Recognition as a Service – RaaS
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[Fast-Track product] The Recognition as a Service (RaaS) platform from Deep Recognition provides customers with an easy way to consume Recognition Technologies (e.g. AI and Decision Support) from Service Providers, Integrators and Telecommunication Companies. Recognition Technologies include vision-based Artificial Intelligence, Satellite Imagery and IoT sensors. The biggest inhibitors to widespread adoption of AI are ease of use, deployment, scalability and the privacy and ethics concerns.
  • Overview
  • Integrations
  • Showroom
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Why RaaS Deep Recognition?

  • Recognition Technologies which incorporate vision-based artificial intelligence, satellite imagery and IoT sensors are one of the major components of the 4th industrial revolution/Industry 4.0 program.
  • With a forecasted Global Market for AI in Computer Vision expected to reach $73.7 Billion by 2027, this is a fast growing market and area.
  • Video is a significant differentiator for 5G and so it will help to monetize and optimize 5G networks.
  • Recognition Technologies solve business problems and are typically embedded in our customers business processes therefore making them sticky.

RaaS Deep Recognition customer persona

Top segments by size (# employees)
0 employees
1 – 4 employees
Small SMBs
5 – 9 employees
Medium SMBs
10 – 49 employees
Large SMBs
50 – 249 employees
249 – 999 employees
999+ employees
Top segments by vertical
Law Enforcement/Security
Primary Industry/Agriculture
Segment 4
Segment 5
Segment 6
Not targeted customer segment
Secondary customer segment
Sweet spot


  • Expansion of AI and Machine Learning types of applications.
  • Better return from existing infrastructure investments with easier management.
  • Improved ease of use for insights and other teams looking to capitalize on vision and sensor data.


  • Better use of existing security and sensor deployments.
  • New or better business insights e.g. Safety Equipment Recognition, People Counting, Livestock/Fish Assessment/Tracking.
  • Greater efficiency and ease of managing cameras and IoT devices and feeds (e.g. speech) from existing installations.

Pain points

  • Lack of flexibility and scalability from point solutions currently deployed or being offered for projects.
  • Legacy equipment prevents scaling out feeds to new services without significant investment or refresh.
  • Lack of ease of use with ability to access multiple AI models in a consumption style service.
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