Ingram Micro ONE: Big Data & AI Drives Actionable Insights

Published on
November 16, 2021
Thor Turrecha
EVP of Global SaaS
Joy Chua
EVP of Strategy & Development

This is a recap of Ingram Micro ONE 2021 session, Big Data: Using AI to Drive Actionable Insights. Brought to you by Ingram Micro & meldCX.

In today's data-intensive economy, data is currency, power, and opportunity. It is key that organizations possess the right connected systems — systems that will collect and aggregate the raw information that businesses increasingly need.

In this session, we will show you how organizations can harness actionable insights from their data stories using single-endpoint artificial intelligence solutions that are simple to use, fast deploying, and secure from the ground up.



Luke Neofytou  0:00  
In today's data intensive economy, data is currency, power and opportunity. It is key that organisations possess the right connected systems, systems that will collect and aggregate the raw information that businesses increasingly need. Hi, I’m Luke Neofytou, the Head of IoT at Ingram Micro Australia. In the next few minutes, we'll show you how organisations can harness actionable insights from their data stories using single endpoint artificial intelligence solutions that are simple to use, fast deploying and scalable from the ground up. By 2025, the broad amount of data created in the world will have grown to 190 zettabytes, that is 180 trillion gigabytes. However, quantity doesn't always equal quality. Businesses are looking for ways to make sense of this influx of raw data. And research shows that artificial intelligence or AI makes IoT data 25% more efficient, and analytics 42% more effective. In the next few years, the use of AI technologies will be integral in bringing together and filtering raw data from multiple sources to be analysed into actionable data and used as information for decision making purposes. Organisations have a choice, adopt or be left behind.

Joy Chua  1:39  
Hi, everyone, my name is Joy, and I'm part of the meldCX team leading strategy and development globally for the business. Today, together with our EVP of Global SaaS, Thor Turrecha, I would like to share a little bit of our company, who we are, you know, and how we've really created the AI building blocks using our analytics platform Viana to help accelerate the IoT and AI driven journey for our customers and partners. So a little bit more about us and who we are. So who is meldCX? meldCX stands for melding the customer experience. And as an organisation, we're really passionate about delivering premier customer experiences using the best that we have an edge and AI technologies. We also are an Ingram Micro, Intel and Microsoft partner. We work closely with all partners to solve complex problems around AI and IoT. We focus on solutions that can improve the human experience. By taking the complex and making it simple and consumable for everyone. No matter which stage of the data journey you are at. We believe in creating scalable and flexible solutions, which is why our products are designed like digital stackable Lego blocks, which includes our vision AI solution Viana. No matter where you're at on your digital AI journey or even just your data driven journey, we will have something for you. So we have a range of modules that range from ready to go all the way to bring your own AI modules, as well as being able to create custom personalised models for your business needs.

Thor Turrecha  3:23  
What Viana does is quite unique. We use high speed computer vision powered by Intel's openvino to anonymously detect humans and objects, capturing real time analytics so that organisations can tell meaningful data stories about their customers. What we really like to say is that we teach machines to see like humans, and use our portal to surface and consolidate data to tell a story, create an intervention to drive action or insight. Say you're walking into a supermarket, picking up some groceries for dinner, we could tap into ceiling cameras to track your flow through the store. analyse what you're most interested in. Buy what you touch your sentiment, what attracted you to pick a particular signage? Is it the positioning or pricing? Further, we stitch feeds across multiple cameras and channels providing insights to the entire journey? For example, how long do customers interact with a product before making a decision? Do they look happy or sad? Was there a content plan to support the sale? Or was it a staff-assisted sale? What is the average assistance required to sell this product? And does a salesperson actually influence the sale? We can also use Viana to recognise staff based on uniforms and help us separate stuff from customer specific data.

Joy Chua  4:53  
One of our customers is actually one of the big four banks in Australia. They're called Westpac. Westpac uses some of our ready to go modules, like audience measurement and content effectiveness, to understand how their impact customers are interacting with digital content in their bank branches. So what we do is we combine up Viana data or really division analytics data captured through sensors with proof of play data. So what we do is we anonymously attack facial coordinates for age, gender sentiment, you know, are they happy, are they neutral as you're looking at ads, and we combine that with their gaze to see if they're watching the content for the entire duration of play. The stats are then compiled and surfaced into you know, BI dashboards that can then be delivered in monthly or quarterly reports back to the bank's retail and product marketing teams for analysis. Through this, Westpac is unable to understand what really counts as effective content, and which audience segments are more receptive to the various messages that they have in store. If any of you are interested, we actually do have an Intel white paper that we did on this subject. So please visit our website or our LinkedIn page to be able to download that white paper. Our use cases are also not just constrained to retail. We worked with Ingram as well and are currently deploying at a major ski resort in the mountains of New Zealand. And what we're doing is we're measuring traffic of the vehicles going in and out of the resort. So equipped with real time data on vehicle count and parking occupancy. The end customer is then able to route the vehicles to the right location on the slopes for example, optimise staffing, manage parking, space efficiency, and overall improve the customer experience. We also service other industry verticals, as you can see on the screen. This is an example of all our available off the shelf modules applied in a connected workspace scenario. Some of these modules include entry monitoring, which basically tracks ins and outs of foot traffic, as well as how many people are in a particular area. Sammy, was just short for surface awareness, management intelligence, and is really our cleaning and compliance modules where we overlay heat mapping technology with camera feeds, to monitor high traffic or high touch environments. To understand that we need to dispatch more cleaning stuff to the area instead of waiting for set cleaning times. So imagine not having, you know, a tick box and paper or a physical manifests, but instead being able to have a digital manifest that tracks who has cleaned his area and at what time. On top of that. We also have zone engagement modules, which I mentioned before, which allows us to track anonymized personas and your movements through different sections in the flop. Other modules that you see on screen now are available, and they are ready to go. And they use the same hardware infrastructure to enable and what that means is that you know, customers and partners can really take and prove these AI use cases validate you know them through the business before they scale them.

Thor Turrecha  8:21  
Viana's edge stack includes cameras, sensors, and media players. Once Viana moves data to the cloud the solution processes in real time. Business intelligence data is then pushed into an interactive dashboard for end users view and engagement. From a privacy perspective, we ensure that all faces are blurred in streams we capture from sensors like Meraki camera, and no identifiable data is stored or streamed. We make sure we process everything at the edge. As a vision analytics company we also have learned that a person is more than face. As a team we track facial coordinates age, gender sentiment, not facial recognition and add more detail and depth to the anonymized persona by combining objects. For example clothes someone's wearing, and non face behaviours like gait and a question I've been asked hundreds of times So Intel openvino helps optimise our model. The best way to describe it is by saying Open vino is like an energy drink for animals are infringed. Inference runs faster and more efficiently. Our requirement when producing real time analytics, in which timeliness is of the essence. In terms of cloud computing, Microsoft Azure provides unparalleled flexibility and scalability without the added cost, leveraging existing API's within Azure such as IoT Hub, Azure ML and Stream Analytics has made data processing for Viana that much faster and smoother, allowing us to render real time analytics into clear, interactive visualisation for the end customer.

Luke Neofytou  10:06  
The Viana solution has been a great addition to our Ingram micro IoT offerings in partnership with Cisco, Intel and Microsoft. It has enabled our partners to provide their end customers with a complete end to end AI solution. That simple to deploy, easy to use, and provides actionable insights, which has been critical for end customers. Viana enables end customers to get started without the need for developers and make setup easy with a single click instal.

Thor Turrecha  10:41  
Perhaps most significantly, the Viana can meet compliance standards by extracting predefined human data without keeping an identifiable information. In terms of privacy, the Viana does not see view or annotate any personal identifiable and sensitive live data in the cloud during processing phases of blurred and human data captured or saved as a token, a randomised number in the system.

Joy Chua  11:08  
So to talk a little bit more about our partner ecosystem as well. You know, for us at meldCX, we're proud to partner with amazing technology leaders of the likes, you know, cause Ingram micro as well as create a recognisable brands like Cisco Meraki, Intel and Microsoft. We operate in a market where we've understood that, you know, it really takes partners to help scale and grow. And I think working with partners allows us to be agile in our approach to you know, interacting and solving problems together. And it also allows us to focus on doing what we do best as a business and be able to, you know, take that and not have to redo what other great giants have already done in that space, compile that together and focus on really delivering that use case for customers. Linking up with Ingram Micro as well has been amazing. They allow us to, you know, multiply our salesforce, work with them, you know, shorten the sales cycle as well, by, you know, having all the relevant contracts and partners that we need in order to quickly scale and we're really happy to be able to work together to provide joint solutions to our customers.

Luke Neofytou  12:25  
Thank you for your time. I hope this has given you a better understanding of how Ingram Micro, meldCX and our ecosystem partners can help to support your journey into artificial intelligence. Our teams are ready to support you have a choice, adopt or potentially be left behind. Thank you

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