TechEX Santa Clara 2024 – An Event Review

Connected devices and analytics are pushing the frontier of digital transformations, and spawning new business models towards delivering and extracting value. This was a major theme at the recent #TechExpo in Santa Clara, and also forms part of ArcInsight Partners’ research universe.

In 2017, ArcInsight Partners provided this vision for Industrial-IoT’s future path.

The impact to business bottom lines spans across nearly every industry sector. Organizations have discovered new ways of monetizing their products, the most popular one being subscription models. Recurring revenues are a new phenomenon for most industrial companies. Having customers pay for use of machines and products on a consumption basis rather than making them pay upfront for the large capital expense represents a huge seismic shift in industry. Offering a suite of analytics applications by wrapping a data management layer around the physical product makes a product doubly valuable to the buyer. Industrial companies are now charging the way software companies did in the past, licensing it to their customers on a per-user basis for each software application.

The promise is far ahead of reality in many cases, however, as was the case with many companies participating as exhibitors and presenters at the IoT Tech Expo and the AI Big Data Summit this year.
We observed many companies starting out on an  IoT  journey – both start-ups as well as large, established companies moving into this space, we did not see much clarity on their ultimate goals.

There is a lot of value to be delivered via many IoT applications, but also plenty of challenges that lie along the road to to deliver that value. The primary challenge lies in understanding the difference between the product’s software features and (what the client perceives as) business benefits. The gap usually lies in a product development process (& culture) where technology leads the product development process with business folks brought in later. As a result, the consciousness and a clear definition around what business value means emerges too late in the product-market fit development.

Identifying the right value proposition of new connected products ensures that product development funds are channeled the right way in focusing efforts on delivering the right customer benefit – the difference between a successful product and a dud.

Connected industrial products can be expensive considering the layers of hardware, firmware, software applications, cloud operations and connectivity partnerships, all wrapped with an assurance of cybersecurity. Addressing the specific customer pain-point requires this stack to be as closely managed as possible, making the entire exercise an expensive one. Not a surprise that connected products today cost several times that of their traditional non-connected counterparts.

The transition path from a product driven to a solutions & services company isn’t straightforward. A fundamental change in DNA may often become necessary to go from a “build it and they will come” mindset to “how can I solve the customer problem”, meticulously uncovering problem areas leveraging deep data insight and turning that insight into software applications to help address them.

Another dimension to being successful in a connected business is the ability to communicate the value of your connected products to your customer – both current and prospects, and how this product delivers on that promised value. Moving from a transactional relationship (with selling goods) to an ongoing partnership (with selling solutions) involves changing not only your own organization. It also requires influencing the client to reshape their organizations as well in order to benefit over the long run.
Not all IoT players understand ROI of their new offerings. Presenters did not always have a clear idea on how they calculate ROI for their products (a panel moderator this year, one from a big brand European oil & gas company) was downright ignorant about practical implementations of industrial IoT. Several of the IoT efforts shown at this year’s expo were quite in their early stage and we got the sense many were pilots masquerading as IoT project implementations. Read more about Transitioning To Subscription Models here – https://www.arcinsightpartners.com/aip/index.php/research-areas/digital-transformation/subscription-model-strategies/

A example of an industrial company which has managed to cross the chasm to a successful connected business model is Voltas. Read about their Digital Transformation Transition Journey in our case study here – https://www.arcinsightpartners.com/aip/index.php/research-areas/digital-transformation/iiot-digital-transformation-how-voltas-turned-its-customers-around/

Digital twins was a common discussion topic at the expo. While definitions vary among practitioners, a working one concerns building a simulated model of the equipment you are connecting and use the model to identify potential faults and predict failures. For complex connected equipment, we’re going to see more of this as equipment models and analytics become more sophisticated. These models can be used for real time fault detection, particularly in complex machinery and equipment. Read more about digital twins here. https://www.arcinsightpartners.com/aip/index.php/news/how-pervasive-digital-twins-are-extending-enterprise-intelligence/

The IIoT Services Maturity Curve – Moving from Product to Solution Selling

AI was an oft mentioned topic with many vendors offering to assist in developing, testing, and deploying AI-enabled IoT solutions. Given AI’s early days it was however hard to find examples of specific cases at the event that had clear integrations between AI and  IoT while adding value  for the client. Many companies are still exploring ways to effectively integrate AI with IoT to create value. However “AIoT” in the industrial context is ripe for future development. For more insight into how this might work to deliver value, see our paper The AI Frontier Of Industrial IoT. Read our insight about Industrial AIoT here – https://www.arcinsightpartners.com/aip/index.php/research-areas/industrial-iot/cognitive-tools-ml-ai/the-a-i-frontier-of-industrial-control-security/

An important area where IoT implementations are more critical than ever is supply chain traceability, quality control, safety and compliance. Traceability enables swift identification and recall of faulty products, ensures adherence to regulatory stands, builds consumer trust be demonstrating transparency and aids in pinpointing the source of issues in the supply chain. Ultimately, it helps organizations maintain high standards and responsiveness throughout the production and distribution processes.

Among other topics of relevance we picked up during conversations and meetings at the expo concerned challenges of setting up an effective IoT infrastructure at scale, especially optimizing the cost of connectivity. Telecom and connectivity providers stressed that cellular is getting cheaper and easier, and costs do continue to come down for cellular data. Third parties are aggregating connectivity and data services and simplifying the process to get coverage for IoT devices. While IoT wireless protocols have many benefits, one size does not fit all: There were lots of chatter about LoRaWAN and HaLow. However a universal wireless standard emerging may be a near term pipe-dream. The choice of protocol often depends on the specific data requirements and operational context of the IoT application.

CONVERSATIONS WITH ARCINSIGHT PARTNERS AT TECH EXPO
Industry analysts specifically ArcInsight Partners who have attended over the years are focused on capturing new industry and market insight. They look for opportunities to help improve the conference profile by designing and moderating panel discussions with industry experts, surfacing the right topics / issues to discuss, recommending the right formats, even market them to their key executive audiences. The firm focuses on Industrial-IoT enabled manufacturing & digital transformations; evolution of intelligent cities enabled by new mobility design, urban dynamics & renewables; and research on emerging business models enabled by SaaS and new monetisation strategies.

Our analyst attending Tech Expo 2024 nevertheless met and spoke with several interesting companies exhibiting at the event, and sat on a few presentation gems which we plan to retain as food for thought. We highlight some of these exhibiting companies/organizations here and share observations from our conversations with them.

IKIGAI
#Ikigai, an early-stage private company in the broader General AI software space. Ikigai is a five-year-old Generative AI company developing Large Graphical Model powered AI solution utilizing business specific, proprietary, time series data like sales, generate insights and forecasts for a multitude of enterprise areas including Financial Performance, Supply/Demand Planning, Sales Forecasting/Planning, and HR/Workforce Planning.
Its co-founder & CEO Devavrat Shah is a professor at MIT teaching statistics, machine learning, and modern parlance AI for the last 20 years. Ikigai is at the forefront of driving differentiated operational value for companies. Ikigai’s platform is based on Large Graphical Models (LGMs) versus today’s better known Large Language Models (LLMs). Where LLMs are based on language, LGMs are affectionately called LLMs for numbers. LGM platforms like Ikigai leverage structured tabular time-series data that are often mathematical in nature making them computationally efficient. Ikigai then leverages stochastic modeling to present data and predict outcomes that account for uncertain levels of predictability or randomness. A key difference between enterprise use of LLMs and LGMs will be moving from workflow optimization which is a key LLM feature of content creation to the data centric LGM output driving a business to take a certain action.
The output of these LGMs is a generative, probabilistic answer to key business questions across several operational departments and horizontally across industries. Today, Ikigai can yield insights into key scenario questions like supply and demand planning, drug shortage planning, improved financial risk management for fraud or cash management, and even modeling/planning people’s skills versus people tasks. The output of these LGMs is a generative, probabilistic answer to key business questions across several operational departments and horizontally across industries. Today, Ikigai can yield insights into key scenario questions like supply and demand planning, drug shortage planning, improved financial risk management for fraud or cash management, and even
modeling/planning people’s skills versus people tasks. Another key difference to highlight between LLMs and LGMs like Ikigai is the cost and infrastructure requirements. Ikigai only needs to access a company’s own data and model in the influence of external factors (weather for instance) versus petabytes of historical novels or historical content a LLM typically requires.

LGMs use structured tabular data in a time series and make them computationally efficient. Where LLMs require large, voluminous data sources to train on, LGMs do not have this large data requirement as they are trained by a company’s internal data which has better context since it is structured enterprise data. A key differentiator between LLMs and LGMs is that LGMs do not hallucinate as a result of having contextual data.
LGMs also differ in that they use stochastic modeling to predict outcomes that account for uncertain

levels of predictability or randomness. LLMs cannot deal effectively with any uncertainty since they sequence based on historical patterns. The ultimate vision is to enable a low code approach built on top of graphical models for predictions, data reconciliation, and data optimization with tabular enterprise data — i.e., generative AI for tabular data.

ROCKSET
#Rockset, founded by former engineers at Meta, builds real-time search and analytics databases, and has benefited from the use of artificial intelligence in applications from chatbots and detecting anomalies.
Vector search is a way to find related text, images or videos that have similar characteristics using machine learning models. While vector embeddings using large language models (LLMs) have rapidly advanced and become widely accessible, the generalizable nature of these models means that they are rarely used in isolation in production applications. All vector search is becoming hybrid search as it drives the most relevant, real-time application experiences. Hybrid search involves incorporating vector search and text search as well as metadata filtering, all in a single query. vector search intertwined with text search, relational search and geospatial search to drive the most relevant results. Rockset is designed and optimized to ingest data in real time, index different data types and run retrieval and ranking algorithms. Rockset has indexing, retrieval and ranking built into its vector database. Rockset stores and indexes vectors alongside text, JSON, geo and time series data within the same collection. Users can create a vector index on any vector field(s).
Rockset’s expertise in real-time data processing and vector search will enhance the ability to quickly access and analyze vast amounts of information, likely leading to faster and more accurate responses from AI models

THE CYBERSECURITY AND INFRASTRUCTURE SECURITY AGENCY (CISA)
#CISA is an operational component of the Department of Homeland Security (DHS). CISA partners with the private sector, professional associations, and the academic community to help us mitigate cyber and physical risks to critical infrastructure. Our

analyst explored several pertinent security area with CISA at TechEx. They covered cybersecurity-based threat vector scenarios including ransomware, insider threats, phishing, and Industrial Control System compromise. We came away with insight into their TapleTop exercises. CISA Tabletop Exercise Packages (CTEPs) are a comprehensive set of resources designed to assist stakeholders in conducting their own exercises. Each package is customizable and includes template exercise objectives, scenarios, and discussion questions as well as a collection of references and resources. Available scenarios cover a broad array of physical security and cybersecurity topics, such as natural disasters, pandemics, civil disturbances, industrial control systems, election security, ransomware, vehicle ramming, insider threats, active assailants, and unmanned aerial systems. CTEPs also provide scenario and module questions to discuss pre-incident information and intelligence sharing, incident response, and post-incident recovery.
These CTEPs include cybersecurity-based scenarios that incorporate various cyber threat vectors including ransomware, insider threats, phishing, and Industrial Control System (ICS) compromise. There are also sector-specific cybersecurity scenarios for elections infrastructure, local governments, maritime ports, water, and healthcare. CISA also covered physical impacts resulting from a cyber threat vector, or cyber impacts resulting from a physical threat vector.

ALPS ALPINE LABS
Based in Japan, Alps #AlpineLabs has a long history of developing electrical and electronics components for consumer markets. Its sweets pot has long been in the automotive industry where it focus on

functional in-car interactive surfaces, cabin controllers, infotainment systems among others. Advances in automated driving and electrification hint at the gathering pace of the once-in-a-century major transformation underway in the world of automobiles and solutions are being sought to address the challenges of a new age. Alps Alpine recently developed a capacitive display panel – the next-generation human-machine interface (HMI) product enabling smart, intuitive control through hovering and gesture operation and vibrational feedback. For the connected car domain, where vehicles are incorporated within aIoT network, Alpine Labs has deployed 5G communication modules for automotive use with C-V2X features. In the AV space, the company focuses on cabin monitoring solutions which make use of cameras and sensors to monitor the driver and passengers from the moment they board the vehicle to enhance their safety and comfort both while driving normally or when operating in autonomous mode. For the mobility-as-a-service (MaaS) markets, Alpine offers digital key system useful for car sharing and corporate fleet management. The system makes it possible to lock and unlock doors, start the engine and manage vehicles efficiently using smartphones in place of car keys. For the broader EV space, Alps Alpine has developed an acoustic vehicle alerting system (AVAS), a technology now mandated for electric and hybrid vehicles. Incorporating expertise built up through involvement with audio products, the system generates a natural and optimal sound matching the specific characteristics of the particular vehicle model. For electric vehicles, which have no engine, road noise cancellation technology cancels out noise caused by vibrations from contact with the road surface while driving, realizing a quiet, comfortable mobility environment where occupants can savor the entertainment.

APPTIO
#Apptio provides cloud cost management and optimization tools for enterprise IT infrastructures. Part of IBM the company supports a very critical often overlooked aspect of IT investments. The new technology

waves (including cloud and AI) have vastly increased the cost base and complexity of IT infrastructures. The complexity isn’t limited to innovation in software and hardware. The expansion of diverse technology footprints increases cybersecurity risk and invites further regulatory compliance and governance considerations. There’s also the matter of shifting from CapEx to OpEx and variable spend models along with decentralized provisioning, making spend less predictable. it’s easy to see how costs can quickly spiral out of control. How do enterprises manage around such a vast and multi-faceted technology footprint. Despite the promise of cloud, including scale, security, flexibility, and faster innovation cycles a vast majority of enterprises do not have clarity on ROI’s from their cloud transformation initiatives. Company leadership wants to see performance, not just technical performance of the solution but positive outcomes for the business. Tying investments to outcomes when operational and financial data is spread across a multitude of systems and business units can feel like a monumental task. It gets more challenging still when you’re trying to connect technology spend to key corporate objectives like operational efficiency, agility, resiliency, risk reduction, or revenue.
Apptio’s Technology Business Management (TBM) and FinOps tools provide its customers a way to efficiently collect operational and financial data from across the enterprise and, importantly, translate that data into terms that stakeholders across the business can understand in terms of outcomes..

EUROFINS MET LABS
#Eurofins MET Labs provides product safety approvals and regulatory certification of electrical products. The MET Mark for product safety is accepted throughout the United States & Canada and indicates

compliance to required standards by virtue of Eurofins ‘ equivalent NRTL accreditations to UL, a better recognized brand in the United States. While UL and MET marks both indicate that the product has met the minimum requirements of the applicable safety standard and both marks validate the product’s continued compliance to these standards as evidenced by periodic factory follow-up inspections, they do differ in a few aspects. MET Labs has so far evaluated a wide range of industry products ranging from Telecom equipment, Food processing equipment, Computers, Gas detectors, Hazardous location equipment, Air conditioners, Washing machines, Blenders, Power tools, Medical equipment, Home audio equipment, among others.

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FRAUNHOFER USA
#Fraunhofer is an organization dedicated to the advancement of applied research. It works closely with Fraunhofer-Gesellschaft, Europe’s largest application-oriented research and development organization.

Franhofer leads strategic research in many fields – generative AI research in Germany and Europe, Bioeconomy, Digital Healthcare, Artificial Intelligence (AI), Next Generation Computing, Quantum Technologies, Resource Efficiency and Climate Technologies.
ArcInsight Parrners has had many interactions with Fraunhofer Institues at Europe’s flagship industrial showcase event Hannover Messe. Over the years we have become familiar with Fraunhofer’s advances in factory of the Future, Trustworthy AI, Robotocs, Autonomous Vehicle design and failure prediction, GenAI based machine control using speech recognition, Ammonia based renewable energy systems, and many others.

LIGHTNING AI
Lightning AI is the company behind PyTorch Lightning, the deep learning framework for training, finetuning and serving AI models. In 2019 PyTorch Lightning started to be used to train huge models on 1024+ GPUs inside Facebook AI. in 2020 as a platform to train models on the cloud across 1000s of GPUs. Today, the platform has evolved to a fully end-to-end platform covering everything from distributed data processing, training, finetuning foundation models, to serving and deploying AI apps. he compan plas in same marketspace as MATLAB, Alteryx, Posit, SAP HANA Cloud and Domo, MosaicML, Dataspark, among others.

OPTIMAL DESIGN
Based in Chicago, Optimal Design provides idea-to-reality services that include industrial design, hardware engineering, embedded software, connectivity and rapid prototyping. The company was established in 2003 and has served customers ranging from Fortune 500 companies to start-up businesses across areas that include consumer and industrial electronics, medical devices, consumer-durables and automotive. The product engineering services (PES) company specializes in the innovation and development of smart connected products and internet of things (IoT) devices. engineering capabilities, including a broad skill set that enables opportunity for clients across the innovation spectrum — from product-ideation to physical prototype development.

SALVENTURE TECH
An interesting new venture that provides Industrial IoT consulting and development services in the specialized process control space. The services provided by this company go to the heart of any major industrial control system within any manufacturing/process facility including plants, oil refineries, water treatment utilities, power generation and transmission, among many others. With the teams expertise in PLC and SCADA systems and support in the field of industrial automation, this company programs PLCs (Programmable Logic Controller) to control and automate manufacturing processes, and SCADA systems (Supervisory Control and Data Acquisition) thatl collect and analyze real-time data from various industrial devices.

SPARKBEYOND
#SparkBeyond empowers organizations to solve their most complex challenges with AI-powered problem-solving. Its platform offers unparalleled productivity and efficiency by automatically analyzing a variety of

structured, disparate, first and third-party data to generate millions of hypotheses in minutes, instead of months. The technology collapses time to value, it’s designed to tackle the bias inherent in human thinking, so that the platform’s ideations run in a multitude of directions, providing a variety of ideas, including many that clients would never have considered on their own.
The company has developed a problem-solving research platform designed to generate concrete solutions to specific business problems such as where to locate a new store, how to make quicker deliveries, or when to cut or raise prices and by how much. It works, in part, by detecting complex patterns in large pools of data and formulating an array of possible strategies. SparkBeyond’s Discovery platform tests millions of algorithmic hypotheses pulled automatically from online libraries of open-source code like GitHub. While the platform can be applied to a company’s own data, it can also draw information from a sprawling network of billions of webpages across the internet, including Wikipedia, news sites, weather maps, scientific papers, economic studies, patents and other sources. SparkBeyond automatically augments this core data with vast repositories of collective human knowledge, allowing both data scientists and business owners to see the bigger picture with an expanded and enriched scope of insights. The Hypothesis Engine in the SparkBeyond platform autonomously analyzes data to generate insights and composite features, discover patterns, or hook datasets together. By gathering, sorting and cross-referencing all this material in real time, SparkBeyond is able to “connect the dots in disparate data sets and information spread across the web and generate solutions. Thus pattern and insight discovers becomes an autonomous process.To help corporate decision makers assess the solutions, every idea is assigned a credibility score based on the range of data that supports it.
Its Research Studio product aggregates and synthesizes billions of web pages and external data. It then identifies current risk signals and anticipate emerging events thereby delivering near-real-time prescriptive intelligence on the global strategic, economic and social risk issues most relevant to your organization.

SOME OBSERVATIONS
As long time attendees of Tech Expo’s global events, one remembers six individual annual expo events held separately, and taking over the entire Santa Clara venue capacity on their own. IoT, Cloud Computing, CyberSecurity, Blockchain, Big Data, Unified Communications, Intelligent Automation, Digital Transformation and Edge Computing Expo. The events are scheduled annually across Santa Clara, London & Amsterdam each of which attracts sizeable crowds of tech enthusiasts and practitioners, and sponsoring companies. Each of those events no doubt tracked the latest technology bandwagon and sought to drum up excitement and exposure for newly minted experts in the field and newly tagged tech pioneers in the space.

Over the years as the bandwagon has moved on to newer more exciting directions – most recently AI & GenAI, attendees have transferred their professional time and attention to these new emerging spaces. While this in no way lessens the immense economic impact and new technological knowledge generation each wave brings to its customers and to the industry, in fact the real value creation and monetization possibilities are happening as we speak. While the big name speakers and crowd magnets have been lured over to the other attractions, it has also opened doors for pseudo-experts to get their 15 minutes of fame on stage. Sponsor companies who are the lifeblood of such conferences clearly observe changes and use this opportunity to field their second (or third) rung managers and employees to make marketing pitches on behalf of their companies.

For the events businesses such as Tech Expo, this obviously means a tapering off of attendee crowds (now limited to practitioners and a collection of tech diehards), content programming challenges, attracting name recognized speakers, managing content quality, while balancing the cost of hosting such shows every year.

At the 2024 Tech Expo in Santa Clara, we were presented with an ensemble of mini-versions of the annual events all present at the same venue. This no doubt presented attendees with a wider range of technologies to observe and content to absorb. The tradeoff with this approach for event organizers is between losing the overarching conference theme that usually defines a tone for such events, and affording economies of scale from dwindling attendee trends by clustering multiple events at one venue. There are of course both advantages and disadvantages for attendees and sponsors.

About the author
Praas Chaudhuri is CEO & Principal Industry Analyst supporting Industrial Autonomy, Intelligent Cities and the broader Digital Transformation markets. The firm’s research scope covers most major equipment companies in industrial manufacturing, mining, process automation, as well as software, hardware, satellite imaging and other innovative technology players focused on building AI-enabled applications to support industrial use-cases. Based in Silicon Valley, Praas is a former strategy consultant with several additional stints in corporate planning & strategy roles at large manufacturing and technology companies. He can be reached at pchaudhuri@arcinsightpartners.com

About ArcInsight Research
ArcInsight Research works with leading global industrial companies involved in smart city infrastructure, process equipment, control software and hardware, design, simulation, operations, optimization. It is deeply plugged into the technology ecosystem – bleeding-edge startups and the investor community.

The group was founded in 2010 by consulting firm partners and senior experienced executives with deep global experience in industrial domain research, strategy consulting, technology and and investment banking. The firm aims to equip senior industry leaders with tools and perspectives to view the bigger picture and longer term over-the-horizon opportunities, and also support their strategy with a tangible path to execution.

The strategy advisory approach offered by ArcInsight Partners is a valuable partnership opportunity for enterprises that may be either starting out on the digital transformation journey, in the midst of of transformation and looking for fresh perspectives to position themselves for a highly connected algorithm driven world.

Some of our past advisory engagements have included assisting clients –
– Validate transformation goals and its transformation journey
– Assess new target markets; Validate TAM and growth rates
– Validate drivers for new business model; Transition strategy to SaaS / Subscription models
– Design new service opportunities
– Build monetization and revenue models;
– Map in-house competencies; Sales strategy and key account coverage
– Structure appropriate partner ecosystems for effective value delivery
– Due-diligence for potential acquisition & partnership targets; Assess deal valuations