The Internet of Things (IoT) promises to make machines smarter, industrial processes more efficient and consumer devices more responsive to our needs. According to research firm Gartner, there will be more than 20 billion connected things in use worldwide by 2020.
But these constrained devices often run on woefully out-of-date software that must be manually patched and upgraded; the market potential is enormous, but so are the risks.
Figuring out successful IoT business models is still a work in progress, and many are trying. We’ve looked at a large sampling of companies that have formed to work on these problems and pared the list down to 10 that warrant special attention. (See how we did it.)
Collectively, the startups featured in this roundup have raised nearly $150 million in venture funding to chase IoT opportunities and tackle the risks. FogHorn Systems ($47.5 million), Armis ($47 million), and AlertMedia ($17 million) have the deepest pockets. At the other end of the spectrum, the rest of the startups have locked down funding in the $3million to $11 million range, enough to provide plenty of runway to get a product to market.
These hot startups offer everything from enterprise emergency notification systems to smart manufacturing platforms to “virtual chips” that add security to any connected device.
What they do: Mass-notification platform for the enterprise
Year founded: 2013
Funding: $17 million
Headquarters: Austin, Texas
CEO: Brian Cruver previously co-founded and CEO of Xenex, a company that develops germ-fighting robots that help hospitals prevent infections. Cruver also authored Anatomy of Greed, his firsthand account of Enron’s collapse.
Problem they solve: Large organizations face numerous threats to their people, assets and operations. When an incident occurs, the faster you can react, the more likely it is that you can minimize losses. Delayed awareness and slow response time can be costly in terms of production, profitability, reputation and the health and safety of employees.
Despite waves of automation elsewhere in the enterprise, emergency response is still a manual, reactive and often much-delayed process.
How they solve it: The AlertMedia platform connects enterprise sensor data, system data, location data and employee smart devices together to create a single multi-channel critical communication platform.
The AlertMedia platform collects signals from gauges, vehicles, GPS locators, etc., and converts those signals into meaningful 24/7 communications. AlertMedia minimizes disruption to the business while keeping employees safe and informed.
AlertMedia helps its customers contend with a variety of emergency situations, such as severe weather, security threats, fires and power outages. But it also helps with more mundane emergencies too. For example, AlertMedia says that it is currently being used by a large restaurant chain to monitor temperatures in their refrigeration systems. When temperatures are outside a specified range, the system triggers notifications to the restaurant’s response team, preventing significant inventory losses.
Competitors include: Everbridge and OnSolve
Customers include: AT&T, Volkswagen, DHL, Greyhound, Kawasaki, The Salvation Army, British Petroleum (BP), H-E-B Grocery Company, State of Texas and New York City
Why they’re a hot startup to watch: Unless you’re a global-warming denier, it’s clear that the market for emergency services will only rise in coming years. AltertMedia’s system, however, doesn’t just help during natural disasters. To return to the restaurant example, a power outage or a compressor failure that ruins enough inventory can be an equally crushing blow to a business’ bottom line.
AlertMedia says that it has 500+ enterprise customers located in 90+ countries around the world, including multinationals AT&T, BP and Volkswagen. With $17M in funding and a leadership team that features serial entrepreneurs who have founded other successful startups (Xenex), achieved successful IPOs (Demand Media), and guided a startup to a successful acquisition (Adometry, acquired by Google), AlertMedia is well-positioned to take advantage of this land-grab opportunity.
What they do: IoT platform for smart manufacturing
Year founded: 2013
Funding: $5 million
Headquarters: Scotts Valley, Calif., and Pune, India
CEO: Vinay Nathan. Prior to founding Altizon, Nathan was Head of Sales, North America and APAC, for Persistent Systems.
Problem they solve: Manufacturing CIOs are looking for ways to implement Industry 4.0 technologies, hoping to leverage things like deep learning and Big Data to improve operating efficiencies and to enable new business models.
In many factories, machines are already technically capable of communicating with one another, but the data they generate still requires plenty of human intervention before anything can be done with it. A lack of real-time visibility into machines, assets, and factory operations limits manufacturers’ ability to make informed, data-driven decisions and move beyond reactive fixes to predictive planning based on real-time machine performance trends.
How they solve it: Altizon’s goal is to help manufacturers revolutionize their shop floors using edge computing, sensors, Big Data, machine learning, and enterprise-ready integrations. Altizon’s IoT platform, called Datonis, consists of three main components: Edge connectors, the core Datonis IIoT backend platform, and a Manufacturing Intelligence component.
Datonis Edge provides connectors to common connectivity protocols, such as OPC-UA, Modbus, Bluetooth, and Wi-Fi, so devices can quickly connect to a manufacturer’s network. The Edge is built as a store-and-forward system and has a built-in cache for storing messages when offline. The Edge also uses data batching, compression, and various other techniques to ensure that it can deal with limited network data bandwidth. The Datonis Edge can also process and analyze sensor data on the edge, ensuring that only relevant data is transmitted back to the main platform.
Altizon’s Datonis IIoT software platform integrates connected devices within enterprise IT, connecting industrial assets and IoT software applications over a hybrid infrastructure. It uses Big Data and machine learning to help manufacturers get the real-time visibility they need to determine the effectiveness of their production system environments, predict their throughput, optimize their energy use, and make quality improvements. Features include device management capabilities, stream analytics, and customizable alerts and notifications.
The Datonis Manufacturing Intelligence (MI) component provides connectors to integrate plant data from a factory’s disparate plant-floor systems. Businesses are able to compile data from machines, existing SCADA and DCS systems, Enterprise Data Historians, and Manufacturing Execution Systems into a single repository that provides a unified view into all manufacturing operations data.
Datonis MI helps manufacturers define and track KPIs that are relevant to plant operations, while integrating those insights into business systems like ERP, CRM and Enterprise Planning and Scheduling systems.
Taken together, these tools help manufacturers build an intelligent connected ecosystem that spurs the flow of machine and enterprise-systems data for measurable business improvement in manufacturing.
Competitors include: C3IoT, Cisco Jasper, GE Digital Predix, PTC ThingWorx, Siemens Mindsphere, Xively, and Cumulocity.
Customers include: Varroc, CPG Company, and Prayas.
Why they’re a hot startup to watch: With $5M in VC funding, several named customers, and more than 150 implementations worldwide, Altizon has the resources to give the Datonis suite a fighting chance when going up against incumbents and major multinationals, such as PTC, Cisco, and GE. Moreover, the startup’s senior team has the right mix of backgrounds to bridge the IT-industrial divide, having gained relevant leadership experience at Persistent Systems, BMC, Storability, Sun Microsystems, Bladelogic, Rockwell, Siemens, and others.
What they do: IoT security
Year founded: 2015
Funding: $47 million
Headquarters: Palo Alto, Calif.
CEO: Yevgeny Dibrov. Prior to co-founding Armis, Dibrov was the first hire at Adallom, a cloud-security company. He began as a product manager and finished as the head of global business development when the company was acquired by Microsoft for $320M.
Problem they solve: Gartner estimates that there will be more than 20 billion connected things in circulation by 2020. With this many connected devices in circulation, any notion of a network/security perimeter becomes obsolete.
According to Armis, the new wave of connected devices comes with three distinct security challenges. First, many devices are now designed to automatically connect to the internet or other devices, meaning they’ll often bypass security by default.
Second, most of these devices are not designed to allow upgrades to their limited operating system or firmware, making vulnerabilities a major issue. Finally, most of these devices have no inherent security, nor, due to memory and processing constraints, can you put any anti-malware or security agents on them.
Beyond device insecurity, IT teams often can’t see devices coming in and out of their networks. Traditional security approaches such as firewalls, network access control and security agents will not protect these unmanaged devices.
How they solve it: Armis’ IoT security platform is designed to eliminate the IoT security blind spot for businesses. Armis is designed to secure unmanaged devices in three ways.
First, Armis provides visibility of all devices in an organization’s environment. Using an agentless approach, Armis identifies all devices and can see how they connect to the network, including over wired and wireless connections.
Second, Armis analyzes a device’s behavior to identify risks and attacks, gaining insights into device reputation, status, connection, version, activity history and more. Third, Armis protects businesses by letting them manually or automatically disconnect devices from networks when they are behaving suspiciously or maliciously.
Competitors include: Cisco, Aruba, ForeScout and ZingBox.
Customers include: Samsung Research America, IDT and Gett.
Why they’re a hot startup to watch: The addressable market for IoT security is massive, and Armis already has a decent foothold with such customers as Samsung Research America and IDT.
Armis also just locked down a $30M Series B in April 2018, bringing their total funding to date to $47M, which leapfrogs them to the third-highest funding total of the 20 finalists in this competition. Finally, Armis did well in the online voting round, finishing in the top 5.
What they do: Operating stack for industrial applications
Year founded: 2013
Funding: $6 million
Headquarters: Sunnyvale, Calif.
CEO: Jane Ren, who previously served as chief business architect for GE Software
Problem they solve: Many industrial processes are reactive, manual and ad hoc in nature, making them extremely inefficient. For example, the lack of coordination when ships and trucks line up at terminals results in hours of wasted time.
Another example Atomiton provides is with oil refineries, where operators heat terminal oil tanks and pipes without insights on the peak energy impact. The inability to analyze real-time data to anticipate and respond to future scenarios leads to waste.
How they solve it: Atomiton provides an industrial IoT software stack, which helps industrial companies anticipate future scenarios and optimize operations based on predictive intelligence. Atomiton is able to run predictive optimization based on real-time data gathered directly from industrial systems (PLCs, SCADA, instruments, sensors, etc.).
The Atomiton Stack encapsulates attributes and behaviors of things into models. These “thing models” provide the interfaces for things to interact with each other, as well as for people to access things in order to, for instance, query or control them. The Atomiton Stack also enables things using different protocols to directly interact with any applications. Things can operate on IP or industrial-based protocols.
Applications can direct things to work with one another to achieve aggregated goals. The things talk and respond to one another using subscription-, notification- and query-based communications. They can create schedules to perform coordinated actions or they can adjust to another thing’s demands. For example, in smart cites the streets lights can dim after 10 p.m. based on the activities captured by nearby parking meters. If the meters report that no one is out and about, the lights can dim in response.
Competitors include: ABB, Siemens, Emerson Electric, GE, and Yokogawa
Customers include: Cisco and Vopak
Why they’re a hot startup to watch: Atomiton’s leadership team is exceptionally strong. Besides founder and CEO Jane Ren’s experience launching industrial internet programs across GE businesses, there is also CTO Alok Batra’s experience leading an operational intelligence startup to an acquisition by Cisco, where Batra then served as CTO for Cisco Emerging Solutions.
The startup hasn’t raised an enormous amount of VC funding, but it does have a high-profile on-the-record customer in Cisco. (And Cisco often reacquires the startups its alums go on to found, so there’s that to consider.) Atomiton’s industrial operating stack concept has the potential to automate processes that aren’t even being executed at present. The potential market for this type of predictive intelligence is enormous.
What they do: IoT industrial apps
Year founded: 2012
Funding: $8.5 million
Headquarters: Houston, Texas
CEO: Krishnan Raman, who previously served as the Head of the Global BI/DW Business for MindTree
Problem they solve: Energy and engineering industries are turning to IoT solutions to try to overcome three big problems. They seek to reduce asset downtime, enhance processes to deliver better quality products and create new business models that take advantage of newly available data.
How they solve it: Flutura industrial IoT apps use data analytics and AI to improve industrial processes. Many industries lack specific IoT apps for their verticals. To address this, Flutura has developed what they call “Nano Apps,” which are specifically meant to solve point problems for specific verticals such as the oil-and-gas industry.
For oil-and gas businesses, Flutura apps monitor frack-pump performance. For manufacturing, they have developed discrete apps that feed IoT sensor data into AI models to improve efficiency and quality. Flutura delivers these apps as a service, priced on a per asset/per app/per month basis.
Competitors include: GE Predix, PTC Thingworks, Siemens Mindsphere, Hitachi Ventara, Tachyus and Spark Cognition.
Customers include: Henkel and Stewart and Stevenson.
Why they’re a hot startup to watch: The first thing you notice about Flutura is that it’s going after a market space dominated by major multinationals, such as GE and Siemens. Yet, legacy incumbents tend to be slow to adopt new technologies.
Flutura is scaling up by targeting industrial niches – oil-and-gas, utilities, manufacturing – where small improvements can deliver enormous ROI. As such, shifting this IoT solution to an opex rather than capex expense is a smart move since operations is where the savings will be realized.
With $8.5M in funding and a couple of named customers, Flutura has a fighting chance to gain a purchase in this market before incumbents can block them. Flurtura also did well in the online voting round of this competition.
What they do: Edge-intelligence software for IoT applications
Year founded: 2014
Funding: $47.5 million
Headquarters: Mountain View, Calif.
CEO: David C. King. Prior to joining FogHorn, King co-founded and served as chairman and CEO of AirTight Networks.
Problem they solve: Most industrial edge solutions ingest sensor data into a local storage repository and then publish the unprocessed data out to a cloud environment for offline analysis. However, many industrial environments and devices lack cost-effective and consistent internet connectivity, making this approach unfeasible.
On offshore oil rigs, for instance, less than one percent of the data generated by 30,000+ sensors is currently being used to make decisions, according to McKinsey & Company.
In addition, this store-batch-and-publish approach is anything but real-time. By the time the data is uploaded to the cloud, processed in the data center, and the results are transferred back to the edge, it may be too late to take any meaningful action.
How they solve it: FogHorn develops edge-intelligence software for industrial and commercial IoT application solutions. FogHorn addresses the challenges of gathering data in remote areas with poor or no connectivity with a miniaturized, scalable complex-event-processing (CEP) software engine that can run advanced operational and predictive analytics locally and in real time.
FogHorn enables high-performance edge processing, optimized analytics and heterogeneous applications to be hosted as close as possible to the control systems and physical sensor infrastructure that pervade the industrial world. This creates intelligence at the edge, resulting in closed-loop device optimization.
FogHorn’s small footprint delivers real-time, industrial-grade analytics to resource-constrained edge devices such as programmable logic controllers, gateways and industrial PCs. FogHorn’s solution helps manufacturers transform real-time machine data into actionable insights to reduce costs, thereby improving production efficiency and reducing unplanned downtime. With actionable real-time data, manufacturers can quickly push beyond simple cost savings to intelligent management and forecasting.
Competitors include: Amazon Greengrass and Microsoft Azure Stream Analytics.
Why they’re a hot startup to watch: With close to $47.5M in VC funding, FogHorn is one of the best-funded startups on this list. FogHorn’s senior leadership team is also exceptionally strong. CEO King led AirTight Networks through four successful up rounds of venture capital funding. Prior to AirTight, he served as Chairman, President and CEO of Proxim, which he led to a successful IPO.
CTO Sastry Malladi, previously served as the Chief Architect of StubHub, and Yuta Endo, VP/GM of APAC Operation and Business Development, previously led product management and strategic industrial partner relationships for Cisco’s IoT division. FogHorn almost missed the cut in the online voting round, but a strong push on the last day got them into round 3, where their funding, market positioning and strength of their leadership put them over the top.
What they do: IoT security
Year founded: 2014
Funding: $10.7 million
Headquarters: Santa Clara, Calif.
CEO: Sam Shawki, who previously served as Global Head of Remote Payments for Visa
Problem they solve: Unlike mobile phones, most IoT devices do not have chip- or SIM-based security to manage their identity, remotely or otherwise. Additionally, consumer IoT devices cannot be managed using traditional platforms that are designed to work within the fixed perimeter of the enterprise.
According to Shawki, “A wide range of applications, including driverless cars, medical devices, fintech and government all have one thing in common: They’re all IoT devices that can't be secured using legacy solutions.”
Two of the most common ways to secure mobile transactions are Secure Elements (SE) and Trusted Execution Environments (TEE). An SE, such as a programmable SIM card or an EMV chip on a payment card, offers a high degree of security, but with the added cost and complexity of an additional chip.
A TEE removes the expense of a separate chip by creating a secure area on the main processor itself. The TEE protects the integrity of applications that execute within it, while also maintaining the confidentiality of their assets. However, the implementation of TEEs is complex. Execution of applications within the TEE can be slow, and TEEs can be resource hogs overall, which limits this approach only to critical applications, such as mobile payments.
Both SEs and TEEs add cost and complexity to the end device. Inserting a hardware security chip into many consumer IoT devices is cost- and support-prohibitive, and for many devices that could support the cost, they don’t have the backend in place to do anything with the connected device. This leaves these devices unsecured, unmanaged and unsupported.
How they solve it: MagicCube eliminates the need for a special chip and/or chip partition, moving the secure execution area into a software-only container. MagicCube replaces the on-chip TEE with a “software Trusted Execution Environment (sTEE™),” or what the startup refers to as “the Cube.”
“Conceptually, it helps to think of the Cube as a virtual chip,” CEO Sam Shawki explained. “Our virtual chip is a secure software container that is isolated from the underlying environment, so it can safely execute sensitive operations and store secrets. By removing the need for a physical chip or on-chip partition, security can be added at will to pretty much any Linux- or Unix-based connected device.”
All an engineer has to do is compile the next release of an app or an IoT device with MagicCube’s SDK. There is no separate app to download, and no alteration is made to the device or OS. The cube has only one API to call (MagicCube’s), which creates a secure virtual container in memory. The cube has its own OS. It utilizes only memory and CPU cycles from the host device but none of the host OS APIs.
The Cube functions as independent device with its own defenses, even on jailbroken devices. It provides a secure in-app container that protects sensitive data, logic and cryptographic operations on the device.
“The Cube is also ephemeral, behaviorally,” Shawki added. “It wakes up, does its job, delivers the results to the app and then it disappears (or shuts back down), all in less than 350 milliseconds. Because of this and other protective measures, in-lab testing accredited by Visa, MasterCard, Rambus and others, our Cube has successfully protected secret data even on compromised operating systems. We have even resisted side-channel attacks, which can compromise physical chips.”
On the backend, devices are monitored and managed via an on-premises appliance, or through the cloud as a service. MagicCube currently offers pre-packaged security profiles for mobile payments, connected cars, and PIN on glass protection at POS terminals.
Competitors include: Qualcomm-NXP, Arxan and Zingbox.
Customers include: Sequent, Yellow Pepper, ID Tech and NTT Data.
Why they’re a hot startup to watch: MagicCube is targeting a market that already consists of more than 20 billion connected devices, according to Gartner. The number of connected devices will spike in coming years and securing those devices will be a paramount challenge. With named customers and more than $10M in funding, MagicCube has the resources to charge in and stake a claim in this land-grab market.
MagicCube’s team has experience with successful exits, such as Shawski’s role in leading Orascom Telecom to an acquisition by VimpleCom for 26 Billion Euros. CTO and co-founder Nancy Zayed helped win Apple an Emmy Award for technological achievement for her work on Final Cut Pro. She also headed the teams that designed and built the consumer telepresence for Cisco.
MagicCube also finished in the top five in the online voting round of this competition.
What they do: Sensor platform for real-time supply chain visibility
Year founded: 2015
Funding: $3.6 million
Headquarters: Cambridge, Mass.
CEO: Krenar Komoni, who was the first employee at Eta Devices, where he developed low-power devices
Problem they solve: Manufacturers lose track of their goods as soon as they load a plane, ship or truck. As a result, in-transit damages and delayed shipments cost these companies billions of dollars every year. Worse, without visibility into those in-transit goods, manufacturers have no hope of avoiding damages and delays, let alone eliminating the root causes of these issues.
At the same time, customer expectations are higher than ever before, as companies like Amazon and Uber set new standards for on-demand transportation and delivery services. To remain competitive, manufacturers can no longer afford to lose sight of their goods as soon as they leave the building.
How they solve it: Tive provides visibility into the supply chain, gathering real-time information about in-transit goods, such as the location and condition of shipments. Tive’s combination of cellular-connected trackers and cloud-based software enable reporting, analysis and customized alerts on shipments across all modes of transport.
Conditions that may damage goods vary from industry to industry. For instance, with pharmaceuticals, maintaining a specific temperature range is critical, while with electronics, tilt and humidity are the key conditions that must be monitored. Thus, Tive relies on a variety of sensors to detect a broad range of conditions that can damage a shipment.
Trackers monitors temperature, shock, orientation, humidity, motion, and light. When damaging conditions occur, Tive sends out an alert via email or text message. In addition to seeing the damage when it happens, Tive also helps its customers track down the root cause of the problem, so they can resolve it for future shipments.
For example, if pharmaceuticals are consistently left sitting in the sun on a specific loading dock, Tive will zero in on the problem. As a result, companies immediately know about any damage or delays, as well as root causes, which helps them improve customer service while also reducing disruptions and logistical costs.
Tive also notes that its cellular-connected trackers last up to six months on a single charge, which makes them suitable for items in long, slow supply chains.
Competitors include: UTC Sensitech, Sendum, OnAsset, Roambee and ZillionSource
Customers include: Nokia
Why they’re a hot startup to watch: Tive is targeting a big market with no clear incumbents. Research firm MarketandMarkets predicts that the connected logistics market will expand from $10B in 2016 to $41B by 2021. As a young startup, Tive already has a top-tier-named customer in Nokia, and the startup’s senior leadership team has been involved in several successful exits, including the GrabCAD sale to Stratasys and Kiva System’s sale to Amazon Robotics.
What they do: Blockchain-based IoT security platform
Year founded: 2016
Headquarters: Palo Alto, Calif.
Funding: $4 million
CEO: Duncan Greatwood. Previously, Greatwood was CEO of Topsy Labs, a social media search and analytics company that was acquired by Apple, where Greatwood then served as an executive in charge of a number of Apple's search-technology projects and products.
Problem they solve: Companies are transforming their operations with IoT, AI, automated management and machine-to-machine cooperation at the edge. The result is a highly interconnected, yet disparate and siloed cyber-physical operational system. This creates a number of security holes that can be difficult to find, let alone defend.
As the internet of things grows, attackers will turn their attention to unsecured edge devices.
This is already a major problem. The recent ransomware attack on Atlanta’s city computer systems knocked traffic and other smart-city systems offline for five days. The Mirai and Reaper botnets took control of millions of connected devices around the world. And IoT vulnerabilities provide a big attack surface in cyberwarfare.
How they solve it: Xage argues that to realize the promise of the industrial IoT revolution, security needs to be woven into IoT’s autonomous, any-to-any, edge-heavy architecture. Security must to be as distributed, redundant, flexible and adaptive as the systems it is tasked to defend.
Xage’s blockchain-based security software distributes authentication and private data across a network of devices, creating an any-to-any fabric for communication and authentication. Xage facilitates autonomous operation, credential rotation, access control and zero-touch deployment to deliver the protection required for Industry 4.0.
Xage software is deployed in nodes, which are a combination of industrial endpoints (such as robots or electrical smart meters) and gateway computers located at industrial sites. The nodes communicate amongst themselves to create the blockchain. Collectively, the nodes form a self-healing fabric that is protected against the compromise of individual components. The gateways also proxy-in legacy unmodified industrial endpoints, enabling them to participate in the system without being upgraded with Xage software.
The fabric acts as a tamper-proof and confidential store of security information – including user credentials, device passwords, enrollment keys and security policies – with the information held at the industrial site. The fabric also serves as the distributed edge identity and authentication manager, enforcing security policy in real time across the industrial edge and protecting against single-point-of-failure security vulnerabilities
Since the system relies on blockchain, the security of a network protected by the Xage security fabric increases with additional nodes. By enforcing immutable records and distributing and sharing identical security data across the nodes in its network, Xage argues that its blockchain-based fabric is tamper-proof, redundant and self-healing.
Tamper-proofing is achieved using consensus mechanisms, including the consensus system at the heart of blockchain. If attackers were to compromise a subset of blockchain nodes, the attackers would not be able to change the security information (for instance, by changing a policy to grant themselves access to robots), nor would they be able to read back confidential information, such as a device password.
When attackers attempt to compromise a node, the healthy nodes detect the attack and the consensus mechanism blocks the attempt. The system then self-heals by rejecting unauthorized changes and then locking out compromised nodes.
This consensus mechanism is the same one that lies at the heart of digital currencies, where the tamper-proofing is used to stop attackers issuing themselves fake money. Xage’s blockchain-based software also integrates well with redundant, threshold- based technologies like Shamir’s Secret Sharing to secure operational data.
Competitors include: Cisco, Microsoft, and Claroty
Customers include: ABB Wireless, IBM, Itron, Dell and NTT
Why they’re a hot startup to watch: For a young startup, $4M in funding provides plenty of runway to get airborne in this wide-open market niche. Cybersecurity companies are losing the arms race against bad actors, especially as hostile foreign nations launch many of the attacks, so a new approach merits a closer look.
The senior leadership team has several successful exits under their belts, including Apple, Cisco and TA Associates. And for a two-year-old startup, having big names like IBM, Dell and NTT as customers helps them punch above their weight.
What they do: Edge-computing platform for real-time IoT apps
Year founded: 2016
Funding: $3.06 million
Headquarters: Santa Clara, Calif.
CEO: Said Ouissal, who formerly served as SVP, Worldwide Sales and Field Operations at Violin Memory
Problem they solve: Despite the availability of cloud technology and agile process advancements, many enterprises remain deeply invested in legacy embedded technology. They continue to deploy monolithic software built on custom silos of supporting hardware and infrastructure.
When changes to software become necessary, numerous manual steps by different functional teams are required. At the edge, this can also involve truck rolls or other costly remote experts. In the past, these processes were fine because embedded computing was assumed as a multi-year, set-it-and-forget-it technology.
IoT has changed all that. Now, everything is generating data. Applications from self-driving cars to industrial robots are using IoT data in real time to make decisions and improve productivity. The long, manual process of dealing with silos of custom embedded computing solutions leads to errors, high costs, operational inefficiencies and security vulnerabilities. Meanwhile, a dearth of software developers who have experience and expertise with embedded systems adds to the problem.
How they solve it: ZEDEDA’s IoT platform manages edge services from the cloud, enabling software developers to use a web interface to virtualize and orchestrate compute, network, storage and other edge services across various edge hardware platforms.
According to ZEDEDA, Edge software is dominated by traditional embedded-computing software development, where the app is tightly integrated with hardware. This approach creates a very efficient use of resources, but it lacks the agility of the cloud and does not facilitate operational repeatability or automated lifecycle management.
As a result, the edge is particularly susceptible to hacking and edge devices and services are difficult to scale.
A cloud-native edge, in contrast, leverages open-source embedded virtualization techniques on edge hardware to create an abstraction layer between the hardware and the apps running on it. This architecture allows edge hardware managed by ZEDEDA’s cloud platform to deploy and run VMs, containers and micro-services in much the same way they would run in a public or private cloud datacenter.
With ZEDEDA, developers deploy hardware loaded with open-source embedded virtualization software. Then, ZEDEDA orchestrates the edge resources with a combination of agentless, standards-based and crypto-routing infrastructure to enable a multi-tenant, cloud-native environment for IoT applications.
ZEDEDA is designed to secure the edge environment and allow cloud-native apps built for containers, VMs, unikernels, etc., to operate at peak efficiency without requiring any additional embedded development work.
The ZEDEDA platform gives software development and operations technology teams the ability to deploy and update real-time edge applications exactly as they would in the cloud. No remote expertise or truck rolls are required. The end result is that embedded computing can leverage agile development practices, while also delivering security to the edge.
According to a ZEDEDA representative, the platform is currently running a private beta with top-tier industrial equipment manufacturers, clean energy companies and automotive system developers.
Competitors include: Amazon Greengrass, Microsoft Azure IoT Edge, Cisco, VMWare Pulse IoT, IOTium, ResinIO and Sierra Wireless
Why they’re a hot startup to watch: ZEDEDA has a strong leadership team with deep knowledge of and plenty of experience in embedded systems and IoT. The startup has raised enough VC funding to push its platform into beta, and the concept of bringing automation, agile processes and security to the edge is a winner. ZEDEDA also finished in the top 10 in the online voting round, beating out more than 55 other IoT startups.