Recently, ManageEngine, the IT enterprise wing of Zoho, confirmed that it would be investing $10 million in NVIDIA, AMD and Intel, aiming to unleash generative AI offerings for its customers.
Following this development, Zoho is now collaborating with Intel to optimise and accelerate its video AI workloads for users. This will empower efficiency, reduce total cost of ownership (TCO), and optimise performance.
Interestingly, the Intel collaboration will most likely enhance Zoho’s existing team communication platform Cliq, which allows users to interact over audio and video calls. Further, last October, the company unveiled its smart conference rooms solution on Cliq, that allows customising room devices such as TV screens for taking video conferences.
Why Intel?
Santhosh Viswanathan, the vice president and MD at Intel, posted that the company has collaborated with Zoho to leverage Intel® Xeon® processors and the OpenVINO™ toolkit to empower its Video AI Assistant.
Source: LinkedIn
Zoho said it is working closely with Intel to accelerate key AI workloads, including CCTV surveillance video analytics and optical character recognition (OCR). Leveraging Intel’s expertise in hardware and software optimisation, Zoho achieved significant improvements in both performance and cost-effectiveness across these vital AI applications.
Further, it said that it is using hardware accelerators, which include Intel® Xeon® Scalable processors and Intel® Distribution of OpenVINO™ toolkit to help organisations achieve faster processing speeds, less delay, and better scalability. These tools are crucial for quick decision-making and real-time processing in tasks like surveillance, digitising documents, and analysing text enabling organisations to attain an optimal total cost of ownership (TCO).
Optimising Video Analytics to Manage AI Workloads
The team said that their solution revolves around the multifaceted nature of video analytics using CCTV surveillance cameras. This necessitates the implementation of sophisticated algorithms adept at various tasks, including enhancing recording quality, detecting objects, and tracking individuals.
Likewise, Tesseract OCR, an OCR engine, plays a pivotal role in digitising text from scanned images, video frames, or documents while providing robust support for multiple global languages. The team said that Camera Image Quality Analyzer is a key tool that helps identify cameras with suboptimal recording quality due to environmental factors such as dust, fog, or spider webs.
Post this, the system tickets the issue and reports for tracking and resolution. Moreover, to optimise operational efficiency and sustainability, AI video assistants facilitate counting functionality. In large spaces where sensor sensitivity may be reduced, the Video AI Assistant can count people using the camera feed and adjust the air conditioning accordingly.
In terms of text digitisation, with Intel® Xeon® features and associated software optimisations, Zoho’s AI Assistant utilises Tesseract OCR technology to convert text into the digital format. This enables the AI assistant to generate relevant search terms, facilitating document management and streamlining information retrieval processes.
Impacting the Real World
When implemented in real-world scenarios, harnessing the capabilities provided by the 4th Gen Intel® Xeon® processors, Zoho has experienced significant performance improvements for specific AI workloads. Through a benchmarking process, the camera Image Quality Analyzer scans all the cameras on the premises, identifying the wrong one and taking it to the respective teams, thereby reducing manual checks and errors.
Shailesh Kumar Davey, co-founder of ManageEngine, emphasised, “At Zoho, we collaborate with leading technology industry vendors in improving the TCO of our infrastructure and solutions to ensure we offer the best value to our customers.”
Zoho recognised the necessity for a robust platform to meet the high-performance requirements of video AI assistants. Hence, collaborating with Intel provides a comprehensive approach that serves as an ideal solution for accelerating AI workloads and overcoming challenges across various applications.
