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Vision-based Analytics That Delivers Business Insights
Our computer vision developers integrates advanced machine learning and deep neural networks to analyze, classify, segment and understand visual content with precision and scale.
Our Computer Vision Development Services
Using advanced AI and deep learning techniques, we build intelligent visual recognition systems tailored to your use case, whether it’s real-time analytics, quality inspection, or customer experience optimization.
Image Classification
Our models deliver accurate and consistent results at scale as they automatically categorize images based on predefined labels.
Object Detection
Our object detection models can identify and localize multiple objects within an image or video stream in real time.
Object Tagging
We implement automated labeling systems that tag objects within images or video with metadata for downstream tasks such as model training, indexing, or content analysis.
Semantic Segmentation
Semantic segmentation models assign class labels to every pixel in an image, offering deep contextual understanding of scenes.
Pose Estimation
Our pose estimation systems track key body or object points to detect postures, gestures, and spatial orientation in 2D and 3D.
The Outcome?
Computer Vision Models That We Use
We have the expertise in using state-of-the-art computer vision models that are suitable for your specific business needs, performance goals, and deployment environments.
YOLO
Vision Transformers (ViT)
ResNet (Residual Networks)
VGG (Visual Geometry Group) Networks
Segment Anything Model (SAM)
OpenCV
Google Vision AI
Microsoft Azure AI Vision
Our Success through Numbers
Turning Language into Intelligence
50+
AI Projects Delivered Across Industries
10+
Generative AI Models Mastered
20+
Global Clients Empowered
5x
Faster Deployment Expertise
99.9%
Client Satisfaction Rate
3
Served with Scalable AI Services
Trusted by 2,000+ Brands
Real Stories, Real Impact
Read our case studies, which showcase our experience and strategy for implementing different Gen AI models into business workflows successfully.
AI-Powered Football
Match Analysis System
Caregiving chatbot
for Alzheimer's patients
RAG Chatbot for business
analytics blogs
Hire On-Demand Dedicated Developers
At Amenity Tech, we have a pre-vetted pool of talented developers with expertise and hands-on
experience in a range of technologies.
React
Developer
Create dynamic web apps using reusable components with React.
Angular
Developer
Develop structured, scalable front-end apps with Angular.
Vue
Developer
Lightweight, fast, and flexible interfaces built with Vue.js.
JavaScript
Developer
Create interactive, responsive websites using core JavaScript skills.
HTML/CSS
Developer
Design clean, responsive layouts using HTML5 and CSS3.
Python
Build fast and flexible apps or data tools with Python
Laravel
Develop modern web apps using Laravel’s PHP framework.
Node
Create real-time, high-performance apps with Node.js.
Django
Secure, scalable back-ends built with Django and Python.
iOS
Build sleek iOS apps with Swift and Apple-native tools.
Android
Create reliable Android apps for all devices and versions.
Flutter
Cross-platform apps from a single codebase with Flutter.
React Native
Build native-like mobile apps with shared React code.
AI Dev
Integrate smart, AI-powered features into your app.
ChatGPT
Deploy AI chat solutions using OpenAI’s ChatGPT.
PyTorch
Design and train deep learning models with PyTorch.
Prompt Engineer
Optimize AI outputs with expert-crafted prompts.
Data Analyst
Extract insights from complex data with AI and ML.
Data Scientist
Visualize and interpret data to guide business decisions.
Data Engineer
Build scalable pipelines and manage data infrastructure.
Testimonials
Client Stories
Read what our clients have to say about the Amenity Tech partnership and the benefits they have received from our innovative Gen AI solutions.
The Amenity Team is a standout group of professionals in AI chatbot development, consistently delivering bug-free, expert-level code. Their strong communication skills and seamless collaboration make working with them a breeze. With deep expertise in AI chatbot projects using LLMs and ChatGPT, including web and WhatsApp platforms, you’re in the best hands!
Ganesh Tangella
have the honor and privilege of working with Amenity on many projects these last 6 months. Amenity has demonstrated immense and exceptional capabilities in developing robust custom computer-vision-learning algorithms, Deep Neural Networks, and Convolutional Neural Networks, and has advanced our R&D exponentially! Trust can never be more valuable and critical for any startup, especially when building and developing partnerships!
I must thank Amenity for opening our eyes and expanding our AI capabilities beyond measure!
Charles B. Moss II
Excellent work, Great communication throughout the project. Took time to understand the task then provided an excellent out come.
Hanif-jan-mohamed
Dealing with amenity such good experience on our AI project. Very co operative team with polite nature.
Aarohi Kaur
Excellent work, Great communication throughout the project. Amenity delivered one of our Most Difficult NLP Based project.
Daniel Sommer
Excellent Work Experience with Amenity, completed incredible IoT work for our project.
Harnam Singh Thakur
Dealing with Amenity such Good Experience on Project. They work are Accurate According to Requirements Also Team is very co operative and Trustworthy.
Naif
Frequently Asked Questions
What is computer vision, and how does it work?
Computer Vision uses deep learning and image processing algorithms to interpret and analyze visual data, turning images and videos into actionable information.
Can computer vision work in real time?
Yes. Modern CV models are optimized for real-time inference using GPU acceleration or on-device deployment (edge/mobile), enabling instant detection and response.
How accurate are computer vision models?
Accuracy depends on the model architecture (e.g., YOLO, Faster R‑CNN, U-Net), dataset quality, and domain specificity, making domain-focused training vital for high performance.
How do you train a computer vision model?
The process involves collecting and labeling data, choosing an appropriate architecture, training the model, validating performance, and deploying it via cloud, edge, or mobile platforms.
Can computer vision handle multiple environments or lighting conditions?
Yes, when properly trained with diverse and augmented datasets to account for variations in lighting, angles, and backgrounds.
Will CV solutions integrate with my existing systems?
Absolutely. We offer flexible deployment options including REST APIs, microservices, edge SDKs, and integrations with cloud platforms like AWS, Azure, and GCP.