Autonomous Checkout

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Part
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Autonomous Checkout Overview

Retailers looking to convert to or establish self-checkout and automated checkout in stores can manage losses by implementing self-checkout lane clerks and shopping apps (backed up by video monitoring), performing random or algorithmic security checks, and estaablisning artificial intelligence loss prevention strategies. Each of these techniques has been recommended by one or more retail technology experts and solutions technology leaders have been identified where applicable.

SELF-CHECKOUT LANE CLERKS

Retailers should use a self-checkout lane clerk to keep customers honest and accurate. Brendan Miller is the principal retail analyst at Forrester. He advises retailers that before they can transition to fully automated checkout, whether product recognition, shelf sensors, or RFID technology-based, they should start with an expedited mobile self-checkout lane. He says that mobile-scan users should be directed to this mobile self-checkout area to scan a bar code at a POS kiosk, overseen by a self-checkout lane clerk.

Adrian Beck is an Emeritus Professor at the University of Leicester. He has over 30 years research experience focusing on helping retailers better understand the impact of loss and how it can be managed. In a report, he says that shoppers need to be kept honest and accurate by using suitable, properly trained and motivated clerks and supervisors working at a self-checkout machine station. The goal of self-checkout lane clerks is to prevent loss and improve the customers' shopping experiences. This solution is native to retail establishments and there are no startups or technology firms in a position of leadership.

SHOPPING APPS

Brendan Miller says that retailers need to provide an app so that customers can check-in with the app as they walk into the store. In addition to shelf sensors, customers should be required to check-in with an app so that the retailer knows their identities and their locations while in the store. This can be enhanced by live video monitoring. This strategy allows retailers to watch inventory and keep an eye on customer activities including possible theft. BingoBox operates several convenience stores in Beijing and Shanghai and has a successful track record with this strategy.

RANDOM OR ALGORITHMIC SECURITY CHECKS

Brendan Miller recommends random or algorithmic security checks. Algorithms should be used to flag high-risk items or in-store activity so that staff can investigate. Mobile-scan customers should check out and leave 90% of the time, but sometimes, based on the activity inside the store or the items scanned, customers should have their bags checked by staff. The retailer should inform all mobile-scan customers beforehand that they may have their bags checked. The goal of this technique is to prevent loss and protect assets and inventory. The company FutureProof provides solutions in this space.

ARTIFICIAL INTELLIGENCE

Dusty Lutz is the Vice President of store transformation solutions at NCR Corporation. He says that retailers should plan to use artificial intelligence to help them analyze and compare point-of-sale video and data to help them to clearly identify each retail transaction and spot fraudulent activity. Errors or suspicious events can be detected by the system, which then notifies a clerk via mobile device and instantly replays a video clip. Dusty Lutz says that artificial intelligence ensures that any theft in autonomous checkout will leave a data trail that can be investigated. The goal of AI is to spot scan avoidance incidents, prevent loss, and protect retailers assets. StopLift is at the forefront of this technology and has so far spotted more than 2.6 million scan avoidance incidents.
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Company Profile: Defendry

Defendry is a security company that provides AI tech solutions for camera surveillance. The company was founded in 2018, and acquired Deep Science in 2019. The executive leadership team includes Pat Sullivan, Sam Tkach, and Sean Huver. Below we have provided a deep dive of our findings which can also be found in the attached spreadsheet.

basic information

Defendry is a private company that provides 24/7 security monitoring services. The company uses the patented Active Response Technology (ART) system to detect threats. This system is an AI security system that instantly detects threats and flags them. The system is affordable and easily integrated with most security surveillance systems.
Defendry, headquartered in Scottsdale, Arizona, was founded on June 1, 2018, by Pat Sullivan. The company acquired Deep Science on March 1, 2019. Since its founding, Defendry has worked on developing and patenting the ART system. In addition, they have reported working on automated workflows for internet of things devices since the acquisition of Deep Science.

Products

The company currently only provides one product, the ART system. The system monitors surveillance cameras 24/7, alerts human monitored systems of threats, auto locks doors, provides automated action plans, and uses secure communication channels.
The company claims that they provide an "ART-ful" solution to human error for security monitoring. They state that the system notifies police, provides emergency action plan instructions, and establishes a secure communication channels all within one app. Unfortunately, any additional information can only be obtained by requesting further information via the company website as there is no other publications detailing claims.

Further details

In order to determine the total funding amount for the company, research began through the financial data provided publicly by the company. Unfortunately, because the company is private, there are no annual reports available to the public. We then searched several company profiles for both Defendry and Deep Science on sites like CrunchBase, Pitchbook, Zirra, and LinkedIn. Through this search, we found several mentions to the company either having no funding or not disclosing the funding amount to the public. To confirm, we searched news publications, articles, and industry reports for any mention of funding. Because we were unable to find any mention of funding and the amount of the Deep Science acquisition is not publicly available, we determined that the funding amount through funding rounds is $0.00.

The executive team at Defendry consists of Pat Sullivan, Founder & CEO; Sam Tkach, Director of AI Technology; and Sean Huver, Chief Science Officer. In addition, some of the company's competitors include Athena Security, Deep Sentinel, and Calipsa.
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Company Profile: Signatrix

Signatrix is a solution provider for artificial intelligence and machine video comprehension for retail stores. The company uses human image and video comprehension to promote productivity in stores effectively. Signatrix enables retail stores to measure customer volume and detect theft via cameras with real-time result and analysis. It claims that it can ensure that no carts carrying unpaid goods leave the retail store unnoticed through the open entrance. Among its competitors are Codete GmbH and Noccela. As available, in rows 3-10, column F of the attached spreadsheet, we have provided the requested information on Signatrix.

METHODOLOGY

We were unable to find the information about the total amount of funding Signatrix has raised to date as well as information on whether it has been acquired or made any acquisitions, and any changes in its senior leadership.

We tried looking for any listing of the company's funding history via databases that contain information about funding rounds such as Crunchbase and ExploreBit. Although we were unable to find the amount of funding raised, we found information about its investors, the date of the funding, and funding type.

Next, we tried to search for the company's financial reports hoping to find the amount of funding raised. However, an exhaustive search through the company's website to see an "Investor Relations" section that may contain links to investor reports was unfruitful. We also tried searching through annual reports sites like AnnualReports.com. However, while annual reports of similar AI companies were available, there was none for Signatrix.

Lastly, we tried looking for articles, publications, industry reports, and news reports that may contain info about the company's funding rounds. Unfortunately, after searching through sites like Business Insider and IBISWorld, the information we found was only on the funds raised by the other similar companies. Therefore, we concluded that the amount of funding is undisclosed and not publicly available because Signatrix is a private company.

For information on whether Signatrix has been acquired or made any acquisitions as well as any changes in senior leadership, we first tried to look for the company's historical background via its website and its LinkedIn page. Unfortunately, there was limited information available to provide a detailed historical background. What we found was more on general info like the date it was established, legal names, and so on.

We then tried searching for news articles, publications through sites like Bloomberg, Forbes, and other online magazines hoping to find topics written about the company, precisely the historical background. Again, we could not find any data about the company's history specifically about whether it has been acquired or made any acquisitions, and any changes in its senior leadership. What we found was general information about the industry with no specific info about Signatrix's history.

Lastly, we tried searching for the professional information of the senior team members of the Signatrix expecting to find relevant information about how they started the company via sources such as speech videos, voice records, and so on. We searched through the company's LinkedIn, Facebook, and Instagram accounts, but there were no posts on its historical background. Instead, posts on the accounts were only on industry updates and personal updates.

While we did not provide any information about whether Signatrix has been acquired or made any acquisitions, and any changes in its senior leadership, we presented useful findings of when and where it was founded and when its first product was launched. We have also assumed that the reason why information is unavailable publicly is that the company just started in 2017.

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Company Profile: Solink

Solink was founded by Michael Matta in 2009 and is based in Ottawa, Canada. Solink is a hub for smart security solutions. It allows one to monitor and guard their business with information from existing video and Point of Sale data. It offers brick and mortar stores a smart way to mange operations, loss prevention and security. Solink uses video auditing software to sync data and transactions. A detailed report of our findings can be found in the attached spreadsheet, column E, rows 3-10.
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Company Profile: Attensi

Attensi uses 3D technology, human psychology, and live interactions to gamify training and simulate business environments in order to improve performance and adapt personnel to changing demands and procedures. The company was founded in Oslo, Norway in 2007 by Odd Skarheim. Its high profile clients include Nestlé and Spar International. The company is led by CEO/CTO Anne Lise Waal along with EVP Sales and MD UK Krister Kristiansen and EVP Sales Bjarne Johnson. Major products include Attensi Behaviour, Attensi Process, Attensi Skills, Attensi Portal, and Attensi Creator. These products range from full 3D environmental simulations through mobile apps and analytical tools. Details on these products, along with a great deal of information about the company, its leadership, and its history have been entered into column D of the spreadsheet entitled Autonomous Checkout, linked here.

We were not able to find the total funding raised by Attensi. There were a few other small pieces of requested information that did not emerge from our research, such the name of the company's first product or a history of its leadership's changes. There are indications that the company has held back some funding and internal operational details in order to preserve a competitive edge.

METHODOLOGY

We began our research with Attensi's public web presence. These sourced generated the majority of the information needed to answer this request. However, Attensi's web sites produced little information about the company's product history, nor did they offer information about total funding, primary competitors, or recent changes in leadership.

Seeking the missing data, we turned to respected investor-targeted databases such as those maintained by CrunchBase, PitchBook, Zirra, and ScaleUpPorto, among other sources. This strategy provided information on primary competitors as well as leading us to a pair of sources that reported on one of Attensi's funding rounds, but it did not give us overall funding numbers nor any of the other missing data points sought in this request.

At this point, we expanded the scope of our research to include trusted, high-profile business media such as Forbes, The Entrepreneur, Times, CNN, Bloomberg, The Financial Times, etc. A source here confirmed that Attensi had kept the amounts raised in its other funding rounds private.

Still seeking additional information, such as the name of the first product launched, recent leadership position changes or similar data, we turned to company profile and review sources such as Datamation, MIT Technology Review, and GoodFirms. Unfortunately, no additional information was discovered from these sources.

CONCLUSION

Attensi offers 3D modeled, gamified training and tools to organizations in order to improve leadership, assess individuals, and test and implement workflows. The company has clients in 60 countries and offers tools in 10 languages. There were a few pieces of information about the company that we could not find, including its funding total. For convenience, a second link to the spreadsheet can be found here.
Part
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Part
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Autonomous Checkout Initiatives

Initiatives that retailers are implementing or developing in terms of autonomous checkout include AI and image recognition, kiosks, Scan & Go, RFID tagging, and vending machines.

METHODOLOGY

Initially, we started our research by looking for technologies in autonomous checkout. We first found the most popular initiatives, being "the most popular" as those that have been developed for the biggest sellers (online or in-store), such as Amazon. These initiatives are AI and image recognition. Then we tried finding different kinds of ways of developing these initiatives from companies such as Walmart, which has its Scan & Go App. Further, we continued our research and found several "physical" technologies such as kiosks and vending machines. However, being older technologies, there is less AI involved. Lastly, we investigated a technology mainly developed in China and Japan, which is RFID tagging.

Initiatives that retailers are implementing or developing in terms of autonomous checkout

1. AI AND IMAGE RECOGNITION

Description: Standard Cognition equips regular retail shops with 27 cameras overhead that identify clients by shape and movement. They also have their iOS/Android app and special light flash patterns, allowing cameras to tie the customer to its account and payment method. It also works without an app. The camera system is 99% accurate and is trained to identify suspicious movements and behavior of shoplifters. In September 2018, Standard Cognition opened a 1,900-sq-ft flagship test store on Market St. in San Francisco. Developing branches of AI (such as machine learning or natural language processing) enable computer systems to make recommendations. Artificial intelligence recognizes if customers are putting products in their pockets or bags or not and knows when to charge for payment.
Goal: Removing the machines that are between people such as conveyor belts, cash registers, scanners, etc. Instead of a complex tech solution that needs a new whole store built around it, retailers pay for the installment of a low number of ceiling cameras and a computer to run them. Another goal is to eliminate lines and reassign cashiers to become concierges who make sure customers find the perfect products. It enables a frictionless customer experience. Artificial intelligence (AI) developments can afford retailers the chance to move from common automation to autonomous computing. It can help add additional customer services such as home delivery or click & collect and enable a frictionless customer experience.

Companies at the forefront include Standard Cognition and Amazon Go. Amazon Go is in Chicago, San Francisco, and Seattle, whereas Standard Store is in San Francisco.

2. KIOSKS

Description: Payment kiosks allow the customer to pay with traditional payment methods such as credit/debit cards or cash. There are two kinds of kiosks:
i. Traditional self-checkout kiosk

ii. Payment kiosk

A self-checkout kiosk at a local grocery store requires the shopper to scan, bag, and pay for their own items. A payment kiosk allows the customer to put items in their bags, go to a payment kiosk, which displays a total amount, and pay, making the interaction with employees shorter. Retailers can decide what capabilities they want to offer on their payment kiosks. It may include benefits such as contactless pay, chip cards, cash, gift cards, or all of them.
Goal: Kiosks allow retailers to maintain the flexibility that shoppers depend on. They offer speed, convenience and better overall customer experience. The goal is to provide an actual frictionless experience for customers by enabling a system that requires the use of an app for payment. It allows customers to shop and then stop at a kiosk via any means they choose.

Companies at the forefront include China Kiosk, Sensis, Kiosk Customized. Retailers include King Soopers, Zara, Mc Donald's, Wendy's, and My Panera.

3. SCAN&GO

Description: Scan & Go users use their smartphones to scan products and pay. They only have to show the digital receipt prior to leaving the store. Scan & Go users are able to view the total cost of all of the items in their carts as they shop. They can scan the bar code on the product or search it in the app database. There are no plans to get rid of cashiers. Instead, it is meant to provide customers with a choice of how they pay.

Goal: The primary goal of Scan & Go is to avoid the privacy issues that camera and AI technologies have. It helps elevate the member experience by making the checkout process faster as well as making it more convenient for the member.

A company at the forefront is Walmart Labs. Retailers include the Dallas-Fort Worth, Orlando, and Northwest Arkansas Walmarts.

4. RFID TAGGING

Description: RFID stands for Radio Frequency Identification. The smart labels are captured by a reader via radio waves. Customers automatically checkout by walking through the checkout lane with the basket containing products with RFID tags. Scanning also the customer's prepaid cards, the solution will automatically scan products and complete payment.

Goal: Its goal is to reduce the store staff operation and contribute to labor-savings. Tracking individual products will enable dynamic pricing.
Companies at the forefront include AB&R, Marktrace RFID, and Panasonic. Retailers include Neiman Marcus, Macy’s, Lululemon, and Rebecca Minkoff.

5. VENDING MACHINES

Description: A customized vending machine provides an automated checkout experience. This system gives the retailer information about sold products within the past 24 hours, week or month, and also shows which products are bestsellers, and warns when restocking is necessary.
Goal: The system automates the checkout experience. It puts a glass between products and customers and eliminates unnecessary touch.

Companies at the forefront include Automated Stores, Digital Media Vending, Innovative Solutions. Retailers include Adidas, Lululemon, Revlon, Mulberry, Caravana, Dirty Lemon, Ives-Saint Laurent, and Hung Fuk Tog.
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Company Profile: Column N

Using its official website, media outlets, and company databases, we were able to acquire the requested information for Vaak Inc. On the attached spreadsheet, our findings on the company are available in rows four through 10 of column N. Below we have provided a brief overview of our findings.

OVERVIEW OF FINDINGS

Founded in November 2017 by Tanaka Atsushi, Vaak operates as a Japanese startup that administers artificial intelligence to identify and prognosticate the actions of shoppers. Its primary investors included the University of Tokyo Matsuo Laboratory, Softbank, and Deep Core. Meanwhile, its first product, VaakEye, was officially launched recently in March 2019, when it was provided as a subscription-based service. VaakEye serves as Vaak's signature product, and it functions as a deep learning, cloud-based AI software system. It searches for possible shoplifters through continuous monitoring of video footage supplied by an establishment's security cameras to distinguish irregular body language as well as behavior.

Set to be launched in August 2019, VaakPay, another product from the company, will utilize security camera footage to observe the items customers remove from shelves. It will also provide customers with a unique checkout-free shopping encounter. One of Vaak's claims is that its optimized deep learning model and comprehensive networks are capable of recognizing and prophesying possible shoplifters. It insists that its product has the capacity to examine over 100 personal features including attributes, movement direction, face, and clothes. Finally, Vaak alleges that their detection system's efficiency in recognizing violations through the use of experimental data is 81%.

At Vaak, Tanaka Atsushi serves as the CEO and President, while Yu Kurakira is the CTO. The company's direct competitors include Trueface.AI and Third Eye. According to Crunchbase, Vaak Inc. has accumulated approximately $500,000 in total funding. Currently, Vaak employs around 20 individuals and is a member of Japan's IoT Consortium. The company was recently awarded the EY Innovative Startup 2019 and the Honda Xcelerator Catapult.
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Company Profile: Column M

DeepCam was founded in 2015 by Don Knasel and is based in Longmont, Colorado. After three years of stealth mode, DeepCam launched its first product in April 2018. They claim that what sets their facial matching apart from the competition is that their systems work accurately with large populations to the millions. They also claim that their technology greatly reduces retail operational costs and loss prevention costs. DeepCam has received a total of $20 million over one round on December 29th 2017.

More details on DeepCam can be found in the attached spreadsheet in Column M, rows 4-10.
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Company Profile: Vendlytics

After reviewing credible sources including its official website, LinkedIn profile, startup sites, and media reports, we have identified the requested details on the company Vendlytics. On the attached spreadsheet, our findings are available in rows three through nine.

OVERVIEW OF FINDINGS

Founded in July 2017 by Elijah Tai and Ashton Rourke, Vendlytics has a headquarters in Toronto, Canada. Vendyltics provides services to businesses in the retail customer industry. It offers its clients details on the behavior of customers by employing video analytics. To help its clients to concentrate on likely customers and improve sales, Vendylitics permits companies to comprehend their shoppers by geography, store type, gender, or age. The company also enables them to evaluate the ways diverse product shelf placements options shape consumer interactions and experiment with various packaging designs. The benefits that Vendylitics offers companies is achieved by replacing sales data with customer-product interactions.

Vendlytics operates as a proprietary algorithms software system that is powered by artificial intelligence. It can be integrated into an establishment's software and video hardware. Additionally, it presents video analytics, in real time, to help avoid retail loss. Vendlytics provides A/B test packaging capabilities and the ability to develop perceptive planograms. One of Vendyltics's claims is that its video analytics technology empowers its clients to enhance the satisfaction index and experience of customers through AI monitoring. In this instance, the AI observes the ways that customers interact with various products and presents Vendlytics's clients with an experience that is result-oriented.

The primary competitors of Vendlytics include Lexalytics, Prism, and Scanalytics. Also, the company is currently in incubation at NEXT Canada.

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Company Profile: ThirdEye

ThirdEye is building the world’s first real-time CCTV powered AI assistant that is intended to be used by retail floor staff. ThirdEye was founded as a private company in London by Peter Rennert and Razwan Ghafoor in 2016. ThirdEye has raised a total of $3.49 million in funding over 2 rounds in 2016 and 2019. Please see below detailed findings about ThirdEye which can also be found in column K and rows 3 to 10 of the attached spreadsheet.

BAsics

ThirdEye is building the world’s first real-time CCTV powered AI assistant that is intended to be used by retail floor staff. The AI assistant comes with a context-aware alert system that helps retailers detect relevant events within CCTV streams and deliver real-time notifications to staff members. The system also comes with an analytics tool that would help brick-and-mortar retailers to make data-driven decisions. The system can “generate new insight to store security, operations, and analytics all working from the same technology.”

HISTORY

ThirdEye was founded as a private company in London by Peter Rennert and Razwan Ghafoor in 2016. ThirdEye's founders received their seed funding from Cambridge Angels group and 2 other investors on Jul 5, 2016. The company currently employs more than 10 staff members.

PRODUCTS

ThirdEye's product is a real-time CCTV powered AI assistant for brick-and-mortar retailers. It comes equipped with a context-aware alert system and an analytic tool for data-driven decision-making. ThirdEye's specialties include CCTV, theft detection, deep learning, machine learning, computer vision, video processing, retail, loss prevention, queue detection, stock-outs, crime prevention, and store technology.

FUNDING

ThirdEye has raised a total of $3.49 million in funding over 2 rounds. On Jul 5, 2016, it raised seed funding that amounted to $867,770 and the lead investor was Episode 1. In their latest funding round on Mar 18, 2019, ThirdEye raised $2.58 million and the lead investor was True.

CLAIMS

ThirdEye claims that its system is able to detect potential shoplifts before they occur. In addition, ThirdEye claims that its system provides actionable datasets for management level decision-making.

TEAM

Razwan Ghafoor is the founder and CEO of ThirdEye, while Peter Rennert is the co-founder and CTO at Third Eye Labs.

COMPETITORS

Among ThirdEye's competitors, are Avigilon Corporation, IntelliVision, and StopLift.
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Company Profile: Detective Analytics

Detective Analytics is a company that uncovers through an AI serial criminal entities by seeing all the crimes that each criminal is responsible for in real-time, then shares and saves investigative insights and interconnect all investigators and investigations. Detective Analytics started three years ago in a meeting between a loss prevention investigations team and a mathematician. It was incorporated on March 2nd, 2017. Among its competitors are ShotSpotter, Hikvision, and Predpol. The information which we were able to find has been completed in rows 3-10, column J of the attached spreadsheet.
While we were able to find some requested information, we were unable to find information on companies' funding, revenue, and clients. Also, no explicit information was found for the leadership team of the company except for that of the founder. Below, we have outlined the strategies which we employed to adequately address the request for a better understanding of the unavailability of the missing data points.

METHODOLOGY

First, we started the research by looking for information on the company website. We found information about the company's main activity, history, interesting facts, the founder, what they offer to their clients and how the company works. Then, we continue the research on public databases, and we found where the company operates and when they started.
Then we searched for information about the company's clients, or if there was any mention of how the company benefits its clients on company news feeds, media publications, and third party sites. There was no information publicly available about their clients or the companies that use the services they offer. However, we did find general information about how different AIs are used to prevent crime, how they drop the criminal cases by a 50%, even general information about how this technology is used to stop crypto criminals, and how the NYPD uses AI for solving cases. However, nothing led us to the specific information we needed.
Next, we broadened the research more, trying to find reviews about the company in business magazines, tech portal news, and cybersecurity websites. We were hoping to find opinions of clients, and then search how those clients use the company's services, but we didn't find any information or even a company mention. The only review found was on their Facebook page, which has almost no information or posts, and the review wasn't done by a client, but by a worker saying that it's the "best company to work for." This strategy again failed to provide us with the information we needed.
Going forward, we attempted looking for any news or report with information about the company benefits or clients currently using its software, with hope to find successful cases solved with the company's services, or clients telling about the benefits of the company's services. Unfortunately, no information or company mentions was found. Information found here was generally about the company services.
Then, we continued searching for the total amount of funding the company has received to date and the revenue. There wasn't any public record found by any straightforward research in Owler, Crunchbase, Pitchbook, and Opendatabase. We also checked for the companies financial report, but couldn't retrieve such data. We also tried to make a calculation using their number of clients and the cost of their services, but that wasn't possible, due to the fact that we didn't find information about their clients, and also, because the company doesn't show any information about the pricing of their services on their homepage. It's important to mention that no paywall resource was also found on this topic either.
Again, we searched for the company's current leadership team, but could only find information about its founder. Information regarding other executive members wasn't found through a direct search on company databases. We only found that the company was a finalist of the RTech Asset Protection Innovation Awards, but nothing else was mentioned about their team or their performance. We also searched on jobs hiring portals like Glassdoor, Indeed, and Hired for any review or information about the leadership team, or people working currently in the company, but we didn't find any information, not even a mention of the company. We also looked in professional social media networks such as LinkedIn and AngelList, trying to find information about the company or people that currently work for the company, but we didn't find information or a mention of the company.
After series of searches through reliable sources, we concluded that the company must have strong politics about client's information disclosure, mainly because they work stopping crime and they manage sensitive information about criminal organizations and criminal actions. They also must have their interest in keeping their information hidden to the public, because of those same reasons, and not to endanger their workers and leadership team as well.
Despite the lack of indicators about the company's tracks, we can surely affirm that the company is very successful in its field since it was a finalist in a very important event related to AI security.

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Company Profile: Ocucon

Despite our best efforts, we were unable to find any funding or revenue information for Ocucon. However, we were able to find the company was founded by Gary Trotter & Stuart Ferguson in 2016. They offer their VSaaS system as well as pixel redaction services. There is more information on the attached spreadsheet.

METHODOLOGY

The first search strategy we used was to look for any financial statements published by Ocucon. Some websites reviewed were CrunchBase, Angel List UK, and Ocucon. We were unable to find any financial statements or annual reports. We believe this may be due to the company being a private limited startup company and they have chosen not to publish that information.

As a second strategy, we tried to find any SEC filings or other public company filings that may provide us with funding or revenue information for Ocucon. Some sites visited were Companies House and Euro Pages. We were able to find some confirmation statements, micro company account information and their incorporation papers. None of these filings had funding data or anything related to financials except the micro account filing.

As a third strategy, we tried to search for any press releases that revealed their investors, their amount of funding, or any revenue data. Some websites visited was NE Connected, Retail Times, and Insider Media Limited. The press releases we found talked about the direction the company was going and possible partnerships, but nothing gave any financially related information for the company.

Since we were unable to find any funding or revenue information on Ocucon, we decided to use the limited financial data we found earlier as a substitute for their funding received to date.

COMPANY PROFILE — OCUCON

Overview

Ocucon is the self-proclaimed “world’s first” Video Surveillance as a Service (VSaaS) system. The purpose of the company is to provide unlimited cloud storage for unlimited cameras. They are also Application Programming Interfaces (APIs) with several other software partners in order to create a kind of one-stop shop for business data intelligence.

History

The VSaaS company was founded by Gary Trotter & Stuart Ferguson in 2016 and is headquartered in Newcastle upon Tyne, UK. There are currently between 11 and 50 employees that work at this privately held company. Ocucon’s VSaaS system officially launched in October 2017. The name of the Business Development Manager is Simon Gardner, Business Operation Support Executive Maral O’Brien, and their Chief Technology Officer is named Stephen Purvis. In November, they appointed a freshly graduated Ph.D. student from North Umbria University named Tom Lawrence. They hired Lawrence to aid in further developing their AI and machine learning technology.

Products

  • Ocucon offers its VSaaS system cloud storage which features the Ocucon portal, long-term storage, data centers, and software solutions.

Financial

  • We were unable to find any information on the amount of funding the company has received thus far.

Claims

  • They also claim to have, “set a new standard for intuitive and cost-effect video redaction."
  • Ocucon also says that their service is stopping fraudulent personal injury claims by helping businesses to, “understand the causes, identify where improvements need to be made, and put a plan into action to mitigate risks."
  • They also say that using their service to combat slips, trips, and falls, they could help businesses save themselves from paying out some estimated £800 million a year that’s currently being paid out for personal injury cases.

TEAM

COMPETITORS

  • Ocucon is the only company that offers its VSaaS system. Their co-founder Gary Trotter said, “I am sure we will have competitors by then, but we will gain a massive market share.”
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Company Profile: Rapitag

Rapitag is a Munich-based, privately owned company that provides Electronic-Article-Surveillance (EAS) hardtags and payment processes in the retail sector. The German startup offers the "world's first patented" self-checkout, anti-theft security tags. These tags allow for 1-click buying into retail stores replacing the traditional EAS. Our detailed findings are compiled in rows 3-10, column H (Rapitag) of the attached spreadsheet. Given below is a summary of our findings.

Summary of findings

Rapitag offers a security tag that allows 1-click buying at retail stores. It has raised US$11,800 in funding. The company was co-founded by Alexander Schneider (CEO) and Sebastian Mueller (CTO). Niclas Fritz oversees the Business Development of the company and Lars Dickmann is the company's Hardware Specialist.
Since Rapitag is the first provider of IoT security tags, it has no direct competitors in its home country. However, some internationally similar companies are Metrics and Sensor Tags. These competitors were identified based on similar products offered.
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Loss Prevention Companies AI

Two additional startup companies that are using AI, machine learning, data analytics or other new technology to help retailers with loss prevention include DeepCam and Vaak. Note that we were also able to identify articles highlighting other such startups, including AI Guardsman and Earth Eyes. Hence, additional requests will yield further results. Below, as well as in rows 1-3, columns M-N of the attached spreadsheet, we have provided an overview of DeepCam and Vaak.

DeepCam LLC

The company's AI technology, DeepCam, uses facial recognition to aid in surveillance. DeepCam is a biometric-enhanced plug-and-play AI platform that helps retail loss prevention. The technology provides large-population biometrics, video forensics, cross-camera event association, behavior analytics, and multi-location analytics to enhance retail loss prevention.

Vaak Inc

Vaak is a Japanese startup company that uses AI to detect and predict human actions. Its platform includes VaakEye software, which detects and predicts shoplifting behavior, and VaakPay, which monitors unmanned cash registers. The technology is designed to detect suspicious in-store behavior and attributes such as the face, clothes, and motion, and analyze the microdata to predict human actions. The technology has already been deployed in about 50 retail stores in Tokyo.

Sources
Sources

From Part 01
Quotes
  • "Drive mobile-scan users to the self-checkout area to scan a barcode at a POS kiosk, which is overseen by the self-checkout lane clerk."
Quotes
  • "Guardianship: this was considered to be the most important factor by respondents but also difficult to ensure compliance at store level. The key was ensuring suitable, properly trained and motivated Supervisors were used and that they were operating in an environment which facilitated rather than hindered their duties. Overall, respondents to this research thought the optimal Supervisor to SCO machine ratio was 5-6 although this could flex depending upon the SCO environment in place."
Quotes
  • "New tools may offer ways to improve security and reduce theft. StopLift’s ScanItAll Self-Checkout Loss Detection uses artificial intelligence to analyze and compare point-of-sale video and data to clearly identify each retail transaction and spot fraudulent activity. When the system senses an error or suspicious event, it notifies an attendant via mobile device and instantly replays a video clip. StopLift has already spotted more than 2.6 million scan avoidance incidents and found as much as five times higher scan avoidance at self-checkout versus manned checkout."
From Part 07
From Part 15
Quotes
  • "DeepCam: Delivers revolutionizing multi-location retail and banking loss prevention platform through biometric-enhanced AI engines to reduce shrink and slashes loss prevention costs"
Quotes
  • "New artificial intelligence software is being used in Japan to monitor the body language of shoppers and look for signs that they are planning to shoplift. The software, which is made by a Tokyo startup called Vaak, differs from similar products that work by matching faces to criminal records. Instead, VaakEye uses behavior to predict criminal action."
Quotes
  • "Vaak made headlines last year when it helped to nab a shoplifter at a convenience store in Yokohama. Vaak had set up its software in the shop as a test case, which picked up on previously undetected shoplifting activity. The perpetrator was arrested a few days later."
Quotes
  • "There have been similar and successful attempts in the past to tackle Shoplifting using AI, one of them that made the headlines last July was the AI GUARD MAN by a team up from the Japanese telecom company NTT East and a Japanese tech startup called Earth Eyes. The technology employed by Vaakeye and AI GUARD MAN is similar. AI GUARD MAN scans the surveillance footage caught by the camera and look out for suspicious behaviour in the shopper’s body language. The company claims AI GUARD MAN has cut down loses by 44 percent."