Forbes readers’ most frequent requests center on which companies are the best to work for in emerging technology fields, including IoT. The Computer Reseller News’ Internet of Things 50, 2019 list of companies is used to complete the analysis as it is an impartial, independent list created by CRN. Using the CRN list as a foundation, the following analysis captures the best companies in their respective areas today.
IoT startups have received $3.6B in funding this year alone, according to IoT Analytics’ estimates.
Manufacturing is attracting the highest percentage of vertically-focused IoT startups at 30%.
43% of all IoT startups are founded in North America, the leading region globally of startup activity.
7 of the top 10 IoT startups primarily focus on AI, Analytics, and Data Science.
46% of all IoT startups tracked by IoT Analytics primarily focus on AI, Analytics, and Data Science.
These and many other fascinating insights are from IoT Analytics’ recently published IoT Startups Report & Database 2019. IoT Analytics found that there approximately 1,018 startups creating Internet of Things (IoT) products or services today. They have defined one of the most thorough methodologies in IoT research to identify the top 10 IoT analytics startups worldwide. To qualify, startups have to be older than 6 years and fit the definition of the Internet of Things, and methodology and criterion explained at the end of this post.
“The hot IoT startups today have a strong focus on data analytics and AI and are increasingly targeting industrial and manufacturing clients. It remains to be seen how much of the analytics technology that today’s startups are building will be scalable across IoT use cases and industries. For now, most of the IoT startups are adding value in specific industries or for specific use cases,” said Knud Lasse Lueth, Managing Director of IoT Analytics.
The following are the top 10 IoT Startups Of 2019 from IoT Analytics:
Arundo Analytics is a hot IoT Startup that provides analytics software for industrial and energy companies. The company has formed several strategic alliances, e.g., with Dell Technologies and WorleyParsons. Arundo has also formed a joint venture with DNV GL to provide stream data analytics for maritime companies. The board of directors includes Tore Myrholt, Senior Partner at McKinsey and Thomas Malone, the founding director of the MIT Center for Collective Intelligence. Recently, Arundo launched several applications incl. machine monitoring and fuel efficiency.
Bright Machines is currently the fastest growing IoT Startup, has grown from virtually zero at the beginning of 2018 to almost 200 employees a year later (April 2019). The firm focuses on “micro-factories” made up of its software and robot cells as well as new software tools that make manufacturing more efficient. The leadership team is filled with former executives from Autodesk, Flextronics, and Amazon including Amar Hanspal (CEO), Brian Mathews (CTO), Tzahi Rodrig (COO) and Nick Ciubotariu (SVP, Software Engineering). The company recently entered into a strategic partnership with BMW i Ventures.
Dragos (IoT Middleware & Software Infrastructure)
Dragos is a cybersecurity startup that offers a software-defined security platform for manufacturers. The company has seen a 300%+ growth in headcount the last two years and collaborates with GE, Deloitte, OSIsoft, ThreatConnect, Crowdstrike, and several other companies. The company recently acquired Atlanta-based NexDefense and collaborates with Waterfall Solution for a joint solution.
Element (IoT Middleware & Software Infrastructure)
Element (also known as Element Analytics) is a fascinating IoT Startup that focuses on industrial analytics software such as Digital Twins, particularly in heavy industries. The company counts an impressive list of investors, including Kleiner Perkins, GE, Honeywell, and ABB. Element partners with Microsoft, Uptake, OSIsoft, and Radix (consulting).
In recent years, US-based startup FogHorn has gained an excellent reputation with leading manufacturers and oil and gas organizations around the world for its real-time edge computing and analytics software. The company has seen an 89% employee growth in the past two years and has secured partnerships with 50+ industrial solution providers, OEMs, gateway providers, and consultants/SIs, including AWS, Google Cloud, Microsoft, Cisco, HP, NTT Data, and more. FogHorn is also a member of LF Edge, an umbrella organization to drive an open, interoperable framework for edge computing to accelerate deployment among the growing number of edge devices. Investors in FogHorn include The Hive, Bosch, Dell, GE, Honeywell, Intel, Saudi Aramco, and Yokogawa.
Iguazio is a hot startup that provides a state-of-the-art data science platform for various verticals, including Industrial IoT, Smart Mobility, and Telecommunications. The company recently entered into collaborations with NVIDIA, Microsoft, and Google. Iguazio markets its Nuclio platform product as a “serverless” framework for multi-cloud environments and is thus well-positioned for the next wave of cloud computing.
IoTium (IoT Connectivity)
IoTium is a quickly upcoming IoT startup from the Silicon Valley area that focuses on software-defined network infrastructure in manufacturing and related verticals. The company has seen a 100%+ growth in headcount over the last two years and now counts John Chambers, former Cisco CEO, as an investor along with other well-known corporate investors incl. Juniper, Qualcomm, SafeNet, and Wind River. The company is also very active in the EdgeX Foundry and recently joined the Siemens’ MindSphere partner program as a gold member.
Preferred Networks is one of Japan’s IoT hotshots, focused on applying real-time machine-learning technologies to new Internet of Things applications. The company has seen a 100%+ employee growth in the last two years and now collaborates with world-leading organizations incl. Toyota Motor Corporation, Fanuc, and the National Cancer Center. The company is also very active in developing the deep-learning framework Chainer™ together with IBM, Intel, Microsoft, Nvidia.
READY Robotics (IoT Hardware)
READY Robotics is a rare robotics startup that is looking to benefit from the increasing automation and flexibility of manufacturing processes around the world. The company emerged from the cutting-edge robotics research at Johns Hopkins University to develop its industrial robotic software called Forge. The company has seen a 150%+ growth in headcount in the last two years and is now producing roughly 15 robot systems per month.
SparkCognition excels in AI-powered analytics, particularly in manufacturing and related verticals. SparkCognition has seen a 100%+ growth in headcount over the last two years. The company has launched Skygrid, a joint venture with Boeing and it has partnered with Siemens as part of its Mindsphere program. The company is also a Google Cloud Technology Partner and works with IBM as a trusted partner.
The full 62-page report (+ 1,018 line-item database) titled “IoT Startups Report & Database 2019” is available for purchase here.
Global spending on IIoT Platforms for Manufacturing is predicted to grow from $1.67B in 2018 to $12.44B in 2024, attaining a 40% compound annual growth rate (CAGR) in seven years.
IIoT platforms are beginning to replace MES and related applications, including production maintenance, quality, and inventory management, which are a mix of Information Technology (IT) and Operations Technology (OT) technologies.
Connected IoT technologies are enabling a new era of smart, connected products that often expand on the long-proven platforms of everyday products. Capgemini estimates that the size of the connected products market will be $519B to $685B by 2020.
These and many other fascinating insights are from IoT Analytics’ study, IIoT Platforms For Manufacturing 2019 – 2024 (155 pp., PDF, client access reqd). IoT Analytics is a leading provider of market insights for the Internet of Things (IoT), M2M, and Industry 4.0. They specialize in providing insights on IoT markets and companies, focused market reports on specific IoT segments and Go-to-Market services for emerging IoT companies. The study’s methodology includes interviews with twenty of the leading IoT platform providers, executive-level IoT experts, and IIoT end users. For additional details on the methodology, please see pages 136 and 137 of the report. IoT Analytics defines the Industrial loT (lloT) as heavy industries including manufacturing, energy, oil and gas, and agriculture in which industrial assets are connected to the internet.
The seven things you need to know about IIoT in manufacturing include the following:
IoT Analytics’ technology architecture of the Internet of Things reflects the proliferation of new products, software and services, and the practical needs manufacturers have for proven integration to make the Industrial Internet of Things (IIoT) work. IoT technology architectures are in their nascent phase, showing signs of potential in solving many of manufacturing’s most challenging problems. IoT Analytics’ technology architecture shown below is designed to scale in response to the diverse development across the industry landscape with a modular, standardized approach.
IIoT platforms are beginning to replace MES and related applications, including production maintenance, quality, and inventory management, which are a mix of Information Technology (IT) and Operations Technology (OT) technologies. IoT Analytics is seeing IIoT platforms begin to replace existing industrial software systems that had been created to bridge the IT and OT gaps in manufacturing environments. Their research teams are finding that IIoT Platforms are an adjacent technology to these typical industrial software solutions but are now starting to replace some of them in smart connected factory settings. The following graphic explains how IoT Analytics sees the IIoT influence across the broader industrial landscape:
Global spending on IIoT Platforms for Manufacturing is predicted to grow from $1.67B in 2018 to $12.44B in 2024, attaining a 40% compound annual growth rate (CAGR) in seven years. IoT Analytics is finding that manufacturing is the largest IoT platform industry segment and will continue to be one of the primary growth catalysts of the market through 2024. For purposes of their analysis, IoT Analytics defines manufacturing as standardized production environments including factories, workshops, in addition to custom production worksites such as mines, offshore oil gas, and construction sites. The lloT platforms for manufacturing segment have experienced growth in the traditionally large manufacturing-base countries such as Japan and China. IoT Analytics relies on econometric modeling to create their forecasts.
In 2018, the industrial loT platforms market for manufacturing had an approximate 60%/40% split for within factories/outside factories respectively. IoT Analytics predicts this split is expected to remain mostly unchanged for 2019 and by 2024 within factories will achieve slight gains by a few percentage points. The within factories type (of lloT Platforms for Manufacturing) is estimated to grow from a $1B market in 2018 to a $1.5B market by 2019 driven by an ever-increasing amount of automation (e.g., robots on the factory floor) being introduced to factory settings for increased efficiencies, while the outside factories type is forecast to grow from $665M in 2018 to become a $960M market by 2019.
Discrete manufacturing is predicted to be the largest percentage of Industrial IoT platform spending for 2019, growing at a CAGR of 46% from 2018. Discrete manufacturing will outpace batch and process manufacturing, becoming 53% of all IIoT platform spending this year. IoT Analytics sees discrete manufacturers pursuing make-to-stock, make-to-order, and assemble-to-order production strategies that require sophisticated planning, scheduling, and tracking capabilities to improve operations and profitability. The greater the production complexity in discrete manufacturing, the more valuable data becomes. Discrete manufacturing is one of the most data-prolific industries there are, making it an ideal catalyst for IIoT platform’s continual growth.
Manufacturers are most relying on IIoT platforms for general process optimization (43.1%), general dashboards & visualization (41.1%) and condition monitoring (32.7%). Batch, discrete, and process manufacturers are prioritizing other use cases such as predictive maintenance, asset tracking, and energy management as all three areas make direct contributions to improving shop floor productivity. Discrete manufacturers are always looking to free up extra time in production schedules so that they can offer short-notice production runs to their customers. Combining IIoT platform use cases to uncover process and workflow inefficiencies so more short-notice production runs can be sold is driving Proof of Concepts (PoC) today in North American manufacturing.
IIoT platform early adopters prioritize security as the most important feature, ahead of scalability and usability. Identity and Access Management, multifactor-factor authentication, consistency of security patch updates, and the ability to scale and protect every threat surface across an IIoT network are high priorities for IIoT platform adopters today. Scale and usability are the second and third priorities. The following graphic compares IIoT platform manufacturers’ most important needs:
99% of mid-market manufacturing executives are familiar with Industry 4.0, yet only 5% are currently implementing or have implemented an Industry 4.0 strategy.
Investing in upgrading existing machinery, replacing fully depreciated machines with next-generation smart, connected production equipment, and adopting real-time monitoring including Manufacturing Execution Systems (MES) are manufacturers’ top three priorities based on interviews with them.
Mid-market manufacturers getting the most value out of Industry 4.0 excel at orchestrating a variety of technologies to find new ways to excel at product quality, improve shop floor productivity, meet delivery dates, and control costs.
Real-time monitoring is gaining momentum to improve order cycle times, troubleshoot quality problems, improve schedule accuracy, and support track-and-trace.
These and many other fascinating insights are from Industry 4.0: Defining How Mid-Market Manufacturers Derive and Deliver Value. BDO is a leading provider of assurance, tax, and financial advisory services and is providing the report available for download here (PDF, 36 pp., no opt-in). The survey was conducted by Market Measurement, Inc., an independent market research consulting firm. The survey included 230 executives at U.S. manufacturing companies with annual revenues between $200M and $3B and was conducted in November and December of 2018. Please see page 2 of the study for additional details regarding the methodology. One of the most valuable findings of the study is that mid-market manufacturers need more evidence of Industry 4.0, delivering improved supply chain performance, quality, and shop floor productivity.
Insights from the Shop Floor: Machine Upgrades, Smart Machines, Real-Time Monitoring & MES Lead Investment Plans
In the many conversations I’ve had with mid-tier manufacturers located in North America this year, I’ve learned the following:
Their top investment priorities are upgrading existing machinery, replacing fully depreciated machines with next-generation smart, connected production equipment, and adopting real-time monitoring including Manufacturing Execution Systems (MES).
Manufacturers growing 10% or more this year over 2018 excel at integrating technologies that improve scheduling to enable more short-notice production runs, reduce order cycle times, and improve supplier quality.
Key Takeaways from BDO’s Industry 4.0 Study
Manufacturers are most motivated to evaluate Industry 4.0 technologies based on the potential for growth and business model diversification they offer. Building a business case for any new system or technology that delivers revenue, even during a pilot, is getting the highest priority by manufacturers today. Based on my interviews with manufacturers, I found they were 1.7 times more likely to invest in machine upgrades and smart machines versus spending more on marketing. Manufacturers are very interested in any new technology that enables them to accept short-notice production runs from customers, excel at higher quality standards, improve time-to-market, all the while having better cost visibility and control. All those factors are inherent in the top three goals of business model diversification, improved operational efficiencies, and increased market penetration.
For Industry 4.0 technologies to gain more adoption, more use cases are needed to explain how traditional product sales, aftermarket sales, and product-as-a-service benefit from these new technologies. Manufacturers know the ROI of investing in a machinery upgrade, buying a smart, connected machine, or integrating real-time monitoring across their shop floors. What they’re struggling with is how Industry 4.0 makes traditional product sales improve. 84% of upper mid-market manufacturers are generating revenue using Information-as-a-Service today compared to 67% of middle market manufacturers overall.
Manufacturers who get the most value out of their Industry 4.0 investments begin with a customer-centric blueprint first, integrating diverse technologies to deliver excellent customer experiences. Manufacturers growing 10% a year or more are relying on roadmaps to guide their technology buying decisions. These roadmaps are focused on how to reduce scrap, improve order cycle times, streamline supplier integration while improving inbound quality levels, and provide real-time order updates to customers. BDOs’ survey results reflect what I’m hearing from manufacturers. They’re more focused than ever before on having an integrated engagement strategy combined with greater flexibility in responding to unique and often urgent production runs.
Industry 4.0’s potential to improve supply chains needs greater focus if mid-tier manufacturers are going to adopt the framework fully. Manufacturing executives most often equate Industry 4.0 with shop floor productivity improvements while the greatest gains are waiting in their supply chains. The BDO study found that manufacturers are divided on the metrics they rely on to evaluate their supply chains. Upper middle market manufacturers are aiming to speed up customer order cycle times and are less focused on getting their total delivered costs down. Lower mid-market manufacturers say reducing inventory turnover is their biggest priority. Overall, strengthening customer service increases in importance with the size of the organization.
By enabling integration between engineering, supply chain management, Manufacturing Execution Systems (MES) and CRM systems, more manufacturers are achieving product configuration strategies at scale. A key growth strategy for many manufacturers is to scale beyond the limitations of their longstanding Make-to-Stock production strategies. By integrating engineering, supply chains, MES, and CRM, manufacturers can offer more flexibility to their customers while expanding their product strategies to include Configure-to-Order, Make-to-Order, and for highly customized products, Engineer-to-Order. The more Industry 4.0 can be shown to enable design-to-manufacturing at scale, the more it will resonate with senior executives in mid-tier manufacturing.
Manufacturers are more likely than ever before to accept cloud-based platforms and systems that help them achieve their business strategies faster and more completely, with analytics being in the early stages of adoption. Manufacturing CEOs and their teams are most concerned about how quickly new applications and platforms can position their businesses for more growth. Whether a given application or platform is cloud-based often becomes secondary to the speed and time-to-market constraints every manufacturing business faces. The fastest-growing mid-tier manufacturers are putting greater effort and intensity into mastering analytics across every area of their business too. BDO found that Artificial Intelligence (AI) leads all other technologies in planned use.
85% of enterprises who develop deep expertise with IoT succeed at driving revenue faster than competitors.
81% of enterprises say Artificial Intelligence streamlines interpreting and taking action on data insights gained from IoT systems and sensors.
68% of enterprises are using IoT to track the security of physical assets, making this use case the most common across enterprises today.
Transport & Logistics and Manufacturing & Industrials saw the most significant increase in adoption between 2018 and 2019.
These and many other fascinating insights are from the 6th annual Vodafone IoT Barometer, 2019. The entire report can be downloaded here (PDF, 32 pp., e-mail opt-in). The methodology is based on 1,758 interviews distributed across the Americas (22%), EMEA (49%) and Asia-Pacific (29%). Eight vertical markets were included with manufacturing (22%), healthcare and wellness (14%) and retail, leisure, and hospitality (14%) being the three most represented markets. Vodaphone is making an interactive tool available here for exploring the results.
Key insights from Vodafone’s 2019 IoT Barometer include the following:
34% of global businesses are now using IoT in daily operations, up from 29% in 2018, with 95% of IoT adopters are already seeing measurable benefits. 81% of IoT adopters say their reliance on IoT has grown, and 76% of adopters say IoT is mission-critical to them. 58% are using analytics platforms to get more insights from their IoT data to improve decision making. 71% of enterprises who have adopted IoT expect their company and others like them will start listing data resources on their balance sheets as assets within five years.
95% of enterprises adopting IoT are achieving tangible benefits and positive ROI. 52% of enterprises report significant returns on their IoT investments. 79% say IoT is enabling positive outcomes that would have been impossible without it, further reflecting robust growth in the enterprise. Across all eight vertical markets reducing operating costs (53%) and gaining more accurate data and insights (48%) are the most common benefits. Transitioning an IoT pilot to production based on cost reduction and improved visibility creates a compelling ROI for many enterprises. The following graphic compares IoT’s benefits to enterprises. Please click on the graphic to expand for easier reading.
Transport & Logistics and Manufacturing & Industrials saw the greatest increase in adoption between 2018 and 2019. Transport and Logistics had the highest IoT adoption rate at 42% followed by Manufacturing and Industrials at 39%. Manufacturers are facing the challenges of improving production efficiency and product quality while accelerating time-to-market for next-generation smart, connected products. IoT contributes to productivity improvements and creates opportunities for services-based business models, two high priorities for manufacturers in 2019 and beyond. The following graphic from the interactive tool compares IoT adoption by industry based on Vodaphone’s IoT barometer data over the last six years:
89% of most sophisticated enterprises have multiple full-scale projects in production, orchestrating IoT with analytics, AI and cloud, creating a technology stack that delivers real-time insights. Enterprises who lead IoT adoption in their industries rely on integration to gain scale and speed advantages quickly over competitors. The greater the real-time integration, the greater the potential to digitally transform an enterprise and remove roadblocks that get in the way of growing. 95% of adopters where IoT is fully integrated say it’s enabling their digital transformation, compared with 55% that haven’t started integration. The following graphics reflect how integrated enterprises’ IoT projects are with existing business systems and processes and the extent to which enterprises agree that IoT is enabling digital transformation.
68% of enterprises are using IoT to track the security of physical assets, making this use case the most common across enterprises today. 57% of all enterprises are using IoT to manage risk and compliance. 53% are using it to increase revenue and cut costs, with 82% of high performing enterprises rely on IoT to manage risk and compliance. The following graphic compares the types of variables enterprises are using IoT to track today and plan to in the future.
IoT adoption is soaring in Americas-based enterprises, jumping from 27% in 2018 to 40% in 2019. The Americas region leads the world in terms of IoT usage assessed by strategy, integration, and implementation of IoT deployments. 73% of Americas-based enterprises are the most likely to report significant returns from their IoT investments compared to 47% for Asia-Pacific (APAC) and 45% for Europe, Middle East and Africa (EMEA).
52% of IoT-enabled enterprises plan to use 5G when it becomes available. Enterprises are looking forward to 5G’s many advantages including improved security via stronger encryption, more credentialing options, greater quality of service management, more specialized services and near-zero latency. Vodafone predicts 5G will be a strong catalyst of growth for emerging IoT applications including connected cars, smart cities, eHealth and industrial automation.
IoT Leaders are achieving cost and revenue gains of at least 15% or more, while laggards see less than 5%.
Pursuing 80% more IoT use cases compared to their peers, IoT Leaders are progressing faster down the learning curve of monetizing their application areas.
IoT Leaders anticipate that their IoT use cases will boost their gross profits by 13% over the next three years, three times as much as IoT laggards.
What IoT leaders do to excel and drive greater results compared to their peers is explored in the recent McKinsey report, What separates leaders from laggards in the Internet of Things. The study is based on interviews with 300 IoT executive-level practitioners from companies with more than $500M revenues which are implementing large-scale IoT strategies with projects that have progressed from pilot to production. Enterprises from 11 major industry segments from Canada, China, Germany, and the United States were included in the survey.
McKinsey found 16% of enterprises have IoT programs in production, delivering aggregate cost and revenue impacts of at least 15%. The study also found 16% of enterprises are lagging, attaining aggregate revenue and cost improvements of less than 5%. The following graphic compares companies by the level of financial impact from IoT initiatives:
Nine practices differentiate IoT Leaders from laggards, and the study provides a fascinating look into each based on the survey data. Key insights into IoT Leader’s practice areas is provided here:
Leaders are more aggressive about pursuing a greater number, scope, and variety of IoT applications and use cases than their less successful peers. What IoT Leaders learn quickly is how steep the IoT learning curve is, and how it’s essential to run as many IoT pilots as possible to learn more. Leaders discover the first 15 or so IoT use cases typically have a modest payback, with the average payback rising until approximately 30 use cases have been achieved. IoT Leaders anticipate that their IoT use cases will boost their gross profits by 13% over the next three years, three times as much as IoT laggards. The following graphic illustrates the financial impact per IoT use case by the cumulative number of IoT use cases enterprises initiate.
Leaders are more willing than their peers to change business processes to unlock IoT’s value. McKinsey found IoT Leaders are three times more likely than their peers to say that managing changes to business processes is one of the three most important capabilities for implementing IoT. CEOs who champion their company’s IoT initiatives make strong contributions in this area, removing barriers and roadblocks quickly to keep IoT programs moving forward.
Leaders design, pilot and move to production IoT use cases that rely on advanced endpoints far more than their peers. McKinsey finds that IoT Leaders are more visionary and aggressive than peers in developing applications with advanced endpoints. Leaders are gaining expertise and mastery of how to creatively use advanced endpoints today, reporting higher levels of satisfaction and positive results.
Leaders clearly define how IoT will create value and excel in building effective business cases. McKinsey found that IoT Leaders are 75% more likely than their peers to cite the preparation of a strong business case as a critical success factor for their IoT programs. The study’s respondents who have an IoT vision that includes a strong value proposition, a proven delivery model, and a business model that drives revenue are getting results faster than their peers. 35% of Leaders rate the importance of “strong business case and vision for value creation” as one of the top three success factors versus 20% of laggards. Leaders leave nothing to chance when it comes to defining how IoT will deliver business value either in the form of greater revenue or reduced costs.
A CEO’s involvement and support are essential for any enterprise to succeed with IoT. Based on personal experience with IoT pilots, C-level executives are indispensable in removing barriers and making process-level changes necessary for success. 72% of the surveyed executives agree. A vital catalyst of any enterprise succeeding with IoT is a clear, unequivocal time commitment on the part of the CEO. Enterprises in the Leaders quintile were 2.4 more likely than laggards to report that their CEO serves as the champion of IoT efforts as the following graphic illustrates:
Leaders credit strong alignment with IoT strategies and priorities enterprise-wide as a critical factor in their success. IoT initiatives and pilots on their way to production require executives, managers, and frontline workers to learn fresh skills and collaborate across business and functional boundaries in new ways. Enterprises need to have a strong unifying vision of where they’re going with IoT, with the CEO championing the change management required to make sure they succeed.
Leaders begin by adding IoT capability to existing products and services first. McKinsey found that Leaders are three times more likely than their peers to make their top priority adding IoT capabilities to existing products. They focus on how to turn the current scale they’ve achieved with suppliers, selling and service networks into a formidable competitive advantage. They’re also more adept at cross-selling and up-selling IoT-enabled products by capitalizing on current customer relationships. The following graphic compares enterprises’ single highest-priority IoT effort:
Leaders excel at tapping into, scaling and relying on an ecosystem of partners for innovation versus doing it all themselves. McKinsey finds that IoT Leaders excel at scaling their partner ecosystems faster and more strategically than their peers. IoT Leaders also rely more on partners for the latest technology innovations instead of attempting to create them entirely on their own. They’re also deliberately choosing IoT platforms that support third-party developers and the advanced endpoints as the graphic below shows:
Leaders prepare for cyber attacks, so they don’t slow things down. McKinsey found that 30% of enterprises from both IoT Leaders and their peers say that they’ve experienced cyber attacks that have resulted in high to severe damage. 57% of Leaders had been the target of cyber attacks compared to 44% of their peers. The higher number of cyber attacks happening for Leaders is due to the broader threat surface their many pilots, and production-level use cases create. The more distributed and varied IoT use cases are the greater the risk of privileged credential abuse as well. Thwarting privileged credential abuse needs to start with a least privilege access approach, minimizing each attack surface, improving audit and compliance visibility while reducing risk, complexity, and costs. Leaders in Zero Trust include Centrify, MobileIron, Palo Alto Networks, and others.
26,792 startups are relying on IoT as one of their main technologies to launch new products and services and support platform-based business models according to Crunchbase.
78.4% of IoT startups Crunchbase tracks have had two funding rounds or less with seed, angel and early-stage rounds being the most common.
IoT startup funding reached $16.7B in Q4, 2018, with last years’ funding levels 94% over 2017 according to Venture Scanner.
By 2020, 50% of IoT spending will be driven by discrete manufacturing, transportation and logistics, and utilities according to the Boston Consulting Group.
The most successful IoT startups selling into enterprises excel at orchestrating analytics, Artificial Intelligence (AI), and real-time monitoring to deliver exceptional customer experiences. As a group, these top 25 IoT startups are showing early potential at enabling profitable new business models, revitalizing industries that have experienced single single-digit growth recently. Each of these startups is taking a unique approach to solving some of the enterprises’ most challenging problems, and in so doing creating valuable new patents that further fuel IoT adoption and growth.
The top 25 startups are concentrating on how to make IoT a growth catalyst for enterprises by designing in AI integration at the platform level. McKinsey found that 27% of AI early adopters are more likely to report using AI to grow their market than companies only experimenting with or partially adopting AI. 52% are more likely to report using it to increase their market share. These and many other survey results are from McKinsey Global Institute’s Artificial Intelligence: The Next Digital Frontier? (PDF, 80 pp., no opt-in).
Top 25 IoT Startups To Watch In 2019
The following list of 25 IoT startups are based on an analysis of their ability to attract new customers, current and projected revenue growth, patents’ current value and potential, and position in their chosen markets. Presented below are the top 25 IoT startups to watch this year:
Armis Security – Armis takes a unique approach to provide visibility into IoT-enabled devices that are unmanaged across an IT network. The company’s solutions treat every IoT device as a threat surface, enabling enterprises to prohibit access to IoT devices and networks based on security guidelines. Another unique aspect of this company’s approach to deployment is the ability to use an enterprises’ existing infrastructure for rapid deployments. Founded in 2015 the company has active customers in finance, healthcare, manufacturing, and high technology industries. Armis Security has raised a total of $47M in funding over 3 Their latest funding was raised on Apr 9, 2018, from a Series B round of $30M from Bain Capital Ventures and Red Dot Capital Partners. Crunchbase reports Armis Security has $2.1M in revenue annually and competes with DigiCert, Skybox Security, and Aruba Networks most often in sales cycles.
Crate.io – Crate.io’s open source SQL database features integrated search for storing and analyzing machine data in real time. The company was founded in 2013 with the purpose of providing SQL developers with an open source SQL database to capture, analyze and manage their machine learning and AI-based data. CrateDB is an open source distributed database offering the scalability and performance of NoSQL with the power and ease of standard SQL. The CrateDB Cloud for Azure IoT is a turnkey data layer, offered as a hosted cloud service on Azure, enabling faster development of IoT platforms and data-driven smart factories. Most CrateDB customers use it for operational analytics workloads, performing fast time series, geospatial, text search, machine learning queries against streams of data and data at rest in Industrial IoT, enterprise cybersecurity & systems monitoring in all industries, smart city and building infrastructure, Vehicle fleet tracking & management and marketing analytics. The company has raised $17.9M in funding over 4 rounds.
Dragos – Dragos specializes in industrial (ICS/IIoT) cybersecurity. Their cloud-based Dragos Platform collects, detects, and automates asset inventorying and visualization, threat detection through threat behavior analytics, and security operations and incident response workflows. Dragos also has a Threat Operations Center that provides customers access to dedicated ICS incident response and threat hunting services as well as industrial specific intelligence reporting on vulnerabilities, threats, and community events. Dragos has raised a total of $48.2M in funding over 3 Their latest funding was raised on Nov 14, 2018, from a $37M Series B round with Canaan Partners.
Drayson Technologies – Drayson Technologies provides an IoT platform startup that is combining wireless charging technology and machine learning software to create smart sensor networks that deliver greater energy and cost efficiencies to its customers. Drayson is known for its expertise in energy-efficient and cost-effective IoT data collection and analysis, which also contributes to their customers’ ability to reduce the cost of deploying, owning and running IoT networks.
Element Analytics –Element Analytics is rapidly establishing itself as a startup to watch in the fields of chemicals & refining, manufacturing, metals & mining, pulp & paper, and upstream oil & gas. Their Element Platform helps industrial organizations easily and rapidly use industrial time-series data to improve production efficiency and product quality. Their platform prepares time-series data, enriches it with analytically relevant context, creating greater contextual insights. The Element Analytics platform also enables machine-learning modeling to surface reliability, productivity, and sustainability insights for operations. Element Analytics has raised a total of $22M in funding over 3 Their latest funding was raised on Jan 8, 2018, from a Series A round. Kleiner Perkins participated in the first two rounds, funding a total of $7M.
FogHorn – FogHorn is a fascinating startup to watch because they excel at embedding real-time analytics and machine-learning support into size- and space- constrained commercial and industry IoT application areas. Realizing that industrial manufacturing and distribution sites often have unreliable Internet connections if they have any at all, Foghorn has designed a miniaturized, scalable complex-event processing (CEP) software engine that is capable of producing analytics in real-time. The FogHorn Lightning™ platform includes the CEP software engine, enabling high-performance edge computing, advanced analytics, Machine Learning, and AI to be implemented highly constrained environments of IIoT. The company has also created a new class of high-performance programming language called Vel ™ which transforms any gateway, programmable logic controller (PLC), industrial PC, or another edge device into an advanced edge computing system. FogHorn has raised a total of $47.5M in funding over 4 Their latest funding was raised on Oct 4, 2017, from a Series B round. The FogHorn Technology Platform is shown below:
GEM – GEM specializes in providing IoT, analytics, and machine learning platforms and solutions for the manufacturing industry, with a specific focus on Overall Equipment Effectiveness (OEE) and predictive maintenance. The company has been able to gain customers in energy, retail, and GEM’s value proposition is based on their ability to increase manufacturers’ OEE levels through greater real-time insights. The GEM Precare platform captures operational data and KPIs in real-time including availability, OEE, performance, quality, MTBF, MTBA, machine statuses, status reasons, and alarms. The following is an example of the GENM technology platform:
IoTium – This is a fascinating company to track due to their patented technology that enables secure connections between Network as a Service (NaaS), legacy onsite systems and cloud-based applications. Customers include CBRE, Emerson, Intelligent Buildings, Obernel, Rexnord, and Sunbelt Controls. IoTium is well positioned to gain new customers in building and industrial automation, oil & gas, manufacturing, transportation, and smart city industries. IoTium has raised a total of $22M in funding over 2 rounds with investors GE Ventures, March Capital, and Juniper Networks. Their latest funding was raised on Sep 19, 2018, from a Series B round.
InfluxData – InfluxData created InfluxDB, their Open Source Platform specifically designed to analyze metrics and events (time series data) for DevOps and IoT applications. Whether the data comes from humans, sensors, or machines, InfluxData enables developers to build monitoring, analytics, and IoT applications at scale, delivering measurable business value quickly. The company reports having 400 customers including Cisco, eBay, IBM, and InfluxData has raised a total of $59.9M in funding over 4 rounds. Their latest funding was raised on Feb 13, 2018, from a Series C round.
Karamba Security – Karamba Security is focused on solving the security challenges of connected vehicles. The company offers Electronic Control Unit (ECU) endpoint security to protect any vehicle with an IoT connection or IP address. What makes this startup so interesting is how they are using patented technologies to reduce IoT-based attacks on vehicles by blocking them autonomously. Internet connectivity or extensive developer work is not needed to implement Karamba across a vehicle fleet. Each device can be reset to its factory settings, eliminating the threat of a vehicle being hacked. Karamba Security has raised a total of $27M in funding over 4 Their latest funding was raised on Apr 10, 2018, from a Series B round.
MachineMetrics – What makes MachineMetrics an interesting company to watch is their innovative approach to using Artificial Intelligence (AI) to discover new insights into manufacturer’s data that improve product quality and performance. It’s one of the first startups to combine Industrial Internet of Things (IIoT) and AI and provide a scalable platform for discrete manufacturers and heavy equipment builders. They’ve also developed an expertise at edge connectivity in manufacturing environments that have enabled greater real-time visibility and more meaningful manufacturing analytics than has been possible in the past. They’re using AI to drive their prescriptive and predictive alerts. MachineMetrics has raised a total of $13.4M in funding over 3 Their latest funding was raised on Dec 11, 2018, from a Series A round. The following is a Workstation View from the MachineMetrics Production platform:
MagicCube – MagicCube is a device independent IoT security platform that protects against on-device, cloud, and network attacks. The MagicCube solution secures digital transactions on any device, in transit, and in the cloud with the same level of security as device hardware solutions without the complexity and cost associated with hardware deployments. MagicCube, Inc. has raised a total of $10.7M in funding over 2 Their latest funding was raised on Aug 8, 2017, from a Series A round.
Myriota – What makes Myriota a fascinating company to watch is their innovative advances in ultra-low-cost satellite Internet of Things (IoT) connectivity and the alliances they are creating, including on with SpaceX. Myriota’s nano-satellite was launched into space aboard the SpaceX Falcon 9 rocket in December 2018. Myriota uses exactEarth’s Low Earth Orbit (LEO) satellite constellation for its connectivity solutions. Myriota is a global leader in low-cost satellite IoT connectivity, providing aggregated sensor reading, environmental sensing, and online tracking and condition monitoring of remote assets. The company has raised a total of $15M in funding over 1 round. This was a Series A round raised on Mar 26, 2018.
Particle – Particle is an Internet of Things (IoT) device platform that enables organizations to develop and fine-tune connectivity across operations using scalable APIs and software development resources. Particle’s development platform is designed to provide organizations with the tools they need to prototype IoT solutions to scale quickly and securely. Over 150,000 product builders in more than 170 countries and half of the Fortune 500 have deployed connected IoT devices powered by Particle. Particle’s customers include NASA, SpaceX, consumer hot tub manufacturer Jacuzzi, and Venture-backed by Root Ventures, Spark Capital, Qualcomm Ventures, and Particle is based in San Francisco, CA and Shenzhen, China. Particle has raised a total of $35.8M in funding over 7 rounds. Their latest funding was raised on Jul 19, 2017, from a Series B round.
Samsara – What makes Samsara noteworthy is their prioritizing how sensor data can increase the safety and efficiency of physical operations, contributing to productivity gains while reducing costs. Samsara is attracting customers from the transportation, logistics, construction, food production, energy, and manufacturing industries with their ability to improve the safety, efficiency, and quality of operations. Samsara builds sensor systems that combine wireless sensors with remote networking and cloud-based analytics. As of February 2019, the company has over 5,000 customers and has a run rate of 200,000 new devices being added every year. Samsara has raised a total of $230M in funding over 5 Their latest funding was raised on Dec 28, 2018, from a Series E round. An example of the company’s Fleet Summary is shown below:
SCADAfence – SCADAfence provides cybersecurity solutions designed to ensure the operational continuity of industrial (ICS/SCADA) networks. The startup excels at integrating Industrial IoT, analytics, realtime monitoring and machine-to-machine connectivity to provide scalable cybersecurity solutions for production networks. As of February 2019 the company has customers in the pharmaceutical, chemical, food & beverage and automotive industries. SCADAFence offers a solution suite that includes continuous real-time monitoring of the industrial environment as well as lightweight tools designed to automate the process of security assessment. The suite provides visibility of day-to-day operations, detection of cyber-attacks and forensics tools designed to improve responsiveness. SCADAfence has raised a total of $10M in funding over 3 Their latest funding was raised on Nov 21, 2017, from a Series A round.
SequoiaDB – SequoiaDB develops and provides commercial support for the open source database SequoiaDB, a document-oriented NewSQL database that supports JSON transaction processing and SQL query. Their database can either be a standalone product to interface with applications providing high performance and horizontally scalable data storage and processing functions or serve as the frontend of Hadoop and Spark for both real-time query and data analysis. It is designed to integrate with Spark, Hadoop/Cloudera. SequoiaDB has raised a total of $40M in funding over 3 Their latest funding was raised on Sep 19, 2018, from a Series C round.
Sight Machine – This is a fascinating startup to watch, I’ve been tracking Sight Machine for several years. The company is succeeding at attracting Fortune 500-level manufacturers as clients by providing them with AI-driven insights into how they can improve operations. Sight Machine’s AI and analytics platform, purpose-built for discrete and process manufacturing, uses artificial intelligence, machine learning, and advanced analytics to help address critical challenges in quality and productivity throughout the enterprise. The platform is powered by the industry’s only Plant Digital Twin, which enables real-time visibility and actionable insights for every machine, line, and plant throughout an enterprise. Sight Machine is optimized to run on the major cloud platforms including AWS, Google Cloud Platform, and Microsoft Azure. The company has raised a total of $30.5M in funding over 5 Their latest funding was raised on Dec 23, 2017, from a Series B round. An example of a Sight Machine dashboard is shown below:
Splice Machine –. Splice Machine provides an open-source dual-engine RDBMS for mixed operational and analytical workloads, powered by Apache Hadoop® and Apache Spark™. The Splice Machine RDBMS executes operational workloads on Apache HBase® and analytical workloads on Apache Spark. Splice Machine is known for its ease of development and use for IoT-based applications and is successfully offload operational and analytical workloads from Oracle, Teradata, and Netezza legacy systems. The company excels at ETL, operational reporting or real-time applications and use cases. Splice Machine has raised a total of $40M in funding over 4 Their latest funding was raised on Dec 20, 2017, from Salesforce Ventures.
SWIM.AI – Swim provides edge-based software that executes real-time analytics and machine learning for enterprises, equipment manufacturers, smart-cities, and IoT and IIoT businesses. Its software locally processes and analyzes massive volumes of streaming data from devices/sensors/equipment where it is created, reducing network volumes, and generating real-time machine-learning business insights. Swim deploys its software at the edge to transform data into insights in real-time and delivers them to businesses, staff, operators, and customers. Swim has successfully been deployed and is in use in existing equipment and brownfield environments. In manufacturing customers’ operations Swim is improving real-time synchronization across multiple systems, reduce project implementation costs, optimizing efficiency using machine learning insights from full resolution edge data and making insights available via real-time APIs. Swim.ai has raised a total of $10M in funding over 2 rounds. Their latest funding was raised on Jul 17, 2018, from a Series B round. Swim’s model is shown below:
Tulip – Tulip was started by a team of engineers out of the MIT Media Lab, and the company’s platform is based on over ten years of research in digital manufacturing. Their self-service technology fills the gap between rigid back-end manufacturing IT systems and the dynamic operations taking place on the shop floor. Tulip’s Manufacturing App Platform combines research in intelligent hardware sensors, computer vision, assistive user interfaces, and applied machine learning. Tulip was launched to bring these latest technological developments from the lab to the factory floor. Today, Tulip’s Manufacturing App Platform is deployed at dozens of global customers in six countries across multiple industries including Electronics, Aerospace & Defense, Medical Devices, Footwear, Pharmaceuticals, and Contract Manufacturing. Tulip Interfaces has raised a total of $13M in funding over 3
Tuya Smart – Tuya Smart is an IoT solution provider for device manufacturers. Their platform enables fast, agile app development, allowing smart device manufacturers to bring their product to market quickly and at competitive prices. Tuya Smart is founded by Jerry Wang, a founding executive of AliYun, Alibaba’s cloud division, along with a group of veterans from Alibaba, Baidu and Haier Electronics. With extensive knowledge in cloud computing, software development, and hardware and supply chain management, Tuya Smart’s team is enabling manufacturers to produce next-generation smart, connected products. Tuya has raised a total of $200M in funding over 3 Their latest funding was raised on Jul 24, 2018, from a Series C round.
Uptake – Uptake Technologies provides a predictive analytics and asset performance management (APM) platform gaining traction in key industrial IoT market segments today. The Uptake platform analyzes data from inside a company and from third party sources to predict and prevent failures, uncover hidden profits, and discover new opportunities to healthcare, insurance, locomotives, construction, manufacturing, and other industries. Uptake Technologies offers a platform for equipment monitoring, diagnostic troubleshooting, event, and condition prediction, and task management to improve uptime, streamline operations, and spot growth opportunities. Key customers include Caterpillar, Progress Rail, Berkshire Hathaway Energy, and the U.S. Army.
VDOO– VDOO has developed a platform of automated solutions to help IoT makers put the right security in their devices before release and enable post-deployment security. The end-to-end platform takes the maker from security analysis to implementation guidance to certification and enables IoT makers to quickly add the right security to their devices with minimal resources. VDOO’s solution is built upon a comprehensive taxonomy of IoT devices and consists of five interrelated and integrated products including the Security Requirements Generator, Security Gap Analysis, Actionable Security Plan, Certification, and Post-Deployment Security Enablement. VDOO has raised a total of $13M in funding over 1 round. This was a Series A round raised on Jan 17, 2018.
Xage Security – Xage provides decentralized security services for industrial manufacturing and distribution businesses including oil and gas, transportation, and utilities. The Xage architecture relies on blockchain to provide a distributed, scalable and highly reliable data store that prevents hackers from attacking and gaining access through any threat surface in an organization. Xage takes a unique approach to using blockchain to thwart hacking attempts at scale, by simultaneously protecting every active ledger in an organization. Xage Security has raised a total of $16M in funding over 2 Their latest funding was raised on Dec 28, 2018, from a Series A round.
