AI & Automation

Computer Vision Solutions

AI That Sees and Understands

Deploy intelligent visual systems that detect defects, recognize objects, analyze video, and automate inspection tasks. Our computer vision solutions operate at scale with accuracy that exceeds human performance.

100+
Vision Models Deployed
99%+
Detection Accuracy
5M+
Images Processed/Day
12+
Industries Served

What is Computer Vision?

Teaching machines to see and understand

Computer vision enables machines to interpret and act on visual information from images, videos, and cameras. Our solutions go far beyond simple image recognition-we build systems that detect specific objects, measure dimensions, identify defects, track movement, and extract meaning from visual data.

Applications span every industry: manufacturing quality inspection that catches defects human eyes miss, retail shelf monitoring that ensures product availability, security systems that detect anomalies, medical imaging that aids diagnosis, and agriculture solutions that monitor crop health.

We develop custom models trained on your specific visual data, achieving accuracy levels impossible with generic pre-trained solutions. Whether you need to process thousands of images per second or deploy models on edge devices in remote locations, we architect solutions that perform reliably in production.

Key Metrics

99%+ mAP
Detection Accuracy
Mean average precision on test data
< 50ms
Inference Speed
Per image on standard hardware
< 0.1%
False Positive Rate
Critical for production reliability
100+ FPS
Throughput
Images processed per second

Why Choose DevSimplex for Computer Vision?

Production-proven visual AI systems

We have deployed over 100 computer vision models processing millions of images daily. Our systems run in manufacturing plants, retail stores, warehouses, and hospitals-environments where reliability and accuracy are not optional.

Our approach prioritizes production readiness. Many teams build impressive demos that fail in real-world conditions. We engineer for edge cases, lighting variations, camera angles, and the countless variables that cause models to fail. Extensive testing on real-world data ensures our models perform as expected when deployed.

We optimize for your deployment environment. Some applications need cloud-scale processing; others require edge inference on constrained devices. We select and optimize architectures-from efficient MobileNets to powerful Vision Transformers-based on your latency, accuracy, and infrastructure requirements.

Continuous improvement is built-in. We implement feedback loops that capture model errors, monitor accuracy over time, and trigger retraining when performance degrades. Your computer vision system gets smarter with use.

Requirements

What you need to get started

Training Images

required

Labeled examples of what the model should detect, classify, or analyze.

Clear Visual Task

required

Well-defined objective: what should the model detect, measure, or classify?

Camera/Image Specifications

required

Details about image sources, resolution, lighting conditions.

Deployment Environment

recommended

Where models will run: cloud, on-premise servers, or edge devices.

Performance Requirements

recommended

Latency, throughput, and accuracy thresholds for production.

Common Challenges We Solve

Problems we help you avoid

Limited Training Data

Impact: Deep learning models require large datasets that may not exist for specialized applications.
Our Solution: Data augmentation, synthetic data generation, and transfer learning from pre-trained models maximize accuracy even with limited samples.

Variable Lighting Conditions

Impact: Models trained in controlled conditions fail when lighting changes.
Our Solution: Training on diverse lighting scenarios, image preprocessing, and robust feature engineering ensure consistent performance across conditions.

Real-Time Performance

Impact: Production systems often require instant results that naive implementations cannot achieve.
Our Solution: Model optimization, GPU acceleration, batched inference, and architecture selection balance accuracy with speed requirements.

Edge Deployment Constraints

Impact: Edge devices have limited compute, memory, and power for complex models.
Our Solution: Model compression, quantization, and efficient architectures deliver high accuracy within edge hardware constraints.

Your Dedicated Team

Who you'll be working with

Computer Vision Engineer

Develops detection and classification models, optimizes for production.

5+ years in CV/deep learning

ML Infrastructure Engineer

Builds training pipelines, manages GPU infrastructure, deploys models.

5+ years in ML systems

Data Annotation Lead

Manages labeling workflows, ensures annotation quality.

3+ years in ML data operations

Solutions Architect

Designs end-to-end system including cameras, networking, and integration.

8+ years in enterprise systems

How We Work Together

Typical engagements begin with a proof-of-concept (6-10 weeks) validating accuracy on your data, followed by production deployment and optimization.

Technology Stack

Modern tools and frameworks we use

PyTorch

Deep learning framework

YOLO / Detectron2

Object detection models

OpenCV

Image processing library

TensorRT

GPU inference optimization

NVIDIA Triton

Model serving at scale

Edge Devices

Jetson, Coral, custom hardware

Value of Computer Vision

Visual AI delivers operational and quality improvements.

100x faster
Inspection Speed
Immediate
99%+ catch rate
Defect Detection
Post-deployment
60-80%
Labor Cost Reduction
6 months
50% fewer escapes
Quality Improvement
3 months

Why We're Different

How we compare to alternatives

AspectOur ApproachTypical AlternativeYour Advantage
Model CustomizationTrained on your specific visual dataGeneric pre-trained models20-40% higher accuracy on your use case
Production ReadinessOptimized for real-world conditionsLab-quality demosReliable in variable conditions
Edge DeploymentOptimized for constrained devicesCloud-only or heavy modelsWorks where you need it
Ongoing SupportMonitoring and continuous improvementOne-time model deliveryAccuracy maintained over time

Ready to Get Started?

Let's discuss how we can help transform your business with computer vision solutions.