Technology

Our engine is based on cutting-edge artificial intelligence and machine learning technologies.

Core Technology

Vision Genius is based on advance technology of Artificial Intelligence, Machine Learning and Computer Vision algorithms. We have developed set of Deep Learning services that we used to extract meta data from videos, By using GPU along with a CPU help us to decrease processing time, enabling real-time video analytics. Vision Genius is compatible with any video recording devices (CCTV/NVR/DVR) or even with already recorded videos with no restraint on mounting height, angle and position which makes it flexible and easy to install with minimal repair and maintenance.

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High Accuracy

we analyze the complete visual detail of every video frame we get and achieve high accuracy numbers that the market demands. Our system can work smoothly in wide range of diverse conditions.

Multiplatform

No matter where you want to apply AI, Vision Genius has you covered. Our System can be accessible via Cloud, On-Premise Server, and as Edge devices.

Camera Agnostic

Our solutions are camera-agnostic and have no setbacks for any particular make and model of camera and smoothly works with any camera provider or camera-enabled device.

Real Time

We can analyzes both live and recorded videos and by using GPU-based machines with our highly optimized deep learning algorithms we can produce results in real time.

system architecture

Our architecture is specifically designed to facilitate wide range of products and services across multiple industries that broaden our scope and overall framework for video analytics.

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Edge Computing

Designed to run in resource constrained environments, Our Edge devices are faster, extremely power and memory-efficient and virtually hardware agnostic.

Pros Cons
  • Cost effective
  • Compact and Standalone Processing
  • Easy installation
  • Offline processing
  • Support limited models
  • Relatively slow computational processing
  • Limited number of camera per device

Suitable For: Small-Medium Size Shop and Industry, Home Users, Researchers, Data Scientists, Small Scale Surveillance and Monitoring

Why Use Edge Device ?

Edge is suitable for scenarios where multi-model processing are not required and a single model meets your requirements. e.g. Alert generation due to detected weapons without the complete security solution i.e. tracking and post-processing.

On-premise Server

Vision Genius can be deployed on local servers to comply with high-security environments and air-gaped systems running within your organization.

Pros Cons
  • Maintain data privacy and control
  • Integrate with whole network of camera
  • Offline processing
  • Cost-effective option for long-term processing
  • High upfront cost due to hardware
  • Maintenance and management cost

Suitable For: Enterprise Level Business, Malls, Governments, Law Enforcement Agencies, High-End Surveillance and Monitoring

Why Use On-premise Server ?

Processing is handled at your facility where the data is collected from your cameras. On-premise servers are ideal for cases where internet or cellular connections are spotty, bandwidth is constrained or data security will always be paramount (i.e. offshore oil platforms, mines, border security etc).

Cloud Computing

Running application on cloud server eliminates the need to have a local server. You can get access to the results from anywhere in the world, having only access to the Internet.

Pros Cons
  • No on-site hardware
  • Pay as you use
  • High computational power
  • Required high speed internet
  • Downtime may occur
  • Uneconomical for very high volume of data

Suitable For: Processing Fixed Length Videos, Brand Outlets, Consultancy firm, Researchers and Data Scientists.

Why Use Cloud Computing ?

Cloud servers are highly customizable and eliminates the need for local infrastructure where running and maintenance cost can vastly vary. It is suitable for analyzing segmented videos where limited duration videos need to be processed in short time. e.g. limited duration of traffic count of a road section.

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