startup

Dataloop secures cash infusion to expand its data annotation tool set • ZebethMedia

By zebethcontrolPosted on November 3, 2022Posted in AI, data labeling, Enterprise, machine learning, Robotics & AI, startup, StartupsNo Comments

Data annotation, or the process of adding labels to images, text, audio and other forms of sample data, is typically a key step in developing AI systems. The vast majority of systems learn to make predictions by associating labels with specific data samples, like the caption “bear” with a photo of a black bear. A system trained on many labeled examples of different kinds of contracts, for example, would eventually learn to distinguish between those contracts and even extrapolate to contracts that it hasn’t seen before. The trouble is, annotation is a manual and labor-intensive process that’s historically been assigned to gig workers on platforms like Amazon Mechanical Turk. But with the soaring interest in AI — and in the data used to train that AI — an entire industry has sprung up around tools for annotation and labeling. Dataloop, one of the many startups vying for a foothold in the nascent market, today announced that it raised $33 million in a Series B round led by Nokia Growth Partners (NGP) Capital and Alpha Wave Global. Dataloop develops software and services for automating aspects of data prep, aiming to shave time off of the AI system development process. “I worked at Intel for over 13 years, and that’s where I met Dataloop’s second co-founder and CPO, Avi Yashar,” Dataloop CEO Eran Shlomo told ZebethMedia in an email interview. “Together with Avi, I left Intel and founded Dataloop. Nir [Buschi], our CBO, joined us as third co-founder, after he held executive positions [at] technology companies and [lead] business and go-to-market at venture-backed startups.” Dataloop initially focused on data annotation for computer vision and video analytics. But in recent years, the company has added new tools for text, audio, form and document data and allowed customers to integrate custom data applications developed in-house. One of the more recent additions to the Dataloop platform is data management dashboards for unstructured data. (As opposed to structured data, or data that’s arranged in a standardized format, unstructured data isn’t organized according to a common model or schema.) Each provides tools for data versioning and searching metadata, as well as a query language for querying datasets and visualizing data samples. Image Credits: Dataloop “All AI models are learned from humans through the data labeling process. The labeling process is essentially a knowledge encoding process in which a human teaches the machine the rules using positive and negative data examples,” Shlomo said. “Every AI application’s primary goal is to create the ‘data flywheel effect’ using its customer’s data: a better product leads to more users leads to more data and subsequently a better product.” Dataloop competes against heavyweights in the data annotation and labeling space, including Scale AI, which has raised over $600 million in venture capital. Labelbox is another major rival, having recently nabbed more than $110 million in a financing round led by SoftBank. Beyond the startup realm, tech giants, including Google, Amazon, Snowflake and Microsoft, offer their own data annotation services. Dataloop must be doing something right. Shlomo claims the company currently has “hundreds” of customers across retail, agriculture, robotics, autonomous vehicles and construction, although he declined to reveal revenue figures. An open question is whether Dataloop’s platform solves some of the major challenges that exist in data labeling today. Last year, a paper published out of MIT found that data labeling tends to be highly inconsistent, potentially harming the accuracy of AI systems. A growing body of academic research suggests that annotators introduce their own biases when labeling data — for example, labeling phrases in African American English (a modern dialect spoken primarily by Black Americans) as more toxic than the general American English equivalents. These biases often manifest in unfortunate ways; think moderation algorithms that are more likely to ban Black users than white users. Data labelers are also notoriously underpaid. The annotators who contributed captions to ImageNet, one of the better-known open source computer vision libraries, reportedly made a median of $2 per hour in wages. Shlomo says it’s incumbent on the companies using Dataloop’s tools to affect change — not necessarily Dataloop itself. “We see the underpayment of annotators as a market failure. Data annotation shares many qualities with software development, one of them being the impact of talent on productivity,” Shlomo said. “[As for bias,] bias in AI starts with the question that the AI developer chooses to ask and the instructions they supply to the labeling companies. We call it the ‘primary bias.’ For example, you could never identify color bias unless you ask for skin color in your labeling recipe. The primary bias issue is something the industry and regulators should address. Technology alone will not solve the issue.” To date, Dataloop, which has 60 employees, has raised $50 million in venture capital. The company plans to grow its workforce to 80 employees by the end of the year.

OpenAI will give roughly 10 AI startups $1M each and early access to its systems • ZebethMedia

By zebethcontrolPosted on November 2, 2022Posted in AI, artificial intelligence, funding, OpenAI, Robotics & AI, startup, Startups, VentureNo Comments

OpenAI, the San Francisco-based lab behind AI systems like GPT-3 and DALL-E 2, today launched a new program to provide early-stage AI startups with capital and access to OpenAI tech and resources. Called Converge, the cohort will be financed by the OpenAI Startup Fund, OpenAI says. The $100 million entrepreneurial tranche was announced last May and was backed by Microsoft and other partners. The 10 or so founders chosen for Converge will receive $1 million each and admission to five weeks of office hours, workshops and events with OpenAI staff, as well as early access to OpenAI models and “programming tailored to AI companies.” “We’re excited to meet groups across all phases of the seed stage, from pre-idea solo founders to co-founding teams already working on a product,” OpenAI writes in a blog post shared with ZebethMedia ahead of today’s announcement. “Engineers, designers, researchers, and product builders … from all backgrounds, disciplines, and experience levels are encouraged to apply, and prior experience working with AI systems is not required.” The deadline to apply is November 25, but OpenAI notes that it’ll continue to evaluate applications after that date for future cohorts. When OpenAI first detailed the OpenAI Startup Fund, it said recipients of cash from the fund would receive access to Azure resources from Microsoft. It’s unclear whether the same benefit will be afforded to Converge participants; we’ve asked OpenAI to clarify. We’ve also asked OpenAI to disclose the full terms for Converge, including the equity agreement, and we’ll update this piece once we hear back. Beyond Converge, surprisingly, there aren’t many incubator programs focused exclusively on AI startups. The Allen Institute for AI has a small accelerator that launched in 2017, which provides up to a $500,000 pre-seed investment and up to $450,000 in cloud compute credits. Google Brain founder Andrew Ng heads up the AI Fund, a $175 million tranche to initiate new AI-centered businesses and companies. And Nat Friedman (formerly of GitHub) and Daniel Gross (ex-Apple) fund the AI Grant, which provides up to $250,000 for “AI-native” product startups and $250,000 in cloud credits from Azure. With Converge, OpenAI is no doubt looking to cash in on the increasingly lucrative industry that is AI. The Information reports that OpenAI — which itself is reportedly in talks to raise cash from Microsoft at a nearly $20 billion valuation — has agreed to lead financing of Descript, an AI-powered audio and video editing app, at a valuation of around $550 million. AI startup Cohere is said to be negotiating a $200 million round led by Google, while Stability AI, the company supporting the development of generative AI systems, including Stable Diffusion, recently raised $101 million. The size of the largest AI startup financing rounds doesn’t necessarily correlate with revenue, given the enormous expenses (personnel, compute, etc.) involved in developing state-of-the-art AI systems. (Training Stable Diffusion alone cost around $600,000, according to Stability AI.) But the continued willingness of investors to cut these startups massive checks — see Inflection AI‘s $225 million raise, Anthropic’s $580 million in new funding and so on — suggests that they have confidence in an eventual return on investment.

Alation bags $123M at a $1.7B valuation for its data-cataloging software • ZebethMedia

By zebethcontrolPosted on November 2, 2022Posted in AI, Alation, data catalog, Enterprise, funding, startup, StartupsNo Comments

There’s been an explosion of enterprise data in recent years, accelerated by pandemic-spurred digital transformations. An IDC report commissioned by Seagate projected companies would collect 42.2% more data by year-end 2022 than in 2020, amounting to multiple petabytes of data in total. While more data is generally a good thing, particularly where it concerns analytics, large volumes can be overwhelming to organize and govern — even for the savviest of organizations. That’s why Satyen Sangani, a former Oracle VP, co-founded Redwood City–based Alation, a startup that helps crawl a company’s databases in order to build data search catalogs. After growing its customer base to over 450 brands and annual recurring revenue (ARR) to over $100 million, Alation has raised $123 million in a Series E round led by Thoma Bravo, Sanabil Investments, and Costanoa Ventures with participation from Databricks Ventures, Dell Technologies Capital, Hewlett Packard Enterprise, Icon Ventures, Queensland Investment Corporation, Riverwood Capital, Salesforce Ventures, Sapphire Ventures and Union Grove, the company announced today. The all-equity tranche values Alation at over $1.7 billion — an impressive 15 times higher than the company’s previous valuation in a challenging economic climate. In an interview with ZebethMedia, Sangani said the new capital — which brings Alation’s total raised to $340 million — will be put toward investments in product development (including through acquisitions) and expanding Alation’s sales, engineering and marketing teams, with a focus on the public sector and corporations based in Asia Pacific, Europe, Latin America and the Middle East. “With the capital, we will continue to focus on engagement and adoption, collaboration, governance, lineage, and on APIs and SDKs to enable us to be open and extensible,” Sangani said via email. “We’re going to bring innovation to the market that will increase the number of data assets we cover and the people who will leverage and access Alation.” With Alation, Sangani and his fellow co-founders — Aaron Kalb, Feng Niu and Venky Ganti — sought to build a service that enables data and analytics teams to capture and understand the full breadth of their data. The way Sangani sees it, most corporate leadership wants to build a “data-driven” culture but is stymied by tech hurdles and a lack of knowledge about what data they have, where it lives, whether it’s trustworthy and how to make the best use of it. Alation’s platform organizes data across disparate systems. Image Credits: Alation According to Forrester, somewhere between 60% and 73% of data produced by enterprises goes unused for analytics. And if a recent poll by Oracle is to be believed, 95% of people say they’re overwhelmed by the amount of data available to them in the workplace. “With the astounding amount of data being produced today, it’s increasingly difficult for companies to collect, structure, and analyze the data they create,” Sangani said. “The modern enterprise relies on data intelligence and data integration solutions to provide access to valuable insights that feed critical business outcomes. Alation is foundational for driving digital transformation.” Alation uses machine learning to automatically parse and organize data like technical metadata, user permissions and business descriptions from sources like Redshift, Hive, Presto, Spark and Teradata. Customers can visually track the usage of assets like business glossaries, data dictionaries and Wiki articles through the Alation platform’s reporting feature, or they can use Alation’s collaboration tools to create lists, annotations, comments and polls to organize data across different software and systems. Alation also makes recommendations based on how information is being used and orchestrated. For example, the platform suggests ways customers can centrally manage their data and compliance policies through the use of integrations and data connectors. “Alation’s machine learning contributes to data search, data stewardship, business glossary, and data lineage,” Sangani said. “More specifically, Alation’s behavioral analysis engine spots behavioral patterns and leverages AI and machine learning to make data more user-friendly. For example, search is simplified by highlighting the most popular assets; stewardship is eased by emphasizing the most active data sets; and governance becomes a part of workflow through flags and suggestions.” According to IDC, the data integration and intelligence software market is valued at more than $7.9 billion and growing toward $11.6 billion over the next four years. But Alation isn’t the sole vendor. The startup’s competition includes incumbents like Informatica, IBM, SAP and Oracle, as well as newer rivals such as Collibra, Castor, Stemma, Data.World and Ataccama, all of whom offer tools for classifying and curating data at enterprise scale. One of Alation’s advantages is sheer momentum, no doubt — its customer base includes heavyweights like Cisco, General Mills, Munich Re, Pfizer, Nasdaq and Salesforce, in addition to government agencies such as the Environmental Protection Agency and Australia’s Department of Defense. Alation counts more than 25% of the Fortune 100 as clients, touching verticals such as finance, healthcare, pharma, manufacturing, retail, insurance and tech. In terms of revenue coming in, Sangani claims that Alation — which has more than 700 employees and expects to be at just under 800 by 2023 — is in a healthy position, pegging the firm’s cumulative-cash-burn-to-ARR ratio at around 1.5x. Despite the downturn, he asserts that customer spend is remaining strong as the demand for data catalog software grows; for the past five quarters, Alation’s ARR has increased year over year. In another win for Alation, the investment from Databricks Ventures is strategic, Sangani says. It’ll see the two companies jointly develop engineering, data science and analytics applications that leverage both Databricks’ and Alations’ platforms. “The most successful data intelligence platforms will be adopted by everyone. Vendors that are jack-of-all-trades, but masters of none, promise everything and succeed at little. Similarly, point products achieve limited success, but only serve to create data silos that our customers are trying to avoid. The future of data intelligence is about connectedness and integration,” Sangani said. “We know that and will continue to put our money behind our beliefs.”

Former Yext CEO launches Roam to provide a virtual HQ for distributed teams • ZebethMedia

By zebethcontrolPosted on November 2, 2022Posted in Enterprise, funding, IVP, remote work, Roam, startup, StartupsNo Comments

Roam, which bills itself as a “cloud HQ” for distributed, remote companies, today emerged from stealth with $30 million in Series A funding led by IVP with participation from undisclosed angel investors. The tranche, which comes after a previously unannounced $10.6 million seed round and values the company at $95 million post-money, will be put toward go-to-market efforts in the U.S. and abroad, CEO Howard Lerman said. Lerman previously co-founded and led Yext, the publicly traded brand management company that uses a cloud-based network of apps and search engines to keep company information up to date across the web. When Yext’s workforce transitioned to remote work during the pandemic, Lerman perceived that employees lost “spontaneity and serendipity,” spent more time in meetings and began to lose visibility into what other meetings were going on and what their colleagues were doing. “I had this flash of insight — what if there was a bird’s-eye view of all the Zooms going on at a company at the same time that everyone could see? And better yet, what if people could move between and among them so they could participate as necessary and then quickly be on to their next thing?” Lerman told ZebethMedia via email. To Lerman’s point, shifts to a mostly remote workforce don’t occur overnight. One survey suggests that nearly half of employees — 46% — find remote work, at least in the early stages, can make it more difficult to maintain professional relationships with key stakeholders. That inspired Roam, which provides what Lerman describes as cloud-based “flex spaces” for workers at home, in offices and in the field. Roam’s Map View lets workers see what’s going on and have “project presence,” Lerman says, as well as chat with colleagues via text or video chat. Lerman didn’t reveal much beyond that — it’s early days for Roam, which currently has around 40 corporate customers. But he argued that the platform as it exists today can save substantial time compared to typical remote setups. Image Credits: Roam “I found my own personal meeting minutes dropped by more than 40% when I switched from Zoom to Roam from 4.5 hours per day to 2.6 hours per day. My average meeting time in Roam is eight minutes, an astounding number when you think about the prescheduled world of 30- and 60-minute Zoom time blocks,” Lerman said. Shorter and fewer meetings can lead to cost savings through improved productivity. One recent study out of the University of North Carolina found that unnecessary meetings waste about $25,000 per employee annually, translating to $101 million a year for any organization with over 5,000 staffers. Roam isn’t the first startup to attempt to tackle challenges around remote work with a cloud-based workspace. In fact, there are dozens of virtual HQ platforms, some venture-backed and some bootstrapped, mixing gamification and productivity into a service. In August, Kumospace raised $21 million for its platform that leverages lo-fi graphics and game-like mechanics to create a sense of togetherness. Gather is another big winner (despite layoffs) in the space, having raised $77 million in total from investors, including Sequoia, Index and Y Combinator. It’s not just startups. This summer, Microsoft launched Viva Engage, an in-house social media app for employee engagement. Other companies are piloting VR and apps such as Oculus for Business or Horizon Workrooms, aiming to boost collaboration with immersive meetings for remote workers. But Lerman believes strongly that Roam is differentiated, having invested the entirety of the seed round himself. He points out that as many as 77% of U.S.-based jobs are now either remote or hybrid, according to a March 2022 Gallup poll, representing a huge potential customer base. Indeed, after more than two years of remote work, many employees have no interest in returning to the office. Not all businesses are behind the changes, but there’s no denying that the pandemic rewrote the rules around the workplace — to the benefit of startups like Roam, potentially. “We are in the midst of a massive platform shift from in-office workplaces to various remote and hybrid models. In pre-pandemic 2019, [only] 40% of US jobs were either remote or hybrid,” Lerman said. “The pandemic has significantly accelerated the rate of distributed businesses and the need for a cloud HQ. No matter the size or how well they are faring, the future of work is a top issue for nearly every company right now.” Roam has 15 employees and plans to hire five more by the end of the year. Lerman declined to reveal financials, including revenue figures, when asked.

MLOps platform Galileo lands $18M to launch a free service • ZebethMedia

By zebethcontrolPosted on November 1, 2022Posted in AI, Enterprise, funding, machine learning, MLops, Robotics & AI, startup, StartupsNo Comments

Galileo, a startup launching a platform for AI model development, today announced that it raised $18 million in a Series A round led by Battery Ventures with participation from The Factory, Walden Catalyst, FPV Ventures, Kaggle co-founder Anthony Goldbloom and other angel investors. The new cash brings the company’s total raised to $23.1 million and will be put toward growing Galileo’s engineering and go-to-market teams and expanding the core platform to support new data modalities, CEO Vikram Chatterji told ZebethMedia via email. As the use of AI becomes more common throughout the enterprise, the demand for products that make it easier to inspect, discover and fix critical AI errors is increasing. According to one recent survey (from MLOps Community), 84.3% of data scientists and machine learning engineers say that the time required to detect and diagnose problems with a model is a problem for their teams, while over one in four (26.2%) admit that it takes them a week or more to detect and fix issues. Some of those issues include mislabeled data, where the labels used to train an AI system contain errors, like a picture of a tree mistakenly labeled “houseplant.” Others pertain to data drift or data imbalance, which happens when data evolves to make an AI system less accurate (think a stock market model trained on pre-pandemic data) or the data isn’t sufficiently representative of a domain (e.g., a data set of headshots has more light-skinned people than dark-skinned). Galileo’s platform aims to systematize AI development pipelines across teams using “auto-loggers” and algorithms that spotlight system-breaking issues. Built to be deployable in an on-premises environment, Galileo scales across the AI workflow — from predevelopment to postproduction — as well as unstructured data modalities like text, speech and vision. In data science, “unstructured” data usually refers to data that’s not arranged according to a preset data model or schema, like invoices or sensor data. Atindriyo Sanyal — Galileo’s second co-founder — makes the case that the Excel- and Python script–based processes to ensure quality data is being fed into models are manual, error-prone and costly. A screenshot of the Galileo Community Edition. Image Credits: Galileo “When inspecting their data with Galileo, users instantly uncover the long tail of data errors such as mislabeled data, underrepresented languages [and] garbage data that they can immediately take action upon within Galileo by removing, re-labeling or by adding additional similar data from production,” Sanyal told ZebethMedia in an email interview. “It has been critical for teams that Galileo supports machine learning data workflows end to end — even when a model is in production, Galileo automatically lets teams know of data drifts, and surfaces the highest-value data to train with next.” The co-founding team at Galileo spent more than a decade building machine learning products, where they say they faced the challenges of developing AI systems firsthand. Chatterji led product management at Google AI, while Sanyal spearheaded engineering at Uber’s AI division and was an early member of the Siri team at Apple. Third Galileo co-founder Yash Sheth is another Google veteran, having previously led the company’s speech recognition platform team. Galileo’s platform falls into the burgeoning category of software known as MLOps, a set of tools to deploy and maintain machine learning models in production. It’s in serious demand. By one estimation, the market for MLOps could reach $4 billion by 2025. There’s no shortage of startups going after the space, like Comet, which raised $50 million last November. Other vendors with VC backing include Arize, Tecton, Diveplane, Iterative and Taiwan-based InfuseAI. But despite having launched just a few months ago, Galileo has paying customers from “high-growth” startups to Fortune 500 companies, Sanyal claims. “Our customers are using Galileo while building machine learning applications such as hate speech detection, caller intent detection at contact centers and customer experience augmentation with conversational AI,” he added. Sanyal expects the launch of Galileo’s free offering — Galileo Community Edition — will boost sign-ups further. The Community Edition enables data scientists working on natural language processing to build machine learning models using some of the tools included in the paid version, Sanyal said. “With Galileo Community Edition, anyone can sign up for free, add a few lines of code while training their model with labeled data or during an inference run with unlabeled data to instantly inspect, find and fix data errors, or select the right data to label next using the powerful Galileo UI,” he added. Sanyal declined to share revenue figures when asked. But he noted that San Francisco–based Galileo’s headcount has grown in size from 14 people in May to “more than” 20 people as of today.

Qwick raises VC money to match gig workers with hospitality jobs • ZebethMedia

By zebethcontrolPosted on November 1, 2022Posted in Apps, gig work, hospitality, labor, startup, StartupsNo Comments

Leisure and hospitality workers are quitting at the highest rates of any industry. About 1 million left the workforce in November 2021 alone, according to the U.S. Bureau of Labor Statistics. Why? Seasonality, low pay and monotonous work are among the reasons for the hospitality industry’s churn rate, as well as a perceived lack of career advancement. So what are hospitality businesses to do? Perhaps turn to services like Qwick, a startup that matches workers with hospitality gig contracts. Qwick today announced that it raised $40 million in a Series B financing round led by Tritium Partners, with participation by current investors Album VC, Kickstart, Desert Angels and Revolution’s Rise of the Rest Seed Fund. Jamie Baxter co-founded Qwick in 2017 with Chris Loeffler. Baxter was previously the segment tech director of risk and financial services at Willis Towers Watson, where he oversaw product and software development. With Qwick, Baxter sought to build a platform that connects service industry workers with food and beverage shifts in real time. Qwick uses a matching algorithm that takes into account factors like distance, the availability of “VIP” workers and supply to fill gigs for hospitality businesses, including stadiums, senior living facilities and corporate catering. “The hospitality industry has been plagued with reputations of low retention rates, low wages and poor management and working conditions for decades,” Baxter told ZebethMedia in an email interview. “Qwick aims to combat the issues of working in the industry and reshape what it means to work in hospitality by creating value for its professionals and offering them a livable wage.” To sign up for Qwick, workers have to complete a profile and watch a five-minute virtual orientation. Once they’re vetted, they receive notifications for open shifts. “Qwick requires incoming professionals to go through an orientation including a one-to-one interview,” Baxter said. “Before being granted access to the platform, all Qwick professionals have been certified and vetted for experience, professionalism and commitment to service.” Baxter also says that Qwick utilizes a two-way, five-star rating system to “ensure continued quality and reliability between professionals and businesses,” although it bears noting that similar ratings systems on gig marketplaces have been found to exacerbate biases against minority workers, Booking gigs through Qwick’s mobile app. Image Credits: Qwick Qwick is akin to startups like Stint, Flexy, Indeed Flex, Gig, Limber and Baristas on Tap, which provide short-term workers to businesses across a number of industries. Advocates for the platforms say that they’re making hospitality into a more financially viable profession by increasing job flexibility. But a recent Eater piece found that some workers on hospitality gig startups take home around the local minimum wage and might be forced to make lengthy unpaid commutes. Critics allege that the platforms could leave businesses with less budget for recruitment and training, encouraging them to replace full-time positions with temporary work. Some hospitality employers have signaled they’re willing to embrace temp workers potentially at the expense of salaried employees. In 2017 and 2018, Marriott and Hilton joined with Airbnb and the TechNet coalition (which includes Uber, Lyft and Taskrabbit) to lobby for a federal bill that would classify anyone who finds work through an online platform as an independent contractor. Baxter pushes back against the notion that Qwick is a force for ill, arguing it provides workers with the “freedom” to work on their schedules. “Thousands of business partners across the U.S. rely on Qwick to end understaffing … [We] only partner with reputable businesses known to treat their staff well, and give professionals the agency to work where and when they want,” Baxter said. “Hundreds of thousands of industry professionals have downloaded our app and signed up to work shifts through Qwick.” Qwick workers are paid an average of $9 above minimum wage in the cities where they work, Baxter added. He also noted that Qwick allows businesses to hire gig workers for traditional off-platform employment at no extra cost, unlike some gig work platforms that impose recruitment and hiring fees. In any case, the demand for Qwick’s service seems very robust on the employer side. After a rough patch during the pandemic — Qwick was forced to lay off 70% of the team, and Baxter stopped taking a salary — business has more than recovered, with revenue having grown an astounding 10,000% over the past three years, according to Baxter. And for better or worse, the gig economy shows no signs of contracting. The Pew Research Center reports that 16% of Americans have completed a job via an online gig platform. And Mastercard predicts that the number of global gig workers will rise to 78 million in 2023, up from 43 million in 2018. Qwick is actively working with over 7,000 businesses across 23 metro areas, and the platform has facilitated over 500,000 shifts so far, Baxter added. Qwick’s investors, for one, appear to be confident in Qwick’s long-term trajectory, whether or not it results in the best outcome for workers. In an emailed statement, Tritium Partners managing partner David Lack said: “Qwick’s impressive growth and history achieving success through its innovative hospitality solution, even through an especially challenging few years for the industry, indicate that the company has truly changed the way people work.” To date, Arizona-based Qwick has raised $69.1 million in capital. The company has a staff of just over 270, which Baxter says will expand to around 300 before the end of the year.

Cover Genius lands $70M infusion to grow its embedded insurance business • ZebethMedia

By zebethcontrolPosted on November 1, 2022Posted in Commerce, Dawn Capital, Fintech, insurtech, King River Capital, startupNo Comments

In 2014, Angus McDonald, the former head of publisher partnerships at Yahoo (full disclosure: ZebethMedia’s parent company), teamed up with ex-Googler Chris Bayley to found Cover Genius, an insurtech platform that prices and handles claims for virtually any line of insurance or warranty. After expanding the business to all 50 U.S. states and more than 60 countries, Cover Genius is gearing up for its next phase of growth, McDonald says, fueled by significant fresh capital. Cover Genius today announced that it raised $70 million in a Series D round led by Dawn Capital with participation from Atlas Merchant Capital, GSquared and King River Capital. Bringing the 420-person company’s total raised to $165 million, McDonald tells ZebethMedia that the proceeds will be put toward “assisting business growth” and further expanding Cover Genius’ insurance distribution services. “We’ve co-created a wide range of protection solutions for partners across many verticals including several of the world’s largest airlines and travel companies, retailers and logistics players, mobility, auto and gig economy companies, banks, fintechs and proptechs and business-to-business software and event ticketing companies,” McDonald said in an email interview. “Having been bootstrapped in our early days, only raising $1 million from inception in 2014 to our Series B in 2018, we’ve been blessed to have significant partners to ensure a healthy and sustainable cash flow, while also carrying frugality in our DNA.” McDonald and Bayley were motivated to launch Cover Genius after encountering insurance challenges with their previous joint venture, an international online travel agency. They found that traditional insurers were difficult to work with because every country the co-founders wanted to target required a separate insurance agreement with separate country leads. In creating Cover Genius, McDonald and Bayley worked to gain licensing and approvals for embedded insurance in most major countries around the world. Unlike typical insurance plans, embedded insurance like Cover Genius’ is bundled with the purchase of a product or service, offered in real time or at the point of sale. Ridesharing app Ola uses Cover Genius to offer insurance to both drivers and riders. Betterplace, an India-based human resources management software provider, taps Cover Genius’ technology to provide healthcare to contract workers. As for buy now, pay later provider Zip, Cover Genius built an AI-powered tool that classifies insurable items (e.g. a power drill) to recommend warranties to e-commerce customers. Among the products Cover Genius offers is Shake Shield, earthquake insurance backed by Swiss Re. Image Credits: Cover Genius “We strongly believed in the embedded insurance model, which is the ability to protect customers at the point of sale or sign-up, and that there would be a major value shift away from direct-to-consumer and traditional insurers toward digital platforms partnering with insurtechs,” McDonald continued. “Customers gain access to tailored protection at the right time, removing the inconvenient need to take a second step to purchase protection. Partners achieve bottom-line growth and stickier customers and insurers benefit from a data-rich distribution channel.” There’s no doubt that embedded insurance is the hot new thing in insurtech. Startups in the space, many founded within the past five years, raised close to $800 million in VC funding in 2021. And a recent report from Simon Torrance, an embedded finance and app strategies advisor, estimates that embedded insurance in property and casualty alone could account for over $700 billion in gross written premiums by 2030, or 25% of the total market worldwide. New York-based Cover Genius has competition in insurance vendors like Extend and Bolttech. But it also has a robust client base, covering 10.5 million customers across merchant partners such as Intuit, Kayak, Booking Holdings, Priceline, Turkish Airlines, SeatGeek, Amazon, eBay and Wayfair. While Cover Genius was initially impacted by the pandemic — the company primarily offered travel insurance in 2020, when the industry took a hit — McDonald notes that it’s been able to branch into a range of new market segments over the past two years. The branching out came through a combination of product launches and acquisitions. In July, Cover Genius made a strategic investment in India-based insurtech Ensuredit and bought Booking Protect, a ticket refund protection startup that brought SeatGeek onto the Cover Genius Platform. And in June, Cover Genius launched a “price-optimized” warranty offering for small- and medium-sized ecommerce businesses. One hurdle on the path to expansion that Cover Genius will have to overcome is the general sentiment around insurance — which isn’t positive. A 2019 survey by the Geneva Association, a global association of insurance companies, found that more than half of people (53%) have had a bad insurance experience. In a separate report from IBM, less than half of customers said that they trust the insurance industry. McDonald says that Cover Genius’ products speak for themselves. “By delivering peace of mind and a high-quality customer experience, boosted by product relevance and seamlessness from the time of sale to claims, our partners get to enter new territory with their customers,” he said. “In the past, they’ve either had experience working with traditional insurers, who negatively impact the customer experience and invariably cause churn and backlash against their own brand, or they’ve tried to engage with traditional insurers and have given up because all the ‘heavy lift’ otherwise sits with them.”

Arnica raises $7M to improve software supply chain security • ZebethMedia

By zebethcontrolPosted on October 31, 2022Posted in Arnica, Enterprise, First Rays Venture Partners, funding, Security, startup, StartupsNo Comments

Everybody wants to talk about software supply chain risks these days, whether that’s security teams, developers or government officials. It’s no surprise then, that VCs, despite the current economic climate, continue to fund startups in this space, too. One of the newest members in this club is Arnica, a startup that takes a somewhat broader view of supply chain security than most of its competitors and helps companies. The company today announced that it has raised a $7 million seed round. The round was led by Joule Ventures and First Rays Venture Partners. A number of angel investors, including Avi Shua (co-founder & CEO of Orca Security), Dror Davidoff (co-founder & CEO of Aqua Security) and Baruch Sadogursky (head of Developer Relations at JFrog), also participated in this round. Arnica founding team. Image Credits: Arnica “As a former buyer of application security products, I tested more than a dozen solutions for securing my previous company’s software supply chain but reached a dead end. Most products were expensive visibility dashboards driven by varying definitions of “best practices,” said Arnica CEO and co-founder Nir Valtman. “We decided to provide this visibility for free, for unlimited users, forever. We went further though and developed a comprehensive solution to not only identify risks based on historical and anomalous behavior but also to mitigate them. We do this by using automated workflows with single-click mitigations that empower developers to own security from within the tools they already use.” The team argues that supply chain attacks succeed because of inefficient developer access management or the inability to detect anomalous identity or code behavior. So that’s where Arnica comes in. Its behavior-based approach combines access management and a service that can detect anomalous developer behavior that could be the result of a breach. “Each of our machine learning algorithms have thousands of features that identify whether it was actually the developer who wrote the pushed code,” explained Valtman. “When an anomaly is detected, it kicks off an immediate workflow to validate it with the developer in a simple and secure way. It is not only good for the company, but also good for developers.” There’s also secret detection to avoid leaking those, a service that continuously monitors security and compliance and tools for identifying the open source libraries used across an organization, which can also compile a full software bill of materials (SBOM). The company plans to use the new funding to accelerate its go-to-market and R&D efforts, with a focus on expanding its automated workflows and mitigation capabilities. “In a market full of security solutions adding only incremental value, Arnica’s instant resolution-oriented approach is a game changer for enterprise dev teams,” said Brian Rosenzweig, partner at Joule Ventures. “Arnica goes beyond just flagging security problems — every issue that is identified can be immediately addressed with a provided one-click fix. This allows businesses to quickly protect their software supply chain from attacks, while behavior-based detection ensures it remains secure in the long term. Arnica’s pragmatic approach and advanced technology enable companies to avoid costly breaches without compromising on agility.”

Versa raises $120M for its software-defined networking and security stack • ZebethMedia

By zebethcontrolPosted on October 27, 2022Posted in BlackRock, cybersecurity, Enterprise, Security, startup, Startups, VersaNo Comments

Networking and cybersecurity firm Versa today announced that it raised $120 million in a mix of equity and debt led by BlackRock, with participation from Silicon Valley Bank. CEO Kelly Ahuja tells ZebethMedia that the proceeds, which bring Versa’s total capital raised to $316 million, will be put toward go-to-market efforts and scaling the company. He demurred when asked what percentage of the financing was equity versus debt. Versa’s large round suggests that, despite the market downturn, VCs haven’t lost faith in cybersecurity vendors yet. According to data from PitchBook, venture capital investments have reached about $13.66 billion so far this year, up from $11.47 billion compared to 2020 (albeit down from $26.52 billion in 2021). It helps these vendors have customers — or at least potential customers — in droves. A December 2021 survey by CSO found that 44% of security leaders at large companies expected their budgets to increase in the upcoming 12 months. And Gartner estimates spending on information security and risk management will total $172 billion in 2022, up from $155 billion in 2021 and $137 billion the year prior. “The pandemic drove enterprises to accelerate their transition to cloud and saw their workforce become fully distributed. This has led to a dramatic increase in cybersecurity issues — leading businesses to look for new ways to protect and connect their users, networks, and applications,” Ahuja told ZebethMedia in an email interview. “We find ourselves in an extremely good place to have the right solution that meets the market needs.” Apurva Mehta and Kumar Mehta, two brothers, co-founded Versa in 2012. They came from Juniper Networks, where Apurva Mehta was the CTO and chief architect of the mobility business unit and Kumar Mehta was the VP of engineering. Kelly Ahuja, a Cisco alum, was tapped as Versa’s CEO in 2016. Versa provides a vast range of subscription-based software services — too many to list here — but positions itself primarily as a secure access service edge (SASE) provider. As described by Gartner in 2019, SASE combines software-based wide area networking and security principles like zero trust into a single service model. Through partnerships with service providers, Versa connects users to apps in the cloud or data centers with security layered on top — like data loss prevention tools and gateway firewalls. Concretely, the company offers a hardware-agnostic software stack that provides a single interface — via the cloud, on-premises or both — to implement corporate security and networking policies. “Versa’s portfolio in SASE converges security and networking,” Ahuja said, noting that Versa has a “sizable” team working on machine learning and AI-based malware detection. “Versa has developed a differentiated platform that combines AI and machine learning-powered security services edge and software-defined WAN (SD-WAN) solutions that helps customers reduce cybersecurity risk.” When asked about current clientele, Ahuja said that 625-employee Versa’s solutions have been deployed by “tens of thousands” of enterprises globally. He declined to reveal revenue figures, instead pointing to San Jose-based Versa’s annual contract value, which he says grew 60% over the “past few years.” “Every industry and business are facing similar macro challenges — high inflation, risk of recession, and supply chain and geopolitical challenges,” Ahuja said. “[But] Versa provides a clear value proposition and ROI of reducing cybersecurity risk.” In a June 2021 piece covering Versa’s last funding round, CRN’s Gina Narcisi pointed out that the SD-WAN and SASE space has seen a great deal of consolidation in recent years. Cisco Systems acquired Viptela and VMware bought SD-WAN vendor VeloCloud, and more recently, HPE’s Aruba snapped up Silver Peak while Palo Alto Networks absorbed CloudGenix. Last year, Ahuja told Fierce Telecom’s Linda Hardesty that Versa wasn’t shopping itself. Plans haven’t changed, he says — Ahuja sees the latest financing as setting the firm on a path toward an initial public offering.

SGNL.ai secures $12M to expand its enterprise authorization platform • ZebethMedia

By zebethcontrolPosted on October 27, 2022Posted in authorization, Costanoa Ventures, Enterprise, identity and access management, Security, startup, StartupsNo Comments

SGNL.ai, a company developing enterprise authorization software, today announced that it raised $12 million in seed funding led by Costanoa Ventures with participation from Fika Ventures, Moonshots Capital and Resolute Ventures. CEO Scott Kriz said the proceeds will be used to develop the company’s core products and hire the initial team, as well as work with design partners to refine SGNL’s solution. In an interview with ZebethMedia, Kriz asserted that authorization is increasingly becoming a concern for management at every level. He’s not wrong. According to Gartner, organizations running cloud infrastructure services will suffer a minimum of 2,300 violations of least privilege policies — i.e. when a user is given privileges above what they need to do their job — per account each year by 2024. Meanwhile, the average global cost of a data breach reached a record $4.24 million in 2021, IBM recently reported, increasing by 10% from 2019 as more people transitioned to remote work. Kriz and SGNL’s second co-founder, Erik Gustavson, spent roughly a decade developing identity solutions at Bitium, which they co-launched in 2011, before conceiving of SGNL. After Google acquired Bitium in 2017, Gustavson joined the tech giant as an engineering manager working on “next-generation” identity access management for G Suite (now Google Workspace). Kriz also spent several years at Google on the product, identity and authorization team. “From our vantage point working in multiple, identity-focused areas at Google, it was clear to Gustavson and I that few companies had been able to effectively solve enterprise authorization at scale,” Kriz said. “Seeing a critical need to help companies keep user and customer data safe, we founded SGNL in 2021 to address the challenge. We quickly attracted a core team of identity industry experts who are passionate about pushing the boundaries of what is possible in enterprise authorization.” SGNL aims to provide “just-in-time” access to enterprise data to a company’s employees based on business context, such as business needs or justifications. Rather than relying on relatively static roles or attributes, the startup’s platform only grants access to software resources and data when a user needs them. A glance at SGNL.ai’s dashboard, which lets admins review authorizations across teams, divisions and individual employees. Image Credits: SGNL Beyond this, SGNL attempts to unify existing systems-of-record such as corporate directories, HR directories, customer relationship management platforms and ticketing systems, building a graph of workforce and customer data that can be used to determine dynamic access rights. Access can be audited in real time, ostensibly making it easier for managers to produce compliance reports and analyze historical authorizations. “The pandemic and broader shift in working patterns — hybrid, remote work, extended workforces, etc. — makes the problem of authorization and access management more urgent for the enterprise. The modern workforce is no longer operating from inside a corporate firewall using only on-premise applications,” Kriz added. “This creates ideal conditions for bad actors to exploit overly broad ambient access rights to attack the enterprise … SGNL’s platform helps contain the blast radius by reducing ambient access and determining access to sensitive data on a just-in-time basis.” Kriz declined to reveal the size of SGNL’s customer base or the company’s current revenue. But he noted identity management has attracted much investment over the past few years as new hurdles emerge across the enterprise security landscape. According to Crunchbase, $3.2 billion in venture dollars went into the identity management space in 2021, about 2.5 times the amount of investment from 2020’s $1.3 billion, which was already a record. SGNL’s challenge will be attracting customers away from rival vendors like Opal, whose software automatically discovers databases, servers, internal tools and apps to delegate access requests to employees. ConductorOne, another identity and access management automation platform, recently nabbed a $15 million investment. Identity and access management software provider ForgeRock filed for an IPO last September after raising over $700 million in VC cash. Kriz says he’s confident, though, that the current slowdown in tech will be a tailwind for SGNL as companies face pressure to purchase solutions instead of building them in-house. To his point, there’s some evidence to suggest IT teams are overwhelmed with tasks related to managing identity and access. For example, in a 2020 poll conducted by 1Password, responding IT personnel said that they burn a full month of work — 21 days — resetting passwords and tracking app usage. “The number and cost of data breaches is only increasing … SGNL is positioned well with the shift in most enterprise organizations to increase security, ensure compliance and reduce expenses,” Kriz said. Palo Alto-based SGNL, which currently has 28 employees, expects to hire seven more people by the end of the year.