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Computer Vision Engineering

We Build Systems That See.

From object detection to AR-guided diagnostics — we engineer production-grade computer vision systems that see, understand, and act.

PyTorch TensorFlow OpenCV ONNX Edge AI CUDA ARKit / ARCore
What We Build

Engineering Services

End-to-end computer vision development — from model training to edge deployment. We turn your camera feeds into actionable intelligence.

Object Detection & Tracking

Real-time detection, classification, and tracking of objects across video streams. People counting, vehicle tracking, defect detection.

Visual AI Assistants

AR-powered guidance systems that overlay instructions on real-world views. Camera-based diagnostics, step-by-step visual workflows.

Video Analytics

Transform CCTV and camera feeds into business data. Footfall analytics, heatmaps, occupancy monitoring, behavior analysis.

Edge AI & Embedded Vision

Optimized models for edge hardware — NVIDIA Jetson, Coral, custom SBCs. On-device inference with no cloud dependency.

Custom Model Development

Training and fine-tuning vision models for your specific use case. Data collection strategy, annotation, training pipelines, deployment.

Cloud & On-Premise Deployment

Scalable vision pipelines on your infrastructure or ours. GPU-accelerated processing, real-time streaming, API integration.

Portfolio

Systems We've Engineered

Real systems we've built, shipped, and scaled. Each one started as a problem — here's what we delivered.

Why Us

Engineering, Not Consulting

We don't make slide decks about AI. We write the code, train the models, build the hardware, and ship production systems.

E2E

End-to-End

From data collection and model training to edge deployment and monitoring.

Edge

Edge to Cloud

We deploy wherever your system needs to run — embedded devices, on-premise servers, or cloud.

Prod

Production-Grade

Not demos. Real systems running 24/7 in harsh conditions, handling real workloads.

Full

Full Stack Vision

Optics, embedded software, ML models, APIs, dashboards — one team, one codebase.

FAQ

Common Questions

What is computer vision engineering?

Computer vision engineering is the process of building software systems that extract meaningful information from images and video. This includes detecting and tracking objects, recognizing faces, reading text, measuring distances, and understanding scenes — then turning those observations into actions like alerts, analytics, or physical controls.

How much does a custom CV system cost?

It depends on complexity. A prototype on your data typically takes 4-6 weeks and costs $5K-15K. A production-ready system with edge deployment, dashboards, and ongoing support ranges from $15K-50K. We scope every project before quoting — no surprises.

How long does it take to deploy a CV system?

A working prototype on your actual data and environment takes 4-6 weeks. Production hardening (error handling, monitoring, edge cases, integration) adds another 8-12 weeks. Total concept-to-deployed system is typically 3-5 months.

Do you work with existing cameras or do we need new hardware?

We work with whatever you have. Most projects use existing CCTV or IP cameras. If the camera quality or placement isn't suitable for your use case, we'll recommend specific hardware — but we always evaluate your existing setup first.

What industries do you work with?

We've shipped CV systems for retail (store analytics), transit (passenger counting), and industrial applications. The engineering principles are the same across industries — detection, tracking, classification, and action. If your problem involves cameras and data, we can likely help.

Contact

Let's Build Something

Have a computer vision challenge? We'll help you scope it, architect it, and ship it. No fluff — just engineering.

hello@thohtdelta.in
+91 99445 31155
74, Thadicombu Road,
Dindigul 624001