuracy.
Schedule a discovery call to assess your visual workflows and identify where computer vision delivers the strongest operational impact.
Industrial cameras, machine vision systems, NVIDIA edge devices, Intel OpenVINO, AWS, GCP, Azure, and custom hardware.