Actionable business insights from streaming data

On the best-in-class real-time analytics platform with AI+ acceleration using FPGAs from edge to cloud 

VAS: VIDEO ANALYTICS SOLUTION

Introducing Megh’s real-time Video Analytics Solution for system integrators (SI) and independent software vendors (ISV):

  • Targets end users in retail, manufacturing, logistics, security, and other segments
  • Accelerates various use cases to deliver the best performance efficiencies
  • Includes the highest performing deep learning engine for object detection and image classification
  • Supports worker safety to help businesses reopen and manage COVID-19 response

  • Enhance worker safety

Monitor social distancing, body temperature, and PPE compliance

  • Manage inventory

Decrease inventory distorting due to misplacement

  • Control access

Enhance access control systems with smart surveillance

  • Prevent fraud

Prevent loss from mis-scans and theft

Capture business intelligence from streaming video

Turn any IP camera into a smart camera and add AI-enabled analytics

Deploy from edge to cloud

Enable real-time analytics at the edge, on premises, or private or public cloud

  • Highest performing

  • FPGAs deliver on average 5x greater throughput than GPUs for best price/channel

  • Lowest deterministic latency processing to support real-time use cases

  • Most scalable

  • Scale-up to scale-out configuration for small to large systems

  • Easily deployable deep learning models to support simple to complex use cases

  • Most flexible

  • Different deployment options for edge-to-cloud configurations

  • Standalone or integrated with existing VMS systems for advanced features

  • Best vendor choice

  • OEM platforms (Dell, HPE, Lenovo, IBM)

  • FPGAs (Intel, Xilinx)

  • Cloud hosts (AWS, Azure)

Built on our best-of-class real-time analytics platform

VAS brings the benefits of the Megh Platform to system integrators (SI) and independent software vendors (ISV) by accelerating their video analytics products

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