Computer Vision
High-Throughput Spatial & Temporal Intelligence
We design, train, optimize, and deploy end-to-end computer vision pipelines for sports performance, industrial operations, and video intelligence. From camera calibration and 3D coordinate projection to real-time multi-object tracking and sub-millisecond edge inference, Alector Lab builds vision systems that operate reliably in challenging visual environments.
We build modular vision pipelines that decouple video ingestion (RTSP/WebRTC), accelerated frame decoding, neural inference (YOLOv10, RT-DETR, custom transformers), spatial tracking (ByteTrack, BoT-SORT), and downstream analytics into high-performance C++ and Python microservices.
Architectural Building Blocks
Multi-Camera Fusion
Synchronize multiple camera angles with automatic homography calibration to generate unified 3D spatial coordinate feeds.
Edge-Optimized Inference
Quantize models (INT8/FP16) for real-time execution on NVIDIA Jetson, Intel OpenVINO, or industrial IPCs without cloud round-trips.
Event & Action Detection
Temporal deep learning models that recognize domain-specific events, safety violations, athletic maneuvers, and workflow anomalies.
Synthetic Data & Active Learning
Systematic data engines that identify edge cases in production, queue them for labeling, and trigger automated re-training cycles.
Full Technical Coverage Areas
All Computer Vision systems are delivered as production code, custom microservices, or fully managed appliances with complete IP transfer to clients.
Request an Architecture Assessment for Computer Vision
Speak directly with our senior systems architects regarding your latency, throughput, and data requirements.