AiThority Interview with Rohan Sanil, Co-Founder and CEO at Deep North

Hi Rohan! Welcome to the AiThority Interview Series. You come from a very enriching background in the Cloud computing and the DataOps industry. Please tell us a little bit about your journey and what inspired you to start Deep North.

Thank you! I have more than two decades of product, business, entrepreneurial leadership in the video analytics space and founded three companies before Deep North, including Akiira Media Systems, Atstream Networks and Tri-Cad. Prior to co-founding Deep North, I led product management at MetricStream and business development at Cambridge Solutions (now part of DXC Technology), building key partnerships with marquee customers such as Polycom, Broadcom, Virgin Mobile, Cisco and Oracle. 

We created Deep North to enable businesses to digitize their physical environments. All our customers are facing extreme competitive pressures, and without proper data to understand behavior on their physical properties, they are left with very little visibility and limited information to make important decisions. For example, many brick-and-mortar retailers don’t know how many people walk into their stores every day, only the number of transactions processed through their POS systems. This is a fundamentally very limited understanding of the business.

How many people walked in and out of the store without purchasing anything?

Were there aggravating factors such as long queue lengths or low service interactions?

These types of insights and more are what we provide our customers.

We strive to empower enterprises who have footprints in the physical world with decision-making insights necessary to be successful in the Age of AI.

Tell us a little bit about Deep North AI. What does your ideal customer profile (ICP) look like?

Deep North is an AI company that utilizes any video security system to capture real-time video analytics for the empowerment of the store, simplify operations, and improve in-store customer experience. There are many factors that Deep North’s intelligent video analytics captures to improve store performance and the customer experience. A couple examples include: a shopper’s journey to conversion, dwell time, traffic flow, associate-customer engagement, and many more. Our ideal customer profile carries a motive to increase operational efficiency to boost revenue in their physical space. Having a long term goal to become the perfect store while creating the best possible customer experience.

Customers who tend to use Deep North technology show an increase in revenue sales, store performance, and customer appearances and reappearances. Deep North’s technology provides extra support on analysis that humans cannot calculate alone. The surveillance captures real-time analysis that humans cannot generate 24/7, which creates an increase in overall store performance. Thus, Deep North’s AI technology can be truly beneficial to any store.

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Which industries and markets are you currently targeting with your AI solutions?

With our AI enabled platform, we’re solving some of the most pressing problems of our clients across six core industries, including retail, quick service restaurants, shopping centers, transportation, commercial real estate, and manufacturing and warehouses.

How has Deep North evolved in the last 2-3 years and what is the driving force that makes your Deep Learning company so competitive?

Throughout the years, Deep North has been on the track of transforming brick-and-mortar retailers into using predictive AI and machine learning. Deep North’s technology captures footfall, occupancy, dwell time, heat mapping, checkout time, customer journey, queue management, engagement, conversion, exit/entry, and staffing in real-time. We have definitely expanded our business to many partners that understand the evolution of AI technology to better manage and facilitate retail enterprises.

To better improve our system, we are adding 14 new patented algorithms for better analysis on customers, stores, and security. What gives Deep North the competitive advantage is that most enterprises do not contain object-re identification, object detection at a high accuracy level, and the ability to learn and make adjustments for better performance. To conclude, Deep North has come far in the last 2-3 years and is only going to continue to progress over the years.

Big data, AI and Cloud computing capabilities have completely changed the way different industries work. Could you please tell us a little bit about your experience in working with the various industries that use Deep North solutions?

Let’s use retail as an example. It’s well known that traditional retailers have struggled to drive foot traffic and customer engagement in brick-and-mortar stores over the past decade. The Internet and rise of retailers like Amazon – coupled obviously with the onset of the pandemic — have changed the retail landscape in unprecedented ways.

But with consumers now venturing back in-store, how can retailers effectively compete with their online counterparts – and other brick-and-mortar businesses?

A clear imperative is to deliver personalized service, convenience, and other engagement factors to drive purchases and loyalty.

However, what physical stores critically lack, unlike their online competitors, is clear visibility into consumers’ browsing and shopping activities. That could mean something as simple as how long a customer waits in line before being able to purchase all the way to the in-store path-to-purchase for a shopper.

Brick-and-mortar retailers can use AI and computer vision solutions from Deep North in combination with their existing store camera infrastructure to understand who their customers are and how they behave, while ensuring customer privacy. With these technologies, retailers can gain real-time insights for decision making so they can positively impact key metrics like in-store (and back-of-house) operations, labor planning and allocation, and, critically, overall consumer experiences.

Retailers can do this through more effective product merchandising and marketing, staff optimization and much more – driving in-store conversions, satisfied customers, and significant cost savings. 

Please tell us a little bit about Checkout IQ and how it could revolutionize the use of Computer Vision for the Retail/ Omnichannel commerce industry?

Checkout IQ is Deep North’s retail loss prevention solution, which uses computer vision and AI to reduce asset loss at checkout. With shrinkage at an all-time high and an increase in organized retail crime, we are providing a new way for retailers to prevent fraud and improve their bottom line. 

Checkout IQ works with retailers’ existing camera systems. By analyzing camera views, the application identifies items that are being scanned by the customer or the cashier, and this count is cross-referenced with the POS item count to detect any discrepancies.

If there is a discrepancy between the two counts, the managers receive an alert in real-time, via mobile or any other system of choice, enabling them to intervene before the transaction is completed. This allows the managers to manually approve a transaction that comes into question. Checkout IQ provides retailers with a seamless way to monitor and rectify potential thefts, prevent unintentional billing errors, and address other retail fraud activities such as employee/customer collaborations. The technology also improves the customer experience by preventing items from being out of stock unexpectedly due to theft. 

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Which industries could benefit from using CV and DL applications for their operations? 

Any of the previously mentioned industries can use computer vision and deep learning to digitize their physical environments and gain critical insights to improve real-time decision-making to enhance profitability, efficiency and safety. Using retail as an example, following are some specific applications of the technologies: 

1. Footfall analytics. With these technologies, retailers can determine metrics like the number of people walking into a store, the number of people walking out of a store and the total number of people in a store at a moment in time.
2. Customer demographics and repeat visitors. Deep learning and computer vision can enable retailers to determine characteristics like customer age range, gender and the people who made more than one trip to the store on a single day.
3. Customer journey. With this functionality, retailers can understand heatmaps/the number of entrances into a zone. They can also determine the length of time spent in-store as well as length of time spent in a specific store zone.
4. Queue management. Computer vision and deep learning provide clarity on the number of people waiting in line for checkout and the average wait time spent in queue before reaching checkout. 
5. Fraud and loss prevention. Retailers can use computer vision and deep learning to combat retail shrink with better loss prevention solutions at the front of the store. 
6. In-store analytics. The technologies provide the ability for retailers to understand shelf engagement, including the number of touch gestures made towards shelved items. It also delivers POS transaction time and conversion details. In addition, they can provide retailers with insight into the dominant customer path, including zone-to-zone traffic patterns from shopper entry to exit.

What is your view on the business leaders advocating the responsible use of AI and machine learning? 

Digital transformation is on its way as business leaders are working up digital initiatives at a pace like no other.

Implementing AI and machine learning I believe is a step forward in the right direction for any company to use to not only achieve operational efficiency, but to create a customer experience one could never forget. Now, AI brings a tremendous amount of opportunities to businesses, but with carrying an asset that could strongly define how a business is operated in the future, comes huge responsibility. Responsible AI comes with the practice of deploying, designing, and developing AI with honest intention to inspire employees and businesses, to trust and scale AI with complete confidence. 

Safeguarding user data requires highly distributed backup infrastructure, as well as new encryption methods. Please shed some light on Edge-centric AI initiatives.

Having a partnership with Dell Technologies we have made a commitment to help stores, shopping malls, and other commercial spaces better understand how the consumer behaves.

Our goal is to strengthen the confidence of every business decision made by either executive or store manager with high level insights from cutting edge accurate data. This will not only increase business revenue, but provide a memorable customer experience which will create loyalty. Now, there is never a better time to make adjustments than the present and by having Edge-centric AI initiatives, you are able to catch everything with real-time monitoring. With Dell’s validated design for Retail Edge with Deep North, we are providing a solution that strengthens a retailer’s customer insights. Overall, there are five benefits of edge computing: 

1. Speed is increased 
2. Improved Security and privacy
3. Cost efficient (reduction of operational costs)
4. Extremely reliable 
5. Scalable

How can companies improve their dependence on Cloud and Security intelligence solutions to prevent catastrophes such as data leaks, hacks and ransomware?

Cloud and Security intelligence are extremely beneficial in today’s society.

For instance, it allows companies to have the liberty of accessing data and data exchange 24/7 for continuous operation. The Cloud is convenient in so many aspects; however, companies need to take extreme precautions at all times. All the amounts of raw and processed data can lead to data leaks, hacks, and ransomware.

There are a few factors that can prevent these problems from occurring. Initial backups of data are very important due to the fact that when it comes to a business, data is what makes up the business, so to avoid financial and data loss, all data files need to be backed up constantly.

Storing sensitive data is another factor that can jeopardize a business. If a company restrains itself from uploading sensitive data, then it can run smoothly without issues. In my opinion, the main solution to prevent catastrophes is using encryptions and reliable passwords.  By having layers of encryption before uploading data the cloud makes it difficult for hackers to access the data. Lastly, testing one’s cloud and security intelligence can have a significant impact than people give it credit for.

Tell us more about a consumers’ perception of AI and how it can be an important tool to reduce security mishaps while improving digital experience? How do you measure these at Deep North?

AI can enable businesses to create safer work environments, detect safety breaches, monitor compliance, and action real time safety and accident alerts. Humans have limitations and cannot monitor everything constantly 24/7; however, with the power of AI and computer vision it’s possible.

The power of AI can detect and prevent malicious behavior from occurring, which creates safety for customers, employees, and the business. Nowadays, AI has become beneficial to enterprises in preventing revenue loss, increasing customer reappearances, and overall business operations. When it comes to Deep North, we use powerful, pragmatic AI that leverages on any existing video and data infrastructure that captures real-time insights to identify opportunities, barriers, and action solutions.

Our product is simple, scalable, and actionable. Lastly, there is always room for improvement, Deep North is just going to continue to improve and make enterprises operate at its highest level while providing its technologies for enhancement.

We see so much happening in the healthcare and consumer services industries with new data privacy laws and upcoming cookie policy changes. How is Deep North specifically gearing up to meet the new-world challenges in data privacy for these industries?

Deep North takes privacy extremely seriously. Deep North was developed to govern and preserve the integrity of every individual by the highest possible standards of anonymization. Deep North is GDPR and CCPA compliant, and the company does not store, save, or transfer any video images outside of the location (e.g., a store). All processing is done inside the location and purged. 

Customers own 100% of their data with Deep North. Data is processed and secured on site (during on-premises deployment) and in the cloud (during cloud deployments).

Data is processed and securely sent as anonymized metadata to the cloud using industry accepted secure methods. Deep North never has access to PII or stores customer data during this process and ensures that all data objects are securely stored and transferred.

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Your take on the future of AI ML operations and how big the industry will become by 2025 for the consumer markets:

If you are a company struggling to break-even or to make a profit, have you considered implementing AI into your operations?

One question we have to ask ourselves as an enterprise is how can we provide a memorable customer experience. Once this is achieved, not only you have integrated good lasting thought to your consumer, but occurring sales.

AI allows the business to operate at its finest and put together large amounts of data which can lead to business intelligence and strategic insights, insights that probably would not have been found. Businesses are starting to realize and adapt to this ever changing environment and many have found out that with the help of AI, it allowed them to obtain or maintain a competitive advantage. I am excited to see the future of AI continue to grow as it plays a crucial part in boosting operational efficiency.   

An advice to every AI CEO looking to start in this space:

My advice to every AI CEO looking to start in this space is to ask the question: how can I implement AI to solve my defined problem? I emphasize define because I believe that many organizations lean to AI to find a problem instead of there already being a problem to fix. Lastly, spend time thinking about this and as you slowly develop your AI plan, a transformative action will start to appear. 

Thank you, Rohan! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]