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‘Our Algorithm Enables Better Security, Better Living, and Better Business’: Andrei Telenkov, CEO of NtechLab


“As a leading facial recognition software company, we have established a worldwide network of trusted partners who implement our technology.”

NtechLab is a world-renowned expert in video analytics with more than 200,000 cameras installed across 20 countries. The company-built facial recognition software is connected with these cameras, making the world a safer and more comfortable place.

NtechLab algorithms are designed to help organisations and businesses make better decisions. The technology empowers governments and security services to act with greater speed and confidence and provides commercial companies with richer audience analytics.

NtechLab was founded in 2015 and is based in Moscow.

To highlight and further understand what NtechLab stands for and seeks to explore in this segment, I sat down with Andrei Telenkov, who serves as the company’s Chief Executive Officer.

Below is an excerpt.

Q. What’s your story? And tell us what motivated you to establish NtechLab?

Our founder, Artem Kukharenko, is the man behind NtechLab technology. He has specialised in neural networks since his time studying at Moscow State University where he authored several scientific works on the subject. In 2015, he developed a smartphone app that could specify a dog’s breed from a single photo called Magic Dog. Through a friend, he was introduced to businessman and passionate tech-investor Alexander Kabakov (who has also funded popular Russian online service YouDo, helping users to find people to help in solving everyday tasks and household chores). Kabakov suggested a pivotal change in the use of the technology behind Magic Dog — regarding creating an algorithm that could instead recognise human faces. Kabakov and his partners became first-round investors in NtechLab, and six months later the company’s product had beaten Google in the MegaFace Challenge, which pits facial recognition technologies head-to-head, organised by the University of Washington.

As for me personally, I joined the NtechLab in 2020. I was proud to become the CEO of a Russian company, which managed, without exaggeration, to achieve such tremendous successes abroad. For you to understand, I became CEO during the COVID-19 pandemic. I met with the employees, introduced myself, and the next day we switched to remote work. Now I can say with confidence that the company has successfully overcome this stage. We not only doubled our revenue but also managed to come up with an effective and working product that made it possible to ensure the safety of residents during the pandemic. The algorithm underlying NtechLab’s solutions have shown a great deal of effectiveness in identifying those who violate quarantine while tracking the social interactions between the potentially contagious and promptly notifying respective authorities.

Q. Tell me about the most difficult customer encounter you’ve experienced. And how did you handle it?

The Western Railway, one of the busiest railway networks in India, has commissioned video cameras featuring real-time face recognition technology. The system, developed by NtechLab, has been installed at 30 railway stations across the western Indian states of Gujarat and Maharashtra, and including the city of Mumbai. The camera system will be used on the busiest section of the network and ensure simultaneous recognition of up to 50 people in a single frame. It was a complex challenge, but we were able to successfully address it efficiently and on schedule.

Q. Trust is one of the most important currencies of leadership that requires authenticity and consistency to maintain. What’s your take on this?

As a leading facial recognition software company, we have established a worldwide network of trusted partners who implement our technology. In every country, we work in strict compliance with local laws and regulations. Besides, we thoroughly check and vet our clients’ compliance.

Our algorithm works with unique facial features which makes it impossible to restore the original image of the face — something that is of distinct importance in ensuring personal data protection. When a person passes a camera linked to a system running our software, the image of their face is transformed into a digital imprint consisting of several lines of code, and only this digital imprint is compared against a reference database of similar digital imprints. In other words, it is impossible to restore the original image of the face.

For commercial applications, our software collects anonymised data, limited to relative age and gender to generate consumer data and insight that enables businesses to improve brand communication and customer journeys. In cases where a business is required to react to certain people (for example, the VIP-scenario, where businesses use the system to recognise special guests to offer them VIP services), we expect businesses to receive written confirmation from individuals authorising the use of their images for such purposes.

Q. What are the different products NtechLab offers? And what can you tell us about their (products) association with FindFace?

NtechLab’s flagship product is FindFace Multi, a groundbreaking tool that accurately detects faces and silhouettes of people, and cars in real-time video streams.

Using an intelligent criteria-based facial search, the system can detect and track ‘persons of interest’ in a split second. It also has high levels of accuracy in detecting faces when they are partially covered with medical masks or clothes. Silhouette recognition enables the identification of people by the color of clothes and accessories. Vehicle recognition identifies the type of body, color, manufacturer, and model of a car. It works even if license plates, or part of the car, are not visible.

Q. In what industries are your clients? Can you provide us with one or two success stories describing the challenges your clients faced and how your solutions helped them overcome those challenges?

I would like to cite a major agreement between FESCO Transport Group and NtechLab, which is poised to create a landmark ‘smart’ shipping port at the Vladivostok Commercial Sea Port in Russia. NtechLab is providing a unified video analytics system to monitor labor and transport safety, based on a common biometric database created by the seaport. The technology delivers remote systems access and the ability to monitor the port’s operational processes in real-time. One aspect of NtechLab’s systems is the ability to manage the access control to the enterprises with far greater efficiency by using biometrics. Our platform will also be able to identify vehicles and read container numbers during loading and unloading to compare and confirm the accuracy of shipping and cargo information. Vehicles are monitored, in real-time, from control rooms.

NtechLab has also been chosen as the technology partner of the Russian pavilion at Expo 2020, which runs for six months from October 2021 to March 2022 in Dubai, United Arab Emirates. NtechLab’s platform will allow the Russian pavilion to collect analytics on visitor numbers, including segmentation based on gender and age, as well as calculating the average length of visit time and whether attendees are new or regular visitors. To ensure effective crowd management and adherence to COVID-19 guidelines, the system will also notify employees when an excessively large number of people gather in one area. It will also provide information about queues in specific areas, such as what time they formed and how many people are in the queue.

Q. NtechLab and the Moscow Department of Information Technology work hand in hand, providing video analytics in the city. That said, how intelligent are the company’s face recognition solutions?

NtechLab’s algorithm is integrated into the Moscow city video analytics system. The functionality of the solution allows real-time high-precision face recognition in the video stream, comparing the results with databases of wanted persons. If a match is found, the system instantly sends alerts to law enforcement officers. The whole process from the actual appearance of a person in front of the camera to receiving a signal takes less than a second, which allows to quickly respond to any situation. The solution can be also used to find missing people. In 2020, over 5,000 crimes were solved in Moscow using a video analytics system with face recognition, according to the data of the Ministry of Internal Affairs of Russia.

Q. Please walk us through the awards and recognitions NtechLab has received so far.

In October, NtechLab won the first G20 innovation award for the best artificial intelligence startup. The event involved 22 countries, 100 startups, over 100 VC and Corporates. The special event was organised in the framework of the Italian Presidency of the G20, which brought together 100 startups from the G20 countries, more than one hundred venture capitalists, and big international companies. At the first stage of the competition, the most promising startups were nominated by each of the G20 countries. At the second stage, 100 startups that made it to the finals were evaluated by venture capital investors based on financial results, product uniqueness, team competencies, innovative ideas to tackle global challenges, the ability to build a more inclusive and sustainable future, and other criteria.

Our algorithm enables better security, better living, and better business. Its superiority in the field of facial recognition services has been acknowledged by a number of renowned organisations. In 2021, the company topped the Face Recognition Vendor Test (FRVT) undertaken by the National Institute of Standards and Technology (NIST) of the US Department of Commerce. Based on the results of seven independent tests, the algorithm developed by NtechLab was given a worldwide top ranking.

Q. About the future, where do you see NtechLab a couple of years from now?

When creating the company, we chose between what we were used to and what we dreamed of – making cities better and safer. We observe that our customers have begun to look at video analytics functions more broadly, that is, video analytics systems are no longer solely a security tool. The concept of a ‘smart city’ with a comfortable living environment for everyone, including people with disabilities, children, mothers with strollers, is becoming technically feasible. And one of the important elements in these concepts — intelligent video analytics systems — now help not only in a timely response but also in making long-term strategic decisions.

As such tasks, I can cite the timely provision of medical care to citizens. Our system can recognize a person falling on the street and send a signal to rescue services, and a smart barrier can recognize an ambulance and let its yard pass (most courtyards in Moscow are equipped with barriers).

“Our algorithm works with unique facial features which makes it impossible to restore the original image of the face — something that is of distinct importance in ensuring personal data protection.”