Classification and Tagging
Sort images into your own categories and apply consistent tags automatically, from product types to defect classes.
Custom Computer Vision
Computer vision that classifies, detects, and extracts structured information from images, trained on your own data and categories. Built for retail, security, manufacturing, and logistics teams, not a certified diagnostic or clinical imaging product.
- 0+Years Engineering Excellence
- 0+Projects Delivered
- 0%Successful Go-Live
- 0 HrsResponse Time
aarvexa · vision-lab / shelf_0412.jpg analysing
7 objects found confidence 0.96
- Detect
- Classify
- Extract
{"objects": 7,"classes": ["bottle","box","can"],"top_confidence": 0.99,"mask": "segmented",}
Capabilities
Four core capabilities that turn raw images into labelled, searchable, structured data.
Object Detection and Pattern Recognition
Locate and count objects, spot patterns and flag anomalies inside a frame, with bounding boxes and confidence scores.
Feature Extraction From Complex Images
Pull structured fields such as text, attributes and measurements out of cluttered or high-resolution images into clean data.
Custom Model Training
Models trained and tuned on your data and labels, so accuracy reflects your environment rather than generic benchmarks.
Industries
One computer-vision approach, tuned to the images and decisions of each industry.
sku · shelf gap
Retail and e-commerce
Auto-tag catalogues, detect shelf gaps and power visual search across product imagery.
person 0.97
Security and surveillance
Spot people, vehicles and unusual activity in camera feeds and raise alerts in real time.
defect 0.93
Manufacturing and industrial
Inspect parts for defects and verify assembly and safety gear on the line.
parcel ×24
Logistics and supply chain
Read labels, count parcels and check pallets and loads as they move.
triage · sort
Healthcare operations
Support operational imaging workflows such as sorting and quality checks. Not a diagnostic product.
Under The Hood
The model families we combine, and tune on your data, to deliver production-grade vision.
Convolutional Neural Networks (CNNs)
Layered filters learn edges, textures and shapes, the proven backbone for classification and detection.
Transformer-Based Vision Models
Attention across image patches captures global context, useful for complex scenes and fine detail.
Multimodal AI Pipelines
Images are combined with text and metadata so outputs are richer and easier to act on.
Custom-Trained Vision Models
Fine-tuned on your labelled data and validated on your own edge cases before launch.
Vision API Comparison
Custom-Built (Aarvexa AI)General-Purpose Vision APIs
Category coverageYour exact categories and labelsFixed, pre-defined label sets
Accuracy on your dataTuned and validated on your own imagesStrong on common objects, weaker on niche cases
Domain specificityBuilt around your domain and edge casesGeneral-purpose with limited domain context
Data ownershipYou own the model, data and outputsImages processed on a shared service; terms vary
DeploymentCloud, on-premise or edgeCloud API only
More Solutions
FAQ
Straight answers on image analysis models, accuracy, custom vs. generic vision APIs, integration and pricing.
It is computer vision that classifies images, detects and counts objects, and extracts structured data from them, using models trained on your own images and categories.
Classification and tagging, object detection and pattern recognition, feature extraction from complex images, and fully custom model training for your use case.
No. The software is built for retail, security, manufacturing and logistics workflows. It is not a certified diagnostic or clinical imaging product.
Retail and e-commerce, security and surveillance, manufacturing and industrial, logistics and supply chain, and healthcare operations such as sorting and quality checks.
Share the problem and a sample of images. We scope it in discovery, build a pilot model on your data and agree success metrics before scaling.