Computer visual intelligence.

Computer vision systems for object detection, image classification, OCR, quality inspection, and video analysis — built with the right balance of accuracy, latency, and deployment footprint for your use case.

Overview

What it means in practice.

Computer vision delivered on its decades of promise around 2018, and the toolkit has only matured since. We build vision systems that work in production — handling real lighting conditions, real camera variation, and real edge cases that demos politely skip.

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What we deliver

Capabilities & deliverables.

Every engagement gets shaped to fit, but these are the building blocks we rely on.

01

Object Detection

Real-time detection for retail, manufacturing, and logistics — counting, tracking, and locating objects in images and video streams.

02

Image Classification

Custom classifiers trained on your domain — defect detection, content categorization, document type identification — with calibrated confidence scores.

03

OCR & Document AI

Text extraction from scanned documents, invoices, IDs, and forms. Multilingual OCR with structured output suitable for downstream automation.

04

Quality Inspection

Industrial vision for assembly line inspection — surface defects, missing components, dimensional checks. Faster and more consistent than manual QC.

05

Video Analytics

People counting, dwell time analysis, queue monitoring, and behavioral patterns from CCTV or IP camera feeds. Privacy-respecting by design.

06

Edge Deployment

On-device vision for low-latency, privacy-sensitive applications. ONNX, TensorRT, and Core ML deployments tuned for the target hardware.

PyTorch YOLO OpenCV ONNX Runtime TensorRT Tesseract Hugging Face Vision Roboflow
Why it works

The SD Technolabs approach.

Two decades of engineering practice, sharpened by the realities of production AI.

01

Realistic accuracy targets

We tell you what's achievable on your data before training starts. No promised 99% on a problem that's structurally 87%.

02

Edge or cloud, picked deliberately

Latency, privacy, and cost trade-offs decided up front. We deploy where the problem actually lives.

03

Annotated data, done properly

We help with annotation tooling, quality review, and class balancing. Models are only as good as the data behind them.

04

Production monitoring

Drift detection, accuracy tracking, and re-training triggers. Vision models degrade quietly without proper observability.

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Let's discuss how this fits your business. We reply within one working day.

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