May
26
2020
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Scandit raises $80M as COVID-19 drives demand for contactless deliveries

Enterprise barcode scanner company Scandit has closed an $80 million Series C round, led by Silicon Valley VC firm G2VP. Atomico, GV, Kreos, NGP Capital, Salesforce Ventures and Swisscom Ventures also participated in the round — which brings its total raised to date to $123M.

The Zurich-based firm offers a platform that combines computer vision and machine learning tech with barcode scanning, text recognition (OCR), object recognition and augmented reality which is designed for any camera-equipped smart device — from smartphones to drones, wearables (e.g. AR glasses for warehouse workers) and even robots.

Use-cases include mobile apps or websites for mobile shopping; self checkout; inventory management; proof of delivery; asset tracking and maintenance — including in healthcare where its tech can be used to power the scanning of patient IDs, samples, medication and supplies.

It bills its software as “unmatched” in terms of speed and accuracy, as well as the ability to scan in bad light; at any angle; and with damaged labels. Target industries include retail, healthcare, industrial/manufacturing, travel, transport & logistics and more.

The latest funding injection follows a $30M Series B round back in 2018. Since then Scandit says it’s tripled recurring revenues, more than doubling the number of blue-chip enterprise customers, and doubling the size of its global team.

Global customers for its tech include the likes of 7-Eleven, Alaska Airlines, Carrefour, DPD, FedEx, Instacart, Johns Hopkins Hospital, La Poste, Levi Strauss & Co, Mount Sinai Hospital and Toyota — with the company touting “tens of billions of scans” per year on 100+ million active devices at this stage of its business.

It says the new funding will go on further pressing on the gas to grow in new markets, including APAC and Latin America, as well as building out its footprint and ops in North America and Europe. Also on the slate: Funding more R&D to devise new ways for enterprises to transform their core business processes using computer vision and AR.

The need for social distancing during the coronavirus pandemic has also accelerated demand for mobile computer vision on personal smart devices, according to Scandit, which says customers are looking for ways to enable more contactless interactions.

Another demand spike it’s seeing is coming from the pandemic-related boom in ‘Click & Collect’ retail and “millions” of extra home deliveries — something its tech is well positioned to cater to because its scanning apps support BYOD (bring your own device), rather than requiring proprietary hardware.

“COVID-19 has shone a spotlight on the need for rapid digital transformation in these uncertain times, and the need to blend the physical and digital plays a crucial role,” said CEO Samuel Mueller in a statement. “Our new funding makes it possible for us to help even more enterprises to quickly adapt to the new demand for ‘contactless business’, and be better positioned to succeed, whatever the new normal is.”

Also commenting on the funding in a supporting statement, Ben Kortlang, general partner at G2VP, added: “Scandit’s platform puts an enterprise-grade scanning solution in the pocket of every employee and customer without requiring legacy hardware. This bridge between the physical and digital worlds will be increasingly critical as the world accelerates its shift to online purchasing and delivery, distributed supply chains and cashierless retail.”

Jan
29
2020
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Greylock’s Reid Hoffman and Sarah Guo to talk fundraising at Early Stage SF 2020

Early Stage SF is around the corner, on April 28 in San Francisco, and we are more than excited for this brand new event. The intimate gathering of founders, VCs, operators and tech industry experts is all about giving founders the tools they need to find success, no matter the challenge ahead of them.

Struggling to understand the legal aspects of running a company, like negotiating cap tables or hiring international talent? We’ve got breakout sessions for that. Wondering how to go about fundraising, from getting your first yes to identifying the right investors to planning the timeline for your fundraise sprint? We’ve got breakout sessions for that. Growth marketing? PR/Media? Building a tech stack? Recruiting?

We. Got. You.

Hoffman + Guo

Today, we’re very proud to announce one of our few Main Stage sessions that will be open to all attendees. Reid Hoffman and Sarah Guo will join us for a conversation around “How To Raise Your Series A.”

Reid Hoffman is a legendary entrepreneur and investor in Silicon Valley. He was an Executive VP and founding board member at PayPal before going on to co-found LinkedIn in 2003. He led the company to profitability as CEO before joining Greylock in 2009. He serves on the boards of Airbnb, Apollo Fusion, Aurora, Coda, Convoy, Entrepreneur First, Microsoft, Nauto and Xapo, among others. He’s also an accomplished author, with books like “Blitzscaling,” “The Startup of You” and “The Alliance.”

Sarah Guo has a wealth of experience in the tech world. She started her career in high school at a tech firm founded by her parents, called Casa Systems. She then joined Goldman Sachs, where she invested in growth-stage tech startups such as Zynga and Dropbox, and advised both pre-IPO companies (Workday) and publicly traded firms (Zynga, Netflix and Nvidia). She joined Greylock Partners in 2013 and led the firm’s investment in Cleo, Demisto, Sqreen and Utmost. She has a particular focus on B2B applications, as well as infrastructure, cybersecurity, collaboration tools, AI and healthcare.

The format for Hoffman and Guo’s Main Stage chat will be familiar to folks who have followed the investors. It will be an updated, in-person combination of Hoffman’s famously annotated LinkedIn Series B pitch deck that led to Greylock’s investment, and Sarah Guo’s in-depth breakdown of what she looks for in a pitch.

They’ll lay out a number of universally applicable lessons that folks seeking Series A funding can learn from, tackling each from their own unique perspectives. Hoffman has years of experience in consumer-focused companies, with a special expertise in network effects. Guo is one of the top minds when it comes to investment in enterprise software.

We’re absolutely thrilled about this conversation, and to be honest, the entire Early Stage agenda.

How it works

Here’s how it all works:

There will be about 50+ breakout sessions at the event, and attendees will have an opportunity to attend at least seven. The sessions will cover all the core topics confronting early-stage founders — up through Series A — as they build a company, from raising capital to building a team to growth. Each breakout session will be led by notables in the startup world.

Don’t worry about missing a breakout session, because transcripts from each will be available to show attendees. And most of the folks leading the breakout sessions have agreed to hang at the show for at least half the day and participate in CrunchMatch, TechCrunch’s app to connect founders and investors based on shared interests.

Here’s the fine print. Each of the 50+ breakout sessions is limited to around 100 attendees. We expect a lot more attendees, of course, so signups for each session are on a first-come, first-serve basis. Buy your ticket today and you can sign up for the breakouts that we’ve announced. Pass holders will also receive 24-hour advance notice before we announce the next batch. (And yes, you can “drop” a breakout session in favor of a new one, in the event there is a schedule conflict.)

Grab yourself a ticket and start registering for sessions right here. Interested sponsors can hit up the team here.


Jan
21
2020
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Google Cloud lands Lufthansa Group and Sabre as new customers

Google’s strategy for bringing new customers to its cloud is to focus on the enterprise and specific verticals like healthcare, energy, financial service and retail, among others. Its healthcare efforts recently experienced a bit of a setback, with Epic now telling its customers that it is not moving forward with its plans to support Google Cloud, but in return, Google now got to announce two new customers in the travel business: Lufthansa Group, the world’s largest airline group by revenue, and Sabre, a company that provides backend services to airlines, hotels and travel aggregators.

For Sabre, Google Cloud is now the preferred cloud provider. Like a lot of companies in the travel (and especially the airline) industry, Sabre runs plenty of legacy systems and is currently in the process of modernizing its infrastructure. To do so, it has now entered a 10-year strategic partnership with Google “to improve operational agility while developing new services and creating a new marketplace for its airline,  hospitality and travel agency customers.” The promise, here, too, is that these new technologies will allow the company to offer new travel tools for its customers.

When you hear about airline systems going down, it’s often Sabre’s fault, so just being able to avoid that would already bring a lot of value to its customers.

“At Google we build tools to help others, so a big part of our mission is helping other companies realize theirs. We’re so glad that Sabre has chosen to work with us to further their mission of building the future of travel,” said Google CEO Sundar Pichai . “Travelers seek convenience, choice and value. Our capabilities in AI and cloud computing will help Sabre deliver more of what consumers want.”

The same holds true for Google’s deal with Lufthansa Group, which includes German flag carrier Lufthansa itself, but also subsidiaries like Austrian, Swiss, Eurowings and Brussels Airlines, as well as a number of technical and logistics companies that provide services to various airlines.

“By combining Google Cloud’s technology with Lufthansa Group’s operational expertise, we are driving the digitization of our operation even further,” said Dr. Detlef Kayser, member of the executive board of the Lufthansa Group. “This will enable us to identify possible flight irregularities even earlier and implement countermeasures at an early stage.”

Lufthansa Group has selected Google as a strategic partner to “optimized its operations performance.” A team from Google will work directly with Lufthansa to bring this project to life. The idea here is to use Google Cloud to build tools that help the company run its operations as smoothly as possible and to provide recommendations when things go awry due to bad weather, airspace congestion or a strike (which seems to happen rather regularly at Lufthansa these days).

Delta recently launched a similar platform to help its employees.

Nov
14
2019
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Eigen nabs $37M to help banks and others parse huge documents using natural language and ‘small data’

One of the bigger trends in enterprise software has been the emergence of startups building tools to make the benefits of artificial intelligence technology more accessible to non-tech companies. Today, one that has built a platform to apply the power of machine learning and natural language processing to massive documents of unstructured data has closed a round of funding as it finds strong demand for its approach.

Eigen Technologies, a London-based startup whose machine learning engine helps banks and other businesses that need to extract information and insights from large and complex documents like contracts, is today announcing that it has raised $37 million in funding, a Series B that values the company at around $150 million – $180 million.

The round was led by Lakestar and Dawn Capital, with Temasek and Goldman Sachs Growth Equity (which co-led its Series A) also participating. Eigen has now raised $55 million in total.

Eigen today is working primarily in the financial sector — its offices are smack in the middle of The City, London’s financial center — but the plan is to use the funding to continue expanding the scope of the platform to cover other verticals such as insurance and healthcare, two other big areas that deal in large, wordy documentation that is often inconsistent in how its presented, full of essential fine print, and typically a strain on an organisation’s resources to be handled correctly — and is often a disaster if it is not.

The focus up to now on banks and other financial businesses has had a lot of traction. It says its customer base now includes 25% of the world’s G-SIB institutions (that is, the world’s biggest banks), along with others that work closely with them, like Allen & Overy and Deloitte. Since June 2018 (when it closed its Series A round), Eigen has seen recurring revenues grow sixfold with headcount — mostly data scientists and engineers — double. While Eigen doesn’t disclose specific financials, you can see the growth direction that contributed to the company’s valuation.

The basic idea behind Eigen is that it focuses what co-founder and CEO Lewis Liu describes as “small data.” The company has devised a way to “teach” an AI to read a specific kind of document — say, a loan contract — by looking at a couple of examples and training on these. The whole process is relatively easy to do for a non-technical person: you figure out what you want to look for and analyse, find the examples using basic search in two or three documents and create the template, which can then be used across hundreds or thousands of the same kind of documents (in this case, a loan contract).

Eigen’s work is notable for two reasons. First, typically machine learning and training and AI requires hundreds, thousands, tens of thousands of examples to “teach” a system before it can make decisions that you hope will mimic those of a human. Eigen requires a couple of examples (hence the “small data” approach).

Second, an industry like finance has many pieces of sensitive data (either because it’s personal data, or because it’s proprietary to a company and its business), and so there is an ongoing issue of working with AI companies that want to “anonymise” and ingest that data. Companies simply don’t want to do that. Eigen’s system essentially only works on what a company provides, and that stays with the company.

Eigen was founded in 2014 by Dr. Lewis Z. Liu (CEO) and Jonathan Feuer (a managing partner at CVC Capital Partners, who is the company’s chairman), but its earliest origins go back 15 years earlier, when Liu — a first-generation immigrant who grew up in the U.S. — was working as a “data-entry monkey” (his words) at a tire manufacturing plant in New Jersey, where he lived, ahead of starting university at Harvard.

A natural computing whiz who found himself building his own games when his parents refused to buy him a games console, he figured out that the many pages of printouts he was reading and re-entering into a different computing system could be sped up with a computer program linking up the two. “I put myself out of a job,” he joked.

His educational life epitomises the kind of lateral thinking that often produces the most interesting ideas. Liu went on to Harvard to study not computer science, but physics and art. Doing a double major required working on a thesis that merged the two disciplines together, and Liu built “electrodynamic equations that composed graphical structures on the fly” — basically generating art using algorithms — which he then turned into a “Turing test” to see if people could detect pixelated actual work with that of his program. Distill this, and Liu was still thinking about patterns in analog material that could be re-created using math.

Then came years at McKinsey in London (how he arrived on these shores) during the financial crisis where the results of people either intentionally or mistakenly overlooking crucial text-based data produced stark and catastrophic results. “I would say the problem that we eventually started to solve for at Eigen became tangible,” Liu said.

Then came a physics PhD at Oxford where Liu worked on X-ray lasers that could be used to decrease the complexity and cost of making microchips, cancer treatments and other applications.

While Eigen doesn’t actually use lasers, some of the mathematical equations that Liu came up with for these have also become a part of Eigen’s approach.

“The whole idea [for my PhD] was, ‘how do we make this cheaper and more scalable?,’ ” he said. “We built a new class of X-ray laser apparatus, and we realised the same equations could be used in pattern matching algorithms, specifically around sequential patterns. And out of that, and my existing corporate relationships, that’s how Eigen started.”

Five years on, Eigen has added a lot more into the platform beyond what came from Liu’s original ideas. There are more data scientists and engineers building the engine around the basic idea, and customising it to work with more sectors beyond finance. 

There are a number of AI companies building tools for non-technical business end-users, and one of the areas that comes close to what Eigen is doing is robotic process automation, or RPA. Liu notes that while this is an important area, it’s more about reading forms more readily and providing insights to those. The focus of Eigen is more on unstructured data, and the ability to parse it quickly and securely using just a few samples.

Liu points to companies like IBM (with Watson) as general competitors, while startups like Luminance is another taking a similar approach to Eigen by addressing the issue of parsing unstructured data in a specific sector (in its case, currently, the legal profession).

Stephen Nundy, a partner and the CTO of Lakestar, said that he first came into contact with Eigen when he was at Goldman Sachs, where he was a managing director overseeing technology, and the bank engaged it for work.

“To see what these guys can deliver, it’s to be applauded,” he said. “They’re not just picking out names and addresses. We’re talking deep, semantic understanding. Other vendors are trying to be everything to everybody, but Eigen has found market fit in financial services use cases, and it stands up against the competition. You can see when a winner is breaking away from the pack and it’s a great signal for the future.”

Aug
29
2018
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Storage provider Cloudian raises $94M

Cloudian, a company that specializes in helping businesses store petabytes of data, today announced that it has raised a $94 million Series E funding round. Investors in this round, which is one of the largest we have seen for a storage vendor, include Digital Alpha, Fidelity Eight Roads, Goldman Sachs, INCJ, JPIC (Japan Post Investment Corporation), NTT DOCOMO Ventures and WS Investments. This round includes a $25 million investment from Digital Alpha, which was first announced earlier this year.

With this, the seven-year-old company has now raised a total of $174 million.

As the company told me, it now has about 160 employees and 240 enterprise customers. Cloudian has found its sweet spot in managing the large video archives of entertainment companies, but its customers also include healthcare companies, automobile manufacturers and Formula One teams.

What’s important to stress here is that Cloudian’s focus is on on-premise storage, not cloud storage, though it does offer support for multi-cloud data management, as well. “Data tends to be most effectively used close to where it is created and close to where it’s being used,” Cloudian VP of worldwide sales Jon Ash told me. “That’s because of latency, because of network traffic. You can almost always get better performance, better control over your data if it is being stored close to where it’s being used.” He also noted that it’s often costly and complex to move that data elsewhere, especially when you’re talking about the large amounts of information that Cloudian’s customers need to manage.

Unsurprisingly, companies that have this much data now want to use it for machine learning, too, so Cloudian is starting to get into this space, as well. As Cloudian CEO and co-founder Michael Tso also told me, companies are now aware that the data they pull in, whether from IoT sensors, cameras or medical imaging devices, will only become more valuable over time as they try to train their models. If they decide to throw the data away, they run the risk of having nothing with which to train their models.

Cloudian plans to use the new funding to expand its global sales and marketing efforts and increase its engineering team. “We have to invest in engineering and our core technology, as well,” Tso noted. “We have to innovate in new areas like AI.”

As Ash also stressed, Cloudian’s business is really data management — not just storage. “Data is coming from everywhere and it’s going everywhere,” he said. “The old-school storage platforms that were siloed just don’t work anywhere.”

Sep
26
2017
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Lively raises $4.2M as it adds investment capabilities for health savings accounts

 Lively co-founder Shobin Uralil likes to describe the health savings account as the “401(k) for healthcare” — but that it’s woefully underused as an investment vehicle like a 401(k). So instead of just relying on it as a way to pay for healthcare, Uralil and his co-founder Alex Cyriac set out to build a way to not only help people start up health savings accounts, but… Read More

Jun
15
2017
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VR’s killer app: business services

 Enterprise adoption is trumping entertainment uses and will spring VR and AR into the mainstream. Read More

Mar
16
2017
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Smart diabetes management service Livongo Health raises $52.5M and looks to new markets

 Glen Tullman doesn’t like it when someone tells him he’s sick when he’s feeling fine. It’s something he thinks his customers probably don’t want to hear, either. Tullman runs a startup called Livongo Health, which offers a blood glucose monitor accompanied with a service designed to intervene and help coach people through managing diabetes. Livongo Health helps… Read More

Jan
18
2017
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Collibra nabs $50M at reported $650M valuation led by ICONIQ

big data words Data governance and management startup Collibra — originally founded in Belgium but now based out of New York to help businesses in sectors like finance and healthcare to manage and comply with data retention policies — has raised $50 million in its latest round of funding. The company is not disclosing the valuation, but we heard that it is in the region of $650 million (which is… Read More

Aug
10
2016
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CareSkore gets $4.3M to bring machine learning to preventive care

CareSkoreProductDevices Among other things, CareSkore wants to use machine learning to anticipate mortality. However, the newly endowed platform is more than just a Facebook poll that tells you how you’ll meet your end this Christmas by being squashed by a falling piano. Storm ventures, Cota Capital, Rising Tide Fund and Liquid 2 Ventures are rallying behind the Y Combinator graduate with today’s… Read More

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