Skip to content

Posts tagged ‘startups’

Mar 27

The Top 20 Cybersecurity Startups To Watch In 2021

  • Cybersecurity, privacy and security startups have raised $1.9 billion in three months this year, on pace to reach $7.6 billion or more in 2021, over four times more than was raised throughout 2010 ($1.7 billion), according to a Crunchbase Pro query today.
  • 22,156 startups who either compete in or rely on cybersecurity, security and privacy technologies and solutions as a core part of their business models today, 122 have pre-seed or seed funding in the last twelve months based on a Crunchbase Pro query.
  • From network and data security to I.T. governance, risk measurement, and policy compliance, cybersecurity is a growing industry estimated to be worth over $300B by 2025, according to C.B. Insight’s Emerging Trends Cybersecurity Report downloadable here.

Today, 680 cybersecurity, privacy, and security startups have received $6.8 billion in funding over the last twelve months, with $4 million being the median funding round and $12.6 million the average funding round for a startup. The number of startups receiving funding this year, funding amounts and the methodology to find the top 20 cybersecurity startups are all based on Crunchbase Pro analysis done today. 

New startups and established vendors are attracting record levels of investment as all organizations look to thwart increasingly complex, costly and unpredictable cyberattacks. There is an arms race going on between cyber attackers using A.I. and machine learning and the many startups and existing vendors whose goal is to contain them. CBInsights and PwC recently published their latest quarterly joint study of the venture capital landscape, MoneyTree™ Report, Q4, 2020. The study finds that monitoring and security deals were the third fastest-growing vertical in 2020, with Q4 being exceptional for all verticals, as the heat map below shows:

The 20 Best Cybersecurity Startups To Watch In 2021

Based on a methodology that equally weighs a startup’s ability to attract new customers, current and projected revenue growth, ability to adapt their solutions to growing industries and position in their chosen markets, the following are the top 20 cybersecurity startups to watch in 2021:

Axis Security – Axis Security’s Application Access Cloud™ is a purpose-built cloud-based solution that makes application access across networks scalable and secure. Built on zero-trust, Application Access Cloud offers a new agentless model that connects users online to any application, private or public, without touching the network or the apps themselves. Axis Security is a privately held company backed by Canaan Partners, Ten Eleven Ventures, and Cyberstarts. Axis is headquartered in San Mateo, California, with research and development in Tel Aviv, Israel.

Bitglass – What makes Bitglass unique and worth watching is how they are evolving their Total Cloud Security Platform to combine cloud access security brokerage, on-device secure web gateways, and zero-trust network access to secure endpoints across all devices. Its Polyscale Architecture is delivering uptimes of 99.99% in customer deployments. Bitglass’s 2020 Insider Threat Report has several interesting insights based on their recent interviews with a leading cybersecurity community. One interesting takeaway is 61% of those surveyed experienced an insider attack in the last 12 months (22% reported at least six).

Cado Security – Cado Security’s cloud-native forensics and response platform helps organizations respond to security incidents in real-time, averting potential breaches and security incidents. The Cado Response platform is built on analytics components that perform thorough forensic analyses of compromised systems. Cado’s platform, Cado Response, is an agentless, cloud-native forensics solution that allows security professionals to quickly and comprehensively understand an incident’s impact across all environments, including cloud and containers as well as on-premise systems. “Finding the root cause of security incidents in cloud or container environments is incredibly difficult. Traditional tools don’t support these new environments, and there is a shortage of people who know both forensics and cloud security,” said CEO James Campbell, formerly Director, Cyber Threat Detection and Response at PricewaterhouseCoopers. “Our Cado Response platform completely changes how security professionals can respond to incidents in the cloud.”

Confluera – Originally mentioned as one of the 20 Best Cybersecurity Startups To Watch In 2020, Confluera’s sustained innovation pace in the middle of a pandemic deserves special mention. They are one of the most resilient startups to watch in 2021.Confluera is a cybersecurity startup helping organizations find sophisticated security attacks going on inside of corporate infrastructures. The startup delivers autonomous infrastructure-wide cyber kill chain tracking and response by leveraging the ‘Continuous Attack Graph’ to stop and remediate cyber threats in real-time deterministically. Confluera’s platform is designed to detect and prevent attackers from navigating infrastructure. Confluera technology combines machine comprehended threat detection with accurately tracked activity trails to stop cyberattacks in real-time, allowing companies to simplify security operations radically. It frees up human security personnel to focus on more important work instead of spending hours trying to join the dots between the thousands of alerts they receive daily, many of which are false positives. The following is a video that explains how Confluera XDR for Cloud Infrastructure works:

DataFleets – DataFleets is a privacy-preserving data engine that unifies distributed data for rapid access, agile analytics, and automated compliance. The platform provides data scientists and developers with a “data fleet”​ that allows them to create analytics, ML models, and applications on susceptible data sets without direct access to the data. Each data fleet has easy-to-use APIs, and under-the-hood, they ensure data protection using advances in federated computation, transfer learning, encryption, and differential privacy. DataFleets helps organizations overcome data privacy and innovation struggle by maintaining data protection standards for compliance while accelerating data science initiatives.

DefenseStorm – DefenseStorm’s unique approach to providing cybersecurity and cyber-compliance for the banking industry make them one of the top startups to watch in 2021.  Their DefenseStorm GRID is the only co-managed, cloud-based and compliance-automated solution of its kind for the banking industry. It monitors everything on a bank’s network. It matches it to defined policies for real-time, complete and proactive cyber exposure readiness, keeping security teams and executives updated on bank networks’ real-time security status. The company’s Threat Ready Active Compliance (TRAC) Team augments its bank customers’ internal teams to protect business continuity and skills availability while ensuring cost-effective coverage and management.

Enso Security –  Enso is an application security posture management (ASPM) platform startup known for the depth of its insights and expertise in cybersecurity. With Enso, software security groups can scale and gain control over application security programs to protect applications systematically. The Enso ASPM platform discovers application inventory, ownership, and risk to help security teams quickly build and enforce security policies and transform AppSec into an automated, systematic discipline.

Ethyca –  Ethyca is an infrastructure platform that provides developers and product teams with the ability to ensure consumer data privacy throughout applications and services design. It also provides your product, engineering, and privacy teams with unmatched ease of use and functionality to better care about your user’s data. The company helps companies discover sensitive data and then provides a mechanism for customers to delete, see, or edit their data from the system. Ethyca’s mission is to increase trust in data-driven business by building automated data privacy infrastructure. Ethyca’s founder and CEO Cillian Kiernan is a fascinating person to speak with on the topics of privacy, security, GDPR, and CCPA compliance. He continues to set a quick pace of innovation in Ethyca, making this startup one of the most interesting in data privacy today. Here’s an interview he did earlier this year with France 24 English:

Havoc Shield – Havoc Shield reduces the burden on small and medium businesses (SMBs) by giving them access to advanced security technology that protects against data breaches, phishing, dark web activity, and other threats. The Havoc Shield platform offers comprehensive security and compliance features that meet the standards of Fortune 100 companies, making it easier for businesses working to win deals with those companies. “For a long time, cybersecurity technology has been virtually inaccessible to small businesses, who largely can’t afford those resources,” said Brian Fritton, CEO and co-founder of Havoc Shield. “We created Havoc Shield because we believe in democratizing cybersecurity for the little guy. Small businesses deserve the ability to protect what they’ve built, just as much as larger companies that have dedicated cybersecurity staff.” Since the end of Q2 2020, Havoc Shield has quadrupled its client list. In the coming months, the company aims to grow its team to help more small businesses protect themselves from threats and achieve customer trust.

Illumio – Widely considered the leader in micro-segmentation that prevents the spread of breaches inside data centers and cloud environments, Illumio is one of the most interesting cybersecurity startups to watch in 2021. Enterprises such as Morgan Stanley, BNP Paribas, Salesforce, and Oracle NetSuite use Illumio to reduce cyber risk and achieve regulatory compliance. The Illumio Adaptive Security Platform® uniquely protects critical information with real-time application dependency and vulnerability mapping coupled with micro-segmentation that works across any data center, public cloud, or hybrid cloud deployment on bare-metal, virtual machines, and containers. The following video explains why Illumio Core is a better approach to segmentation.

Immuta – Immuta was founded in 2015 based on a mission within the U.S. Intelligence Community to build a platform that accelerates self-service access to and control sensitive data. The Immuta Automated Data Governance platform creates trust across data engineering, security, legal, compliance, and business teams to ensure timely access to critical data with minimal risk while adhering to global data privacy regulations GDPR, CCPA, and HIPAA. Immuta’s automated, scalable, no-code approach makes it easy for users to access the data they need when they need it while protecting sensitive information and ensuring customer privacy. Selected by Fast Company as one of the World’s 50 Most Innovative Companies, Immuta is headquartered in Boston, MA, with offices in College Park, MD, and Columbus, OH.

Isovalent – Isovalent makes software that helps enterprises connect, monitor and secure mission-critical workloads in modern, cloud-native ways. Its flagship technology, Cilium, is the choice of leading global organizations, including Adobe, Capital One, Datadog, GitLab, and many more. Isovalent is headquartered in Mountain View, CA, and is backed by Andreessen Horowitz, Google and Cisco Investments. Earlier this month, Isovalent announced that it had raised $29 million in Series A funding, led by Andreessen Horowitz and Google with participation from Cisco Investments. Google recently selected Cilium as the next-generation dataplane for its GKE offering calling Cilium “the most mature eBPF implementation for Kubernetes out there” in its “New GKE Dataplane V2 increases security and visibility for containers” blog: https://cloud.google.com/blog/products/containers-kubernetes/bringing-ebpf-and-cilium-to-google-kubernetes-engine.

JupiterOne – JupiterOne, Inc. reduces cloud security cost and complexity, replacing guesswork with granular data about cyber assets and configurations. The company’s software helps security operations teams shorten the path to security and compliance and improve their overall posture through continuous data aggregation and relationship modeling across all assets. JupiterOne customers include Reddit, Databricks, HashiCorp, Addepar, Auth0, LifeOmic, and OhMD. Earlier this year, JupiterOne received $19 million in venture funding. The Series A round was led by Bain Capital Ventures, with additional investment from Rain Capital, LifeOmic, and individual investors. “JupiterOne has developed a compelling product that integrates quickly, has applicability across enterprise segments, and is highly reviewed by current customers,” said Enrique Salem, partner at Bain Capital Ventures and former CEO at Symantec. Salem now joins the JupiterOne board. “We see a multibillion-dollar market opportunity for this technology across mid-market and enterprise customers. Asset management is the first step in building a successful security program, and it’s currently a tedious, imperfect process that’s well-suited for automation.”

Lightspin –  Lightspin is a pioneer in contextual cloud security protecting native, Kubernetes, and microservices from known and unknown risks and has recently announced a $4 million seed funding round on November 24th. They will use the proceeds of the round to finance continued R&D on how to secure cloud infrastructures. The financing round was led by Ibex Investors LLC, the firm’s first global investment from its new $100 million early-stage fund, and also included participation from private angel investors. Lightspin’s technology uses graph-based tools and algorithms to provide rapid, in-depth visualizations of cloud stacks, analyze potential attack paths and detect the root causes, all of which are the most critical vulnerabilities that attackers can exploit.

Orca Security – Orca Security is noteworthy for its innovative approach to providing instant-on, workload-deep security for AWS, Azure, and GCP without the gaps in agents’ coverage and operational costs.Orca integrates cloud platforms as an interconnected web of assets, prioritizing risk based on environmental context. Delivered as SaaS, Orca Security’s patent-pending SideScanning™ technology reads cloud configuration and workloads’ runtime block storage out-of-band, detecting vulnerabilities, malware, misconfigurations, lateral movement risk, weak and leaked passwords, and unsecured PII.

SECURITI.ai – SECURITI.ai is an AI-Powered PrivacyOps company that helps automate all significant functions needed for privacy compliance on a single platform. It enables enterprises to grant individual and group rights to data and comply with global privacy regulations like CCPA and bolster their brands. They collect and manage consent from multiple sources, including web properties, web forms, and SaaS applications. Their AI-Powered PrivacyOps platform is a full-stack solution that operationalizes and simplifies privacy compliance using robotic automation and a natural language interface. SECURITI.ai was founded in November 2018 and is headquartered in San Jose, California.

SecureStack – SecureStack helps software developers find security & scalability gaps in their web applications and offers ways to fix those gaps without forcing them to become security experts. The results are faster time to business and a 60%-70% reduction in the app attack surface.

The SecureStack platform’s intelligent automation manages security controls across distributed infrastructures using rules and profiles customizable by customers. SecureStack is noteworthy for its analytics and logging expertise in helping enterprises scale applications across cloud infrastructures.

Stairwell – What makes Stairwell one of the top startups to watch in 2021 is its unique approach to cybersecurity built around a vision that all security teams should be able to determine what alerts are threat-related or not and why. Mike Wiacek, the founder of Google’s Threat Analysis Group and co-founder and former Chief Security Officer of Alphabet moonshot Chronicle, leads the company as its CEO and founder. Wiacek is joined by Jan Kang, former Chief Legal Officer at Chronicle, as COO and General Counsel. Stairwell is backed by Accel Venture Partners, Sequoia Capital, Gradient Ventures, and Allen & Company LLC.

Ubiq Security – What makes Ubiq Security one of the top cybersecurity startups to watch in 2021 is how rapidly their API-based developer platform is maturing while gaining traction in the market. Ubiq Security recently signed commercial agreements with the United States Army and the Department of Homeland Security. This month, the startup announced it had raised $6.4 million in a seed equity investment round. Okapi Venture Capital, an early investor in Crowdstrike, led the round with participation from TenOneTen Ventures, Cove Fund, DLA Piper Venture, Volta Global, and Alexandria Venture Investments. Ubiq will use the funds to accelerate platform development, developer relations, and customer acquisition.

Unit21 – Unit21 helps protect businesses against adversaries through a simple API and dashboard to detect and manage money laundering, fraud, and other sophisticated risks across multiple industries. Former Affirm and Shape Security employees Trisha Kothari and Clarence Chio founded Unit21 in 2018 and work with customers like Intuit, Coinbase, Gusto, and Line to create a powerful & customizable rules engine for risk and compliance teams. Unit21’s highly flexible, customizable, and intelligent cloud-based system provides a configurable engine for transaction monitoring, identity verification, case management, operations management, and analytics and reporting. On October 19th of this year, Unit21 announced a $13 million funding round led by A.Capital Ventures. Additional participation includes investors such as Gradient Ventures (Google’s A.I. venture fund), Core V.C., South Park Commons, Diane Greene (founder of VMWare), William Hockey (founder of Plaid), Chris Britt and Ryan King (founders of Chime), Sumit Agarwal (founder of Shape Security), and Michael Vaughan (former COO of Venmo). Unit21 will use the new capital to grow its product and distribution-focused management team, increase sales and marketing efforts, and sell into new industries.

Jul 25

10 Ways AI Is Improving New Product Development

10 Ways AI Is Improving New Product Development

  • Startups’ ambitious AI-based new product development is driving AI-related investment with $16.5B raised in 2019, driven by 695 deals according to PwC/CB Insights MoneyTree Report, Q1 2020.
  • AI expertise is a skill product development teams are ramping up their recruitment efforts to find, with over 7,800 open positions on Monster, over 3,400 on LinkedIn and over 4,200 on Indeed as of today.
  • One in ten enterprises now uses ten or more AI applications, expanding the Total Available Market for new apps and related products, including chatbots, process optimization and fraud analysis, according to MMC Ventures.

From startups to enterprises racing to get new products launched, AI and machine learning (ML) are making solid contributions to accelerating new product development. There are 15,400 job positions for DevOps and product development engineers with AI and machine learning today on Indeed, LinkedIn and Monster combined. Capgemini predicts the size of the connected products market will range between $519B to $685B this year with AI and ML-enabled services revenue models becoming commonplace.

Rapid advances in AI-based apps, products and services will also force the consolidation of the IoT platform market. The IoT platform providers concentrating on business challenges in vertical markets stand the best chance of surviving the coming IoT platform shakeout. As AI and ML get more ingrained in new product development, the IoT platforms and ecosystems supporting smarter, more connected products need to make plans now how they’re going to keep up. Relying on technology alone, like many IoT platforms are today, isn’t going to be enough to keep up with the pace of change coming.   The following are 10 ways AI is improving new product development today:

  • 14% of enterprises who are the most advanced using AI and ML for new product development earn more than 30% of their revenues from fully digital products or services and lead their peers is successfully using nine key technologies and tools. PwC found that Digital Champions are significantly ahead in generating revenue from new products and services and more than a fifth of champions (29%) earn more than 30% of revenues from new products within two years of information. Digital Champions have high expectations for gaining greater benefits from personalization as well. The following graphic from Digital Product Development 2025: Agile, Collaborative, AI-Driven and Customer Centric, PwC, 2020 (PDF, 45 pp.) compares Digital Champions’ success with AI and ML-based new product development tools versus their peers:

10 Ways AI Is Improving New Product Development

 

  • 61% of enterprises who are the most advanced using AI and ML (Digital Champions) use fully integrated Product Lifecycle Management (PLM) systems compared to just 12% of organizations not using AI/ML today (Digital Novices). Product Development teams the most advanced in their use of AL & ML achieve greater economies of scale, efficiency and speed gains across the three core areas of development shown below. Digital Champions concentrate on gaining time-to-market and speed advantages in the areas of Digital Prototyping, PLM, co-creation of new products with customers, Product Portfolio Management and Data Analytics and AI adoption:

10 Ways AI Is Improving New Product Development

  • AI is actively being used in the planning, implementation and fine-tuning of interlocking railway equipment product lines and systems.  Engineer-to-order product strategies introduce an exponential number of product, service and network options. Optimizing product configurations require an AI-based logic solver that can factor in all constraints and create a Knowledge Graph to guide deployment. Siemens’ approach to using AI to find the optimal configuration out of 1090 possible combinations provides insights into how AI can help with new product development on a large scale. Source: Siemens, Next Level AI – Powered by Knowledge Graphs and Data Thinking, Siemens China Innovation Day, Michael May, Chengdu, May 15, 2019.

10 Ways AI Is Improving New Product Development

  • Eliminating the roadblocks to getting new products launched starts with using AI to improve demand forecast accuracy. Honeywell is using AI to reduce energy costs and negative price variance by tracking and analyzing price elasticity and price sensitivity as well. Honeywell is integrating AI and machine-learning algorithms into procurement, strategic sourcing and cost management getting solid returns across the new product development process. Source: Honeywell Connected Plant: Analytics and Beyond. (23 pp., PDF, no opt-in) 2017 Honeywell User’s Group.

10 Ways AI Is Improving New Product Development

  • Relying on AI-based techniques to create and fine-tune propensity models that define product line extensions and add-on products that deliver the most profitable cross-sell and up-sell opportunities by product line, customer segment and persona. It’s common to find data-driven new product development and product management teams using propensity models to define the products and services with the highest probability of being purchased. Too often, propensity models are based on imported data, built-in Microsoft Excel, making their ongoing use time-consuming. AI is streamlining creation, fine-tuning and revenue contributions of up-sell and cross-sell strategies by automating the entire progress. The screen below is an example of a propensity model created in Microsoft Power BI.

10 Ways AI Is Improving New Product Development

  • AI is enabling the next generation of frameworks that reduce time-to-market while improving product quality and flexibility in meeting unique customization requirements on every customer order. AI is making it possible to synchronize better suppliers, engineering, DevOps, product management, marketing, pricing, sales and service to ensure a higher probability of a new product succeeding in the market. Leaders in this area include BMC’s Autonomous Digital Enterprise (ADE). BMC’s ADE framework shows the potential to deliver next-generation business models for growth-minded organizations looking to run and reinvent their businesses with AI/ML capabilities and deliver value with competitive differentiation enabled by agility, customer centricity and actionable insights. The ADE framework is capable of flexing and responding more quickly to customer requirements than competitive frameworks due to the following five factors: proven ability to deliver a transcendent customer experience; automated customer interactions and operations across distributed organizations; seeing enterprise DevOps as natural evolution of software DevOps; creating the foundation for a data-driven business that operates with a data mindset and analytical capabilities to enable new revenue streams; and a platform well-suited for adaptive cybersecurity. Taken together, BMC’s ADE framework is what the future of digitally-driven business frameworks look like that can scale to support AI-driven new product development. The following graphic compares the BMC ADE framework (left) and the eight factors driving digital product development as defined by PwC (right) through their extensive research. For more information on BMC’s ADE framework, please see BMC’s Autonomous Digital Enterprise site. For additional information on PwC’s research, please see the document Digital Product Development 2025: Agile, Collaborative, AI-Driven and Customer Centric, PwC, 2020 (PDF, 45 pp.).

10 Ways AI Is Improving New Product Development

  • Using AI to analyze and provide recommendations on how product usability can be improved continuously. It’s common for DevOps, engineering and product management to run A/B tests and multivariate tests to identify the usability features, workflows and app & service responses customers prefer. Based on personal experience, one of the most challenging aspects of new product development is designing an effective, engaging and intuitive user experience that turns usability into a strength for the product. When AI techniques are part of the core new product development cycle, including usability, delivering enjoyable customer experiences, becomes possible. Instead of a new app, service, or device is a chore to use, AI can provide insights to make the experience intuitive and even fun.
  • Forecasting demand for new products, including the causal factors that most drive new sales is an area AI is being applied to today with strong results. From the pragmatic approaches of asking channel partners, indirect and direct sales teams, how many of a new product they will sell to using advanced statistical models, there is a wide variation in how companies forecast demand for a next-generation product. AI and ML are proving to be valuable at taking into account causal factors that influence demand yet had not been known of before.
  • Designing the next generation of Nissan vehicles using AI is streamlining new product development, trimming weeks off new vehicle development schedules. Nissan’s pilot program for using AI to fast-track new vehicle designs is called DriveSpark. It was launched in 2016 as an experimental program and has since proven valuable for accelerating new vehicle development while ensuring compliance and regulatory requirements are met. They’ve also used AI to extend the lifecycles of existing models as well. For more information, see the article, DriveSpark, “Nissan’s Idea: Let An Artificial Intelligence Design Our Cars,” September 2016.
  • Using generative design algorithms that rely on machine learning techniques to factor in design constraints and provide an optimized product design. Having constraint-optimizing logic within a CAD design environment helps GM attain the goal of rapid prototyping. Designers provide definitions of the functional requirements, materials, manufacturing methods and other constraints. In May 2018, General Motors adopted Autodesk generative design software to optimize for weight and other key product criteria essential for the parts being designed to succeed with additive manufacturing. The solution was recently tested with the prototyping of a seatbelt bracket part, which resulted in a single-piece design that is 40% lighter and 20% stronger than the original eight component design. Please see the Harvard Business School case analysis, Project Dreamcatcher: Can Generative Design Accelerate Additive Manufacturing? for additional information.

Additional reading:

2020 AI Predictions, Five ways to go from reality check to real-world payoff, PwC Consulting

Accenture, Manufacturing The Future, Artificial intelligence will fuel the next wave of growth for industrial equipment companies (PDF, 20 pp., no opt-in)

AI Priorities February 2020 5 ways to go from reality check to real-world pay off, PwC, February, 2020 (PDF, 16 pp.)

Anderson, M. (2019). Machine learning in manufacturing. Automotive Design & Production, 131(4), 30-32.

Bruno, J. (2019). How the IIoT can change business models. Manufacturing Engineering, 163(1), 12.

Digital Factories 2020: Shaping The Future Of Manufacturing, PwC DE., 2017 (PDF, 48 pp.)

Digital Product Development 2025: Agile, Collaborative, AI Driven and Customer Centric, PwC, 2020 (PDF, 45 pp.)

Enabling a digital and analytics transformation in heavy-industry manufacturing, McKinsey & Company, December 19, 2019

Global Digital Operations 2018 Survey, Strategy&, PwC, 2018

Governance and Management Economics, 7(2), 31-36.

Greenfield, D. (2019). Advice on scaling IIoT projects. ProFood World

Hayhoe, T., Podhorska, I., Siekelova, A., & Stehel, V. (2019). Sustainable manufacturing in industry 4.0: Cross-sector networks of multiple supply chains, cyber-physical production systems and AI-driven decision-making. Journal of Self-

Industry’s fast-mover advantage: Enterprise value from digital factories, McKinsey & Company, January 10, 2020

Kazuyuki, M. (2019). Digitalization of manufacturing process and open innovation: Survey results of small and medium-sized firms in japan. St. Louis: Federal Reserve Bank of St Louis.

‘Lighthouse’ manufacturers lead the way—can the rest of the world keep up?  McKinsey & Company, January 7, 2019

Machine Learning in Manufacturing – Present and Future Use-Cases, Emerj Artificial Intelligence Research, last updated May 20, 2019, published by Jon Walker

Machine learning, AI are most impactful supply chain technologies. (2019). Material Handling & Logistics

MAPI Foundation, The Manufacturing Evolution: How AI Will Transform Manufacturing & the Workforce of the Future by Robert D. Atkinson, Stephen Ezell, Information Technology and Innovation Foundation (PDF, 56 pp., opt-in)

Mapping heavy industry’s digital-manufacturing opportunities, McKinsey & Company, September 24, 2018

McKinsey, AI in production: A game changer for manufacturers with heavy assets, by Eleftherios Charalambous, Robert Feldmann, Gérard Richter and Christoph Schmitz

McKinsey, Digital Manufacturing – escaping pilot purgatory (PDF, 24 pp., no opt-in)

McKinsey, Driving Impact and Scale from Automation and AI, February 2019 (PDF, 100 pp., no opt-in).

McKinsey, ‘Lighthouse’ manufacturers, lead the way—can the rest of the world keep up?,by Enno de Boer, Helena Leurent and Adrian Widmer; January, 2019.

McKinsey, Manufacturing: Analytics unleashes productivity and profitability, by Valerio Dilda, Lapo Mori, Olivier Noterdaeme and Christoph Schmitz, March, 2019

McKinsey/Harvard Business Review, Most of AI’s business uses will be in two areas,

Morey, B. (2019). Manufacturing and AI: Promises and pitfalls. Manufacturing Engineering, 163(1), 10.

Preparing for the next normal via digital manufacturing’s scaling potential, McKinsey & Company, April 10, 2020

Reducing the barriers to entry in advanced analytics. (2019). Manufacturing.Net,

Scaling AI in Manufacturing Operations: A Practitioners Perspective, Capgemini, January, 2020

Seven ways real-time monitoring is driving smart manufacturing. (2019). Manufacturing.Net,

Siemens, Next Level AI – Powered by Knowledge Graphs and Data Thinking, Siemens China Innovation Day, Michael May, Chengdu, May 15, 2019

Smart Factories: Issues of Information Governance Manufacturing Policy Initiative School of Public and Environmental Affairs Indiana University, March 2019 (PDF, 68 pp., no opt-in)

Smartening up with Artificial Intelligence (AI) – What’s in it for Germany and its Industrial Sector? (52 pp., PDF, no opt-in) McKinsey & Company.

Team predicts the useful life of batteries with data and AI. (2019, March 28). R & D.

The AI-powered enterprise: Unlocking the potential of AI at scale, Capgemini Research, July 2020

The Future of AI and Manufacturing, Microsoft, Greg Shaw (PDF, 73 pp., PDF, no opt-in).

The Rise of the AI-Powered Company in the Postcrisis World, Boston Consulting Group, April 2, 2020

Top 8 Data Science Use Cases in Manufacturing, ActiveWizards: A Machine Learning Company Igor Bobriakov, March 12, 2019

Walker, M. E. (2019). Armed with analytics: Manufacturing as a martial art. Industry Week

Wang, J., Ma, Y., Zhang, L., Gao, R. X., & Wu, D. (2018). Deep learning for smart manufacturing: Methods and applications. Journal of Manufacturing Systems, 48, 144–156.

Zulick, J. (2019). How machine learning is transforming industrial production. Machine Design

Feb 20

Top 25 IoT Startups To Watch In 2019

 

  • 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:

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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:

  1. 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:

  1. 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.
  2. 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.
  3. 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.
  4. 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:

  1. 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.
  2. 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.
  3. 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.
  4. 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:

  1. 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.
  2. 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.
  3. 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:

  1. 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.
  2. 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:

  1. 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
  2. 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.
  3. 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.
  4. 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.
  5. 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.

Oct 22

1 Comment

The Top 100 Enterprise Analytics Startups Of 2014

public-cloud-computing-forecast-2011-2016With the potential of removing legacy IT silos and freeing up valuable data to gain greater insights into their operations, enterprises continue to invest heavily in analytics.

Providing powerful analytics tools to business analysts who can get to work immediately on complex challenges instead of having to wait for ITs’ often over-committed resources is also driving analytics market growth. The better a business unit or division gets at understanding their own business, the faster they change their future.

Analytics Are Streamlining Industry Value Chains

Across every area of an enterprise, from supply chains, quality, manufacturing, marketing, services and pricing, analytics are making an impact daily.  IDC forecast that the advanced and predictive analytics software market will grow from $2.2B in 2013 to $3.4B in 2018, attaining a 9.9% compound annual growth rate (CAGR).  Wikibon’s excellent analysis of the Big Data market projects a $28.5B market in 2014, growing to $50.1B in 2015. For additional forecasts please see my post Roundup Of Analytics, Big Data & Business Intelligence Forecasts And Market Estimates, 2014.

Admit It: Analytics Startups Are the Sexiest Of All

The field of analytics is proliferating with entirely new approaches to solve very challenging, difficult problems, removing the barriers that held business analysts and the divisions they work for from accomplishing more.

That’s what makes analytics startups the sexiest of all. With the insights these companies are capable of delivering you can completely change your approach to marketing, selling, service, supply chains, pricing, service and over time reach an entirely new level of performance. There are many excellent startups in this arena and I’ve been tracking many of them out of personal interest for years.

Tracking Analytics Startups

Having seen just how much pain there is in enterprises trying to get the data they need to better manage their business units, divisions and departments, I’ve tracked many of the analytics startups mentioned in the list below.  Using manually-based methods to track their funding rounds and momentum in the market proved incomplete.

To gain a greater insight into analytics startups I signed up for a free first month trial of Mattermark (opt in).  Mattermark uses a combination of artificial intelligence and data quality analysis to provide insights into over 500,000 companies, over 125,000 with employee data, and over 90,000 funding events.  It’s a fascinating company that has created many new metrics for tracking momentum of startups on specific metrics and key performance indicators (KPIs) including their own Mattermark score.  This score is not meant to provide guidance on which startup to invest in.  Rather it’s a measure of momentum across the metrics and KPIs that Mattermark measures.   Their service is easy to use, powerful in the insight it delivers, and produced the following list of 100 enterprise analytics startups, ranked by total funding in the table below.  You can download the table here in Microsoft Excel format as well.

Top 100 Enterprise Analytics Startups Infographic

 

%d bloggers like this: