Meet this Artificial Intelligence startup ‘VisualCortex’, helping bring video data to the enterprise with its Video Intelligence Platform

It has always been challenging to efficiently produce insights that solve real-world business challenges at scale. Moreover, video is today’s most incredible data mining opportunity – which is notoriously difficult to extract analyzable and valuable insights from, even with emerging computer vision technologies. 

The world’s largest underutilized pool of potential insights, video now accounts for over 80% of web traffic and has increased 15-fold since 2017. The fact that an estimated 80% of all data is unstructured underscores the immense value that unstructured data analysis can unleash, such as computer vision’s capacity to analyze individual image frames in video to programmatically detect specific objects and actions. Computer vision use cases – also often referred to as video analytics – are diverse: From people counting and dwell-time analysis to determine customer exposure and engagement in retail settings; to license plate recognition or vehicle detection and tracking to better-understand road usage. Often the result of back-of-house R&D projects, or basic Proof-of-Concept consulting engagements, computer vision technology has typically struggled to satisfy the demands of commercial deployments for a number of key reasons. Traditionally, it has: Struggled to scale technologically and financially; Required expensive bespoke hardware; Been unable to address multiple use cases per deployment; Prevented non-technical audiences from accessing insights due to its complexity; and has struggled to produce detection rates and confidence scores with commercially dependable accuracy. 

VisualCortex is a computer vision start-up aiming to change all that, and bring computer vision into the mainstream. 

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“Traditionally, computer vision solutions have been built by and for data scientists,” said VisualCortex CEO and CoFounder, Patrick Elliott. “We see enormous potential to democratize access to video analytics throughout the enterprise. We want to empower non-technical people to understand and act on the insights derived from computer vision. The goal is to enable our customers to realize value across all parts of their organization – from business analysts and machine learning experts, through to operations and security teams, sales and marketing, and the c-suite.”

According to VisualCortex, its Video Intelligence Platform “offers the stability, scalability, and flexibility” needed to run multiple machine learning models, across any number of video sources – from live streams, Video Management Systems (VMSs), cameras, or footage repositories – within one production-ready computer vision environment. Multiple implementation options also allow VisualCortex clients to deploy the platform in a manner that aligns to defined use cases and security protocols – from on-premise and on-the-edge, to public and private clouds, or a hybrid approach.

“Unlike camera-side or point solutions, VisualCortex can be used for any video analytics use case in any industry,” said Elliott. “VisualCortex’s platform approach enables clients to run multiple machine learning models on the same footage and hardware, meaning they can produce video analytics about multiple use cases quickly and inexpensively.”

In particular, VisualCortex focuses on turning video assets into actionable data. That is, producing metadata about defined objects (people or vehicles, for example) and actions (such as traffic entering a specific area or time spent in certain locations). The data generated by VisualCortex can be used to trigger immediate action (such as real-time alerts within the platform or third-party systems) and historical analysis via integrated reports and dashboards. 

“Our purpose is to transform video assets into analyzable streams of data, reliably delivering disruptive insights to everyday business decision-makers,” said Elliott. “We want organizations to be able to view and harness video-based data streams as they would any other data source, which they can then draw upon for enterprise reporting.

“Ultimately, we see computer vision’s usefulness being the ability to provide a new data stream from video content. When customers combine that new incremental data with their traditional data, it really allows them to get a broader, much deeper understanding of their business. It’s for these reasons that we don’t see video analytics as a standalone service offering. We see it as part of the instrumental data backbone of an organization.”

Additionally, the VisualCortex Model Store provides a secure marketplace for customers, partners, and independent machine learning experts to share quality-controlled computer vision models.

“Alongside deployability, we know that building and maintaining reliable machine learning models is another major obstacle for organizations attempting to deliver video analytics programs,” said Elliott. “The VisualCortex Model Store addresses that challenge, helping customers generate insights from their video content fast and obtain tangible ROI as quickly as possible.”

To expand its reach and leverage industry-specific knowledge, VisualCortex uses a channel-based go-to-market approach.  

“We’ve done this because we fully appreciate the data, integrations and deployment work required to make customers successful with sophisticated AI-based technologies, such as video analytics,” said Elliott. 

According to data from a Gartner survey, a lack of skills was the biggest obstacle faced by organizations working on AI projects (56%). To help both its customers and internal development team bridge that gap, VisualCortex has built and announced a number of significant partnerships.

Servian, Australia’s leading data consulting firm, recently struck a referral and services agreement with the Video Intelligence Platform. Additionally, VisualCortex is collaborating with the University of Wollongong to share model-building capabilities and promote industry-research collaboration. From a vendor perspective, VisualCortex has also announced two technology alliances of note: The first is with Firmus – creators of computational cloud, Supercloud – to make large-scale video analytics environmentally sustainable and commercially feasible for customers. The second is with i-PRO, a pioneer in intelligent cameras, network video recordings, and edge devices. The partnership allows clients to combine VisualCortex with leading AI-enabled devices, enabling them to produce the best video-based insights possible.

VisualCortex has also joined the Google Cloud Partner Advantage Program and holds Premier status in the NVIDIA Inception partner program. Both initiatives aim to hasten the development of cutting-edge artificial intelligence and data science start-ups.

VisualCortex is backed by its Chairman and Co-Founder, Tony Nicol, a well-known data and technology entrepreneur based in Australia.

Nicol said that VisualCortex was conceived to enable complex computer vision use cases; 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.

“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.”

In the upcoming year, VisualCortex hopes to establish more successful alliances like the one with Servian. In addition to distributors and resellers, it seeks to form additional technology partnerships with security firms, VMS providers, and university researchers.

In April 2023, the company intends to expand into North America. In September 2023, it hopes to do the same in Europe via Ireland. 

“We’ve already begun conversations with potential partners around the world, including New Zealand, Belgium, Canada, USA, Saudi Arabia and more,” said Elliott. “We’ll expand the list in 2023 as we scale out further, carefully balancing that growth with our primary objective – to make our foundational customers enormously successful.”

VisualCortex early adopters come from the commercial real estate, retail, and transportation sectors. In addition to building more enterprise-grade solutions for specific industry verticals, VisualCortex also plans to release a SaaS offering to serve both businesses and mass consumer audiences.

For a demonstration of the VisualCortex platform or to submit an inquiry, organizations should get in touch via the contact form on the VisualCortex website:

To watch a short overview video about the VisualCortex platform, go to



Note: Thanks to VisualCortex team for the thought leadership/ Educational article above. VisualCortex has supported and sponsored this Content.

Asif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.

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