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YOLOv9 Β· SAM 2 Β· OCR Β· VLMs Β· Edge Deployment

πŸ‘ Computer Vision
That Sees. That Detects. That Acts.

Object detection, defect inspection, OCR, and visual AI β€” deployed at production scale. We build computer vision systems processing images and video in real time at up to 60fps, from cloud GPU to Jetson edge devices.

Start Your Project β†’ Book Free Discovery Call
99.1%
Detection Precision
β˜…β˜…β˜…β˜…β˜…
4.9 / 5.0
<100ms
Inference Latency
Edge
Ready
services/ai/vision-pipeline.py
from ultralytics import YOLO
# Production defect detection pipeline
model = YOLO("nexcode-defect-v9.pt")
results = model.predict(
source="rtsp://camera-01/stream",
conf=0.82, device="cuda:0", stream=True
)
# 99.1% precision @ 45fps on Jetson AGX
for r in results: alert_if_defect(r.boxes)
What We Build

Every vision use case,
shipped to production

From production line defect detection to multi-language document OCR β€” we cover every computer vision pattern required in production, trained on your actual images with hard accuracy targets.

Discuss Your Project β†’
  • β†’Object detection and counting in images and live video streams
  • β†’Production line defect detection and quality control at 25–60fps
  • β†’Document OCR: invoices, receipts, contracts, and handwriting recognition
  • β†’Real-time video stream analysis (RTSP, WebRTC, HTTP streams)
  • β†’Face and people analytics (anonymised, fully GDPR-compliant)
  • β†’Visual product search and image similarity at scale
  • β†’Edge deployment on Jetson, Raspberry Pi, and ONNX Runtime
  • β†’Multimodal VLM integration (GPT-4o Vision, Gemini Pro Vision)
Services Breakdown

Full-spectrum
vision engineering

Every layer of computer vision β€” from data labelling to edge inference and cloud monitoring β€” owned by one team.

πŸ”
Object Detection
YOLOv9 Β· RT-DETR Β· ByteTrack

State-of-the-art detection and multi-object tracking for images and video β€” from security cameras to manufacturing lines at 60fps.

  • YOLOv9 and RT-DETR custom model training
  • Multi-class detection and object counting
  • Multi-object tracking (ByteTrack, DeepSORT)
  • RTSP and WebRTC stream processing
πŸ“„
OCR & Document Intelligence
EasyOCR Β· PaddleOCR Β· Layout analysis

Intelligent document processing extracting structured data from invoices, contracts, and forms β€” output clean JSON ready for your systems.

  • Invoice, receipt, and contract field extraction
  • Multi-language OCR (50+ languages supported)
  • Handwriting recognition pipelines
  • Layout-aware parsing for tables and forms
🏭
Quality Inspection
Anomaly detection Β· Surface inspection

Custom-trained defect detection models deployed on your production hardware β€” catching faults that escape human inspection.

  • Defect and anomaly detection on product images
  • Surface, dimensional, and colour inspection
  • Real-time alerting on production line integration
  • Custom training on your product photography
πŸ‘₯
People Analytics
Crowd counting Β· Access Β· Anonymised

Privacy-first people analytics for retail footfall, event management, and access control β€” anonymised and GDPR compliant.

  • Anonymised crowd counting and flow analysis
  • Workplace safety and PPE detection
  • Access control and attendance integration
  • Age and demographic estimation
πŸ–Ό
Visual Search
FAISS Β· pgvector Β· Multimodal

Power "find similar products" and reverse image search with sub-second results across millions of images.

  • Image similarity search at scale with FAISS
  • Product visual search for eCommerce
  • Reverse image search pipelines
  • Multimodal text and image retrieval
☁
Cloud & Edge Deployment
TensorRT Β· ONNX Β· Kubernetes Β· Jetson

We optimise and deploy models for your target hardware β€” from cloud GPU inference to sub-100ms edge on NVIDIA Jetson.

  • GPU inference on AWS, GCP, and Azure
  • TensorRT and ONNX edge optimisation
  • Kubernetes auto-scaling inference servers
  • REST and gRPC inference APIs
Technology

The stack behind every Computer Vision project

Best-in-class tools chosen for performance, reliability, and team expertise β€” not hype.

YOLOv9RT-DETRSAM 2EasyOCRPaddleOCRGPT-4o VisionPyTorchTensorRTONNX RuntimeUltralyticsAWS RekognitionNVIDIA JetsonLabel StudioRoboflow
Our Process

Brief to deployed β€” how we work

A clear, collaborative process with no surprises and working demos at every milestone.

01
Requirements & Data Audit
Week 1

Define the visual task, collect sample images and video, assess data quality, and set precision and recall targets.

02
Data Labelling Pipeline
Week 1–3

Build annotation workflow, create labelling guidelines, label training data, and validate annotation quality.

03
Model Training & Tuning
Week 2–5

Train baseline model, iterate on architecture, augmentation, and hyperparameters with full experiment tracking.

04
Evaluation & Edge Cases
Week 4–6

Evaluate against held-out test data, adversarial samples, and real-world lighting and angle conditions.

05
Inference API & Integration
Week 5–7

Build production inference service with batching, streaming, and monitoring. Integrate with your application.

06
Monitoring & Drift Detection
Ongoing

Monitor prediction confidence, detect data drift, and trigger automated retraining when accuracy degrades.

Why Nexcode

What sets our Computer Vision work apart

πŸ—
Senior Engineers Only

No juniors, no mid-weight delegation. Every engineer on your project is 5+ years experience, senior by any measure.

⚑
Performance as Pass/Fail

We set Lighthouse 90+ as a non-negotiable acceptance criterion β€” not a target, a requirement. Deployments fail if CWV regress.

πŸ§ͺ
Test Coverage Standard

Unit, integration, and E2E tests as standard deliverable. We don't ship without coverage. No exceptions under deadline pressure.

πŸ“
Architecture Before Code

Full system design β€” schema, API contracts, auth, deployment β€” documented and approved before any code is written.

β™Ώ
Accessibility Built-in

WCAG 2.1 AA from component 1, not added at the end. Keyboard navigation, screen readers, colour contrast β€” non-negotiable.

πŸ”
Weekly Working Demos

End of every sprint, you get a live staging URL to click through. Not a Loom recording β€” a real deployed demo.

πŸ”’
Zero Lock-in Guarantee

100% IP & code transfer. Your repo, your infra, your AWS account. Full documentation so your team can own it the day we hand over.

πŸ“Š
Analytics-Ready Launch

GA4, Mixpanel or Amplitude wired in before go-live. You launch with data, not waiting weeks to set up tracking after.

How we compare
Criteria ✦ Nexcode Typical Agency Offshore Dev Shop Freelancer
Full IP & code ownershipβœ“βœ“βœ“βœ“
Client Reviews

What clients say about our Computer Vision work

β˜…β˜…β˜…β˜…β˜…
4.9 / 5.0 Β· 50+ AI projects
"

Nexcode rebuilt our entire frontend in Next.js App Router in 12 weeks. Lighthouse score went from 41 to 97. The code quality, test coverage, and documentation are unlike anything I've ever received from an external team. We extended the engagement twice.

SM
Sarah Mitchell
CTO, Apex Financial Β· SaaS Platform Rebuild
β˜…β˜…β˜…β˜…β˜…
Upwork Verified
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"They architected and built our entire web platform from scratch β€” real-time collaboration, complex permissions, WebSockets. Every edge case handled, zero bugs at launch."

JK
James Kowalski
CEO, NovaBrain AI
AI Web Platform
β˜…β˜…β˜…β˜…β˜…

"Our new storefront loads in 0.8s and converts at 3.2x our old Magento site. Every detail considered β€” mobile-first, accessibility, structured data. The results speak."

RP
Rachel Patel
Director, LuxeCommerce
Headless eCommerce
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"From Figma to deployed in 8 weeks. Their React architecture thinking sets them apart from every agency I\"

TN
Thomas Nguyen
Founder, WanderGo
Travel Booking Platform
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"200K concurrent users on launch day β€” not a single outage. The infrastructure and caching strategy Nexcode built handled load I didn\"

LM
Laura MΓΌller
VP Product, EduPath
EdTech LMS
β˜…β˜…β˜…β˜…β˜…

"The real-time dashboard processes 1M+ events/day without a hiccup. Clean code, exceptional docs, and they explained every architectural decision. Extended the team afterward."

AK
Amir Khan
CTO, SwiftFreight
Logistics Dashboard
FAQ

Computer Vision questions
answered

Have a question not covered here? Book a free 30-min call β†’

How much training data do we need for computer vision?↕
It depends on task complexity. Binary defect detection on a consistent background can achieve excellent results with 500–1,000 labelled images per class. Multi-class detection in varied environments typically requires 2,000–10,000 per class. We use transfer learning and synthetic augmentation to reduce your labelling requirement significantly.
Can computer vision run in real time on a production line?↕
Yes. We deploy systems running at 25–60fps on production hardware. TensorRT optimisation achieves sub-100ms inference on NVIDIA Jetson AGX for edge deployment. We validate on your actual hardware before every go-live.
How do you handle GDPR compliance for people detection?↕
We design privacy-first: anonymisation at source, no storage of identifiable faces, on-device processing where possible, and full GDPR documentation. We build architectures where raw images never leave your facility.
What does a computer vision project cost?↕
Custom object detection with cloud inference API from Β£14,000. Production line defect detection system from Β£22,000. Full edge deployment with hardware setup from Β£32,000. All include training, evaluation, deployment, and 30 days support.
Related Services

Often paired with Computer Vision

🧠
Multimodal LLMs
β†’
πŸ“
NLP & Text AI
Document intelligence
β†’
βš™οΈ
Model deployment ops
β†’
πŸ€–
Vision-powered agents
β†’
πŸ‘

Build computer vision that sees what humans miss.

Free vision scoping call. We review your visual task, assess your data, and provide a fixed-price proposal with a realistic accuracy target.

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