(MENAFN- PR Newswire)
Technology entrepreneur, Tony Nicol, launches video analytics start-up VisualCortex, making video insights accessible, actionable and valuable for all video-rich industries and business functions
SYDNEY and NEW YORK, June 23, 2022 /PRNewswire/ -- VisualCortex – the cloud-based Video Intelligence Platform, connecting computer vision's potential to real-world business outcomes – has officially launched today worldwide. VisualCortex is headquartered in Sydney, Australia.
Watch the VisualCortex overview video here: visualcortex.com
Unlike camera-side or point solutions – which typically focus on one video analytics challenge per deployment – VisualCortex delivers a highly performant enterprise-grade platform to facilitate any real-time or historical video analytics use case. Built to work with both streaming and offline footage, the VisualCortex platform applies machine learning models to video content, enabling organizations to produce analyzable data streams about defined objects and actions. Insights from that data can then be embedded straight into customers' traditional data infrastructure.
VisualCortex is backed by its Chairman and Co-Founder, Tony Nicol, who sold Australia's largest data-focused cloud consultancy, Servian, to US-based professional services company, Cognizant, in January 2021. Nicol founded Servian in 2008, where he remained CEO of the 900-person-strong enterprise transformation business until June 2021.
Utilizing experiences building some of the largest and most complex enterprise data platforms, Nicol said that VisualCortex's purpose was to enable any complex computer vision use case without compromising robustness and reliability.
'We built VisualCortex to overcome the limitations of single-use-case solutions, without sacrificing the stability, security, scalability, flexibility and governance that naturally occurs in homegrown point solutions,' said Nicol.
Commenting on VisualCortex's launch, Nicol said the company's mission was to enable any organization to become a vision aware enterprise, allowing them to solve commercially valuable challenges with video-based insights at scale.
'For the first time, we're making video data truly actionable throughout the enterprise,' said Nicol. 'Up until now, computer vision technology has struggled to make commercial sense and generate impactful business value. They've also been prohibitively hard-to-use and expensive in terms of cost and time-to-value, hampering the ability to be harnessed by anyone other than machine learning experts.
'VisualCortex's Video Intelligence Platform removes those barriers and provides an enterprise-grade approach and control to computer vision initiatives,' said Nicol. 'We're enabling any business unit to quickly and easily build and implement a video analytics use case to facilitate future ways of working, today – no matter the nature of your business, hardware or video content.'
CEO and Co-Founder, Patrick Elliott, said that VisualCortex was enabling organizations – regardless of the industry or business function – to produce analyzable video-based data streams about any aspect of their operations.
'VisualCortex is making video intelligence accessible and valuable for all video-rich industries and business functions,' said Elliott. 'Our Video Intelligence Platform provides the AI smarts, governance and stability. Clients just need to bring their standard infrastructure, commodity hardware and video – from any stream, camera or repository. With VisualCortex, you can run multiple machine learning models, for any number of video sources, across your existing cameras and video feeds.
'We're enabling anyone to quickly connect machine learning models with a production-ready cloud-based environment, transforming video assets into analyzable and actionable streams of data at scale. VisualCortex empowers technical users, like software developers and data scientists, as well as business users – from marketing executives and business analysts, to operations teams for OHS, security, car parks and more.'
Elliott added that VisualCortex had already signed a number of commercial agreements and that specific partner and customer announcements would be made in the near future.
'We've encountered strong demand for VisualCortex's approach to video analytics,' said Elliott. 'We're set to announce a number of partnerships in the short-term with software and hardware vendors, service providers and the public sector. In terms of customers, we've signed NDAs – and are in various stages of conducting pilots and working on long-term agreements – with organizations in transport, retail and commercial real estate. Stay tuned for further exciting announcements regarding customer success and our growing partner ecosystem.'
CTO and Co-Founder, Ben Evans, said that VisualCortex facilitated both real-time action and strategic analysis for any video analytics use case.
'We're enabling organizations to easily define, detect, track and produce tangible analytics about the objects and incidents that matter to them – from vehicle and number plate recognition, to people counting and dwell analysis,' said Evans. 'Customers can use those analytical insights operationally, triggering real-time alerts – and pushing the video-based data into operational systems – to prompt immediate action. Users can also analyze the data derived from their video assets with in-platform reports or pipe it into third-party databases. Combining video data streams with traditional data sources can unearth powerful integrated insights.'
Evans added that the VisualCortex Model Store would also play a significant role in helping more organizations realize faster, stronger returns on their video analytics initiatives.
'We know that building, training and maintaining reliable machine learning models is resource intensive,' said Evans. 'The VisualCortex Model Store provides a secure digital marketplace for customers, partners and independent machine learning experts to share – and generate revenue from – quality controlled computer vision models .
'At its core, the Model Store provides models-as-a-service. Anyone with appropriate security access can upload video footage into the VisualCortex platform, then define events to track, leveraging models from the Model Store, and produce data for analysis.'
VisualCortex is committed to building, training and maintaining a growing set of machine learning models, available out-of-the-box with a VisualCortex subscription license.
Browse the VisualCortex Model Store here: visualcortex.com/model-store
The VisualCortex Video Intelligence Platform can be securely deployed in multiple ways to meet individual organization's needs: As a fully-managed service in the cloud, on customers' private cloud, via public cloud providers, on-premise, at the edge, or via a hybrid deployment model. VisualCortex is generally available to the market from Friday 24th June, 2022.
VisualCortex is making video data actionable in the enterprise. As the world's best Video Intelligence Platform, VisualCortex provides the stability and scalability to productionize computer vision technology for the first time. Unlike camera-side or point solutions, VisualCortex can be used for any video analytics use case in any industry. VisualCortex's production-ready cloud-based environment transforms video assets into analyzable streams of data at scale.
The VisualCortex platform delivers the artificial intelligence smarts, governance and usability, enabling organizations to connect any number of video streams, repositories and use existing commodity hardware. An intuitive user interface, out-of-the-box reporting, range of configurations and integrations empower non-technical people to produce, analyze and act on insights derived from computer vision throughout the enterprise. Organizations can easily combine these AI-generated video insights with other data sources and systems to facilitate both real-time operations and strategic analysis. The VisualCortex Model Store also provides a secure marketplace for customers, partners and independent machine learning experts to share quality controlled computer vision models.
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