We tend to think of venture capital in tens or hundreds of millions, even billions of dollars, so it’s refreshing to find Evening Fund, a new $ 2 million micro fund that focuses on small investments between $ 50,000 and $ 100,000 as it seeks to help young startups with early funding.
The new fund was launched by Kat Orekhova and Rapha Danilo. Orekhova, who started her career as a math professor, is a former Facebook data scientist who has been dabbling in angel investing and working with young startups for awhile now. They call it Evening Fund because they work as founders by day and investors by night.
She says that she wanted to create something more formal to help early-stage startups get off the ground and has help from limited partners that include Sarah Smith at Bain Capital, Lee Linden, general partner at Quiet Capital and a long list of tech industry luminaries.
Orekhova says she and her partner invest small sums of money in B2B SaaS companies, which are pre-seed, seed and occasionally A rounds. They will invest in consumer here and there as well. She says one of their key value propositions is that they can help with more than just the money. “One way in which I think Rapha and I can really help our founders is that we give very specific, practical advice, not just kind of super high level,” she told me.
That could be something like how to hire your first designer where the founders may not even know what a designer does. “You’re figuring out ‘how do I hire my first designer?’ and ‘what does the designer even do?’ because most founders have never hired a designer before. So we give them extremely practical hands-on stuff like ‘here are the competencies’ or ‘what’s the difference between a graphic designer, a visual designer, a UX designer and a researcher,’ ” she said. They go so far as to give them a list of candidates to help them get going.
She says that she realized while she was at Facebook that she wanted to eventually start a company, so she began volunteering her time to work with companies going through Y Combinator. “I think a lot of people don’t know where to start, but in my case I looked at the YC list, found a company that I thought I could be helpful to. I reached out cold and said ‘Hey, I don’t want money. I don’t want equity. I just want to try to be helpful to you and see where that goes,’ ” she said.
That lead to scouting for startups for some larger venture capital firms and eventually dabbling in financing some of these startups that she was helping. Today’s announcement is the culmination of these years of work and the groundwork she laid to make herself familiar with how the startup ecosystem works.
The new firm already has its first investment under its belt, Dala, an AI-powered internal search tool that helps connect users to workplace knowledge that’s often locked in applications like Google Suite, Slack and Notion.
As though Evening isn’t enough to keep her and Danilo busy, they are also each working on their own startups. Orekhova wasn’t ready to share much on that just yet as her company remains in stealth.
With an increasing number of enterprise systems, growing teams, a rising proliferation of the web and multiple digital initiatives, companies of all sizes are creating loads of data every day. This data contains excellent business insights and immense opportunities, but it has become impossible for companies to derive actionable insights from this data consistently due to its sheer volume.
According to Verified Market Research, the analytics-as-a-service (AaaS) market is expected to grow to $ 101.29 billion by 2026. Organizations that have not started on their analytics journey or are spending scarce data engineer resources to resolve issues with analytics implementations are not identifying actionable data insights. Through AaaS, managed services providers (MSPs) can help organizations get started on their analytics journey immediately without extravagant capital investment.
MSPs can take ownership of the company’s immediate data analytics needs, resolve ongoing challenges and integrate new data sources to manage dashboard visualizations, reporting and predictive modeling — enabling companies to make data-driven decisions every day.
AaaS could come bundled with multiple business-intelligence-related services. Primarily, the service includes (1) services for data warehouses; (2) services for visualizations and reports; and (3) services for predictive analytics, artificial intelligence (AI) and machine learning (ML). When a company partners with an MSP for analytics as a service, organizations are able to tap into business intelligence easily, instantly and at a lower cost of ownership than doing it in-house. This empowers the enterprise to focus on delivering better customer experiences, be unencumbered with decision-making and build data-driven strategies.
Organizations that have not started on their analytics journey or are spending scarce data engineer resources to resolve issues with analytics implementations are not identifying actionable data insights.
In today’s world, where customers value experiences over transactions, AaaS helps businesses dig deeper into their psyche and tap insights to build long-term winning strategies. It also enables enterprises to forecast and predict business trends by looking at their data and allows employees at every level to make informed decisions.
Vena, a Canadian company focused on the Corporate Performance Management (CPM) software space, has raised $ 242 million in Series C funding from Vista Equity Partners.
As part of the financing, Vista Equity is taking a minority stake in the company. The round follows $ 25 million in financing from CIBC Innovation Banking last September, and brings Vena’s total raised since its 2011 inception to over $ 363 million.
Vena declined to provide any financial metrics or the valuation at which the new capital was raised, saying only that its “consistent growth and…strong customer retention and satisfaction metrics created real demand” as it considered raising its C round.
The company was originally founded as a B2B provider of planning, budgeting and forecasting software. Over time, it’s evolved into what it describes as a “fully cloud-native, corporate performance management platform” that aims to empower finance, operations and business leaders to “Plan to Grow” their businesses. Its customers hail from a variety of industries, including banking, SaaS, manufacturing, healthcare, insurance and higher education. Among its over 900 customers are the Kansas City Chiefs, Coca-Cola Consolidated, World Vision International and ELF Cosmetics.
Vena CEO Hunter Madeley told TechCrunch the latest raise is “mostly an acceleration story for Vena, rather than charting new paths.”
The company plans to use its new funds to build out and enable its go-to-market efforts as well as invest in its product development roadmap. It’s not really looking to enter new markets, considering it’s seeing what it describes as “tremendous demand” in the markets it currently serves directly and through its partner network.
“While we support customers across the globe, we’ll stay focused on growing our North American, U.K. and European business in the near term,” Madeley said.
Vena says it leverages the “flexibility and familiarity” of an Excel interface within its “secure” Complete Planning platform. That platform, it adds, brings people, processes and systems into a single source solution to help organizations automate and streamline finance-led processes, accelerate complex business processes and “connect the dots between departments and plan with the power of unified data.”
Early backers JMI Equity and Centana Growth Partners will remain active, partnering with Vista “to help support Vena’s continued momentum,” the company said. As part of the raise, Vista Equity Managing Director Kim Eaton and Marc Teillon, senior managing director and co-head of Vista’s Foundation Fund, will join the company’s board.
“The pandemic has emphasized the need for agile financial planning processes as companies respond to quickly-changing market conditions, and Vena is uniquely positioned to help businesses address the challenges required to scale their processes through this pandemic and beyond,” said Eaton in a written statement.
Vena currently has more than 450 employees across the U.S., Canada and the U.K., up from 393 last year at this time.
Google today announced a sizable update to its Anthos multicloud platform that lets you build, deploy and manage containerized applications anywhere, including on Amazon’s AWS and (in preview) on Microsoft Azure.
Version 1.7 includes new features like improved metrics and logging for Anthos on AWS, a new Connect gateway to interact with any cluster right from Google Cloud and a preview of Google’s managed control plane for Anthos Service Mesh. Other new features include Windows container support for environments that use VMware’s vSphere platform and new tools for developers to make it easier for them to deploy their applications to any Anthos cluster.
Today’s update comes almost exactly two years after Google CEO Sundar Pichai originally announced Anthos at its Cloud Next event in 2019 (before that, Google called this project the “Google Cloud Services Platform,” which launched three years ago). Hybrid and multicloud, it’s fair to say, takes a key role in the Google Cloud roadmap — and maybe more so for Google than for any of its competitors. Recently, Google brought on industry veteran Jeff Reed to become the VP of Product Management in charge of Anthos.
Reed told me that he believes that there are a lot of factors right now that are putting Anthos in a good position. “The wind is at our back. We bet on Kubernetes, bet on containers — those were good decisions,” he said. Increasingly, customers are also now scaling out their use of Kubernetes and have to figure out how to best scale out their clusters and deploy them in different environments — and to do so, they need a consistent platform across these environments. He also noted that when it comes to bringing on new Anthos customers, it’s really those factors that determine whether a company will look into Anthos or not.
He acknowledged that there are other players in this market, but he argues that Google Cloud’s take on this is also quite different. “I think we’re pretty unique in the sense that we’re from the cloud, cloud-native is our core approach,” he said. “A lot of what we talk about in [Anthos] 1.7 is about how we leverage the power of the cloud and use what we call “an anchor in the cloud” to make your life much easier. We’re more like a cloud vendor there, but because we support on-prem, we see some of those other folks.” Those other folks being IBM/Red Hat’s OpenShift and VMware’s Tanzu, for example.
The addition of support for Windows containers in vSphere environments also points to the fact that a lot of Anthos customers are classical enterprises that are trying to modernize their infrastructure, yet still rely on a lot of legacy applications that they are now trying to bring to the cloud.
Looking ahead, one thing we’ll likely see is more integrations with a wider range of Google Cloud products into Anthos. And indeed, as Reed noted, inside of Google Cloud, more teams are now building their products on top of Anthos themselves. In turn, that then makes it easier to bring those services to an Anthos-managed environment anywhere. One of the first of these internal services that run on top of Anthos is Apigee. “Your Apigee deployment essentially has Anthos underneath the covers. So Apigee gets all the benefits of a container environment, scalability and all those pieces — and we’ve made it really simple for that whole environment to run kind of as a stack,” he said.
I guess we can expect to hear more about this in the near future — or at Google Cloud Next 2021.
Software-as-a-Service (SaaS) is now the default business model for most B2B and B2C software startups. And while it’s been around for a while now, its momentum keeps accelerating and the ecosystem continues to expand as technologists and marketers are getting more sophisticated about how to build and sell SaaS products. For all of them, we’re pleased to announced TechCrunch Sessions: SaaS 2021, a one-day virtual event that will examine the state of SaaS to help startup founders, developers and investors understand the state of play and what’s next.
The single-day event will take place 100% virtually on October 27 and will feature actionable advice, Q&A with some of SaaS’s biggest names, and plenty of networking opportunities. $ 75 Early Bird Passes are now on sale. Book your passes today to save $ 100 before prices go up.
We’re not quite ready to disclose our agenda yet, but you can expect a mix of superstars from across the industry, ranging from some of the largest tech companies to up-and-coming startups that are pushing the limits of SaaS.
The plan is to look at a broad spectrum of what’s happening in with B2B startups and give you actionable insights into how to build and/or improve your own product. If you’re just getting started, we want you to come away with new ideas for how to start your company and if you’re already on your way, then our sessions on scaling both your technology and marketing organization will help you to get to that $ 100 million annual run rate faster.
In addition to other founders, you’ll also hear from enterprise leaders who decide what to buy — and the mistakes they see startups make when they try to sell to them.
But SaaS isn’t only about managing growth — though ideally, that’s a problem founders will face sooner or later. Some of the other specific topics we will look at are how to keep your services safe in an ever-growing threat environment, how to use open source to your advantage and how to smartly raise funding for your company.
We will also highlight how B2B and B2C companies can handle the glut of data they now produce and use it to build machine learning models in the process. We’ll talk about how SaaS startups can both do so themselves and help others in the process. There’s nary a startup that doesn’t want to use some form of AI these days, after all.
And because this is 2021, chances are we’ll also talk about building remote companies and the lessons SaaS startups can learn from the last year of working through the pandemic.
Don’t miss out. Book your $ 75 Early Bird pass today and save $ 100.
By 2025, 463 exabytes of data will be created each day, according to some estimates. (For perspective, one exabyte of storage could hold 50,000 years of DVD-quality video.) It’s now easier than ever to translate physical and digital actions into data, and businesses of all types have raced to amass as much data as possible in order to gain a competitive edge.
However, in our collective infatuation with data (and obtaining more of it), what’s often overlooked is the role that storytelling plays in extracting real value from data.
The reality is that data by itself is insufficient to really influence human behavior. Whether the goal is to improve a business’ bottom line or convince people to stay home amid a pandemic, it’s the narrative that compels action, rather than the numbers alone. As more data is collected and analyzed, communication and storytelling will become even more integral in the data science discipline because of their role in separating the signal from the noise.
Data alone doesn’t spur innovation — rather, it’s data-driven storytelling that helps uncover hidden trends, powers personalization, and streamlines processes.
Yet this can be an area where data scientists struggle. In Anaconda’s 2020 State of Data Science survey of more than 2,300 data scientists, nearly a quarter of respondents said that their data science or machine learning (ML) teams lacked communication skills. This may be one reason why roughly 40% of respondents said they were able to effectively demonstrate business impact “only sometimes” or “almost never.”
The best data practitioners must be as skilled in storytelling as they are in coding and deploying models — and yes, this extends beyond creating visualizations to accompany reports. Here are some recommendations for how data scientists can situate their results within larger contextual narratives.
Make the abstract more tangible
Ever-growing datasets help machine learning models better understand the scope of a problem space, but more data does not necessarily help with human comprehension. Even for the most left-brain of thinkers, it’s not in our nature to understand large abstract numbers or things like marginal improvements in accuracy. This is why it’s important to include points of reference in your storytelling that make data tangible.
For example, throughout the pandemic, we’ve been bombarded with countless statistics around case counts, death rates, positivity rates, and more. While all of this data is important, tools like interactive maps and conversations around reproduction numbers are more effective than massive data dumps in terms of providing context, conveying risk, and, consequently, helping change behaviors as needed. In working with numbers, data practitioners have a responsibility to provide the necessary structure so that the data can be understood by the intended audience.
SambaNova raises $676M at a $5.1B valuation to double down on cloud-based AI software for enterprises
Artificial intelligence technology holds a huge amount of promise for enterprises — as a tool to process and understand their data more efficiently; as a way to leapfrog into new kinds of services and products; and as a critical stepping stone into whatever the future might hold for their businesses. But the problem for many enterprises is that they are not tech businesses at their cores and so bringing on and using AI will typically involve a lot of heavy lifting. Today, one of the startups building AI services is announcing a big round of funding to help bridge that gap.
SambaNova — a startup building AI hardware and integrated systems that run on it that only officially came out of three years in stealth last December — is announcing a huge round of funding today to take its business out into the world. The company has closed in on $ 676 million in financing, a Series D that co-founder and CEO Rodrigo Liang has confirmed values the company at $ 5.1 billion.
The round is being led by SoftBank, which is making the investment via Vision Fund 2. Temasek and the Government of Singapore Investment Corp. (GIC), both new investors, are also participating, along with previous backers BlackRock, Intel Capital, GV (formerly Google Ventures), Walden International and WRVI, among other unnamed investors. (Sidenote: BlackRock and Temasek separately kicked off an investment partnership yesterday, although it’s not clear if this falls into that remit.)
Co-founded by two Stanford professors, Kunle Olukotun and Chris Ré, and Liang, who had been an engineering executive at Oracle, SambaNova has been around since 2017 and has raised more than $ 1 billion to date — both to build out its AI-focused hardware, which it calls DataScale and to build out the system that runs on it. (The “Samba” in the name is a reference to Liang’s Brazilian heritage, he said, but also the Latino music and dance that speaks of constant movement and shifting, not unlike the journey AI data regularly needs to take that makes it too complicated and too intensive to run on more traditional systems.)
SambaNova on one level competes for enterprise business against companies like Nvidia, Cerebras Systems and Graphcore — another startup in the space which earlier this year also raised a significant round. However, SambaNova has also taken a slightly different approach to the AI challenge.
In December, the startup launched Dataflow-as-a-service as an on-demand, subscription-based way for enterprises to tap into SambaNova’s AI system, with the focus just on the applications that run on it, without needing to focus on maintaining those systems themselves. It’s the latter that SambaNova will be focusing on selling and delivering with this latest tranche of funding, Liang said.
SambaNova’s opportunity, Liang believes, lies in selling software-based AI systems to enterprises that are keen to adopt more AI into their business, but might lack the talent and other resources to do so if it requires running and maintaining large systems.
“The market right now has a lot of interest in AI. They are finding they have to transition to this way of competing, and it’s no longer acceptable not to be considering it,” said Liang in an interview.
The problem, he said, is that most AI companies “want to talk chips,” yet many would-be customers will lack the teams and appetite to essentially become technology companies to run those services. “Rather than you coming in and thinking about how to hire scientists and hire and then deploy an AI service, you can now subscribe, and bring in that technology overnight. We’re very proud that our technology is pushing the envelope on cases in the industry.”
To be clear, a company will still need data scientists, just not the same number, and specifically not the same number dedicating their time to maintaining systems, updating code and other more incremental work that comes managing an end-to-end process.
SambaNova has not disclosed many customers so far in the work that it has done — the two reference names it provided to me are both research labs, the Argonne National Laboratory and the Lawrence Livermore National Laboratory — but Liang noted some typical use cases.
One was in imaging, such as in the healthcare industry, where the company’s technology is being used to help train systems based on high-resolution imagery, along with other healthcare-related work. The coincidentally-named Corona supercomputer at the Livermore Lab (it was named after the 2014 lunar eclipse, not the dark cloud of a pandemic that we’re currently living through) is using SambaNova’s technology to help run calculations related to some Covid-19 therapeutic and antiviral compound research, Marshall Choy, the company’s VP of product, told me.
Another set of applications involves building systems around custom language models, for example in specific industries like finance, to process data quicker. And a third is in recommendation algorithms, something that appears in most digital services and frankly could always do to work a little better than it does today. I’m guessing that in the coming months it will release more information about where and who is using its technology.
Liang also would not comment on whether Google and Intel were specifically tapping SambaNova as a partner in their own AI services, but he didn’t rule out the prospect of partnering to go to market. Indeed, both have strong enterprise businesses that span well beyond technology companies, and so working with a third party that is helping to make even their own AI cores more accessible could be an interesting prospect, and SambaNova’s DataScale (and the Dataflow-as-a-service system) both work using input from frameworks like PyTorch and TensorFlow, so there is a level of integration already there.
“We’re quite comfortable in collaborating with others in this space,” Liang said. “We think the market will be large and will start segmenting. The opportunity for us is in being able to take hold of some of the hardest problems in a much simpler way on their behalf. That is a very valuable proposition.”
The promise of creating a more accessible AI for businesses is one that has eluded quite a few companies to date, so the prospect of finally cracking that nut is one that appeals to investors.
“SambaNova has created a leading systems architecture that is flexible, efficient and scalable. This provides a holistic software and hardware solution for customers and alleviates the additional complexity driven by single technology component solutions,” said Deep Nishar, Senior Managing Partner at SoftBank Investment Advisers, in a statement. “We are excited to partner with Rodrigo and the SambaNova team to support their mission of bringing advanced AI solutions to organizations globally.”
The office shut-down at the start of the COVID-19 pandemic last year spurred huge investment in digital transformation and a wave of tech companies helping with that, but there were some distinct losers in the shift, too — specifically those whose business models were predicated on serving the very offices that disappeared overnight. Today, one of the companies that had to make an immediate pivot to keep itself afloat is announcing a round of funding, after finding itself not just growing at a clip, but making a profit, as well.
SnackMagic, a build-your-own snack box service, has raised $ 15 million in a Series A round of funding led by Craft Ventures, with Luxor Capital also participating.
(Both investors have an interesting track record in the food-on-demand space: Most recently, Luxor co-led a $ 528 million round in Glovo in Spain, while Craft backs/has backed the likes of Cloud Kitchens, Postmates and many more.)
The funding comes on the back of a strong year for the company, which hit a $ 20 million revenue run rate in eight months and turned profitable in December 2020.
Founder and CEO Shaunak Amin said in an interview that the plan will be to use the funding both to continue growing SnackMagic’s existing business, as well as extend into other kinds of gifting categories. Currently, you can ship snacks anywhere in the world, but the customizable boxes — recipients are gifted an amount that they can spend, and they choose what they want in the box themselves from SnackMagic’s menu, or one that a business has created and branded as a subset of that — are only available in locations in North America, serviced by SnackMagic’s primary warehouse. Other locations are given options of pre-packed boxes of snacks right now, but the plan is to slowly extend its pick-and-mix model to more geographies, starting with the U.K.
Alongside this, the company plans to continue widening the categories of items that people can gift each other beyond chocolates, chips, hot sauces and other fun food items, into areas like alcohol, meal kits and nonfood items. There’s also scope for expanding to more use cases into areas like corporate gifting, marketing and consumer services, as well as analytics coming out of its sales.
Amin calls the data that SnackMagic is amassing about customer interest in different brands and products “the hidden gem” of the platform.
“It’s one of the most interesting things,” he said. Brands that want to add their items to the wider pool of products — which today numbers between 700 and 800 items — also get access to a dashboard where they monitor what’s selling, how much stock is left of their own items, and so on. “One thing that is very opaque [in the CPG world] is good data.”
For many of the bigger companies that lack their own direct sales channels, it’s a significantly richer data set than what they typically get from selling items in the average brick and mortar store, or from a bigger online retailer like Amazon. “All these bigger brands like Pepsi and Kellogg not only want to know this about their own products more but also about the brands they are trying to buy,” Amin said. Several of them, he added, have approached his company to partner and invest, so I guess we should watch this space.
SnackMagic’s success comes from a somewhat unintended, unlikely beginning, and it’s a testament to the power of compelling, yet extensible technology that can be scaled and repurposed if necessary. In its case, there is personalization technology, logistics management, product inventory and accounting, and lots of data analytics involved.
The company started out as Stadium, a lunch delivery service in New York City that was leveraging the fact that when co-workers ordered lunch or dinner together for the office — say around a team-building event or a late-night working session, or just for a regular work day — oftentimes they found that people all hankered for different things to eat.
In many cases, people typically make separate orders for the different items, but that also means if you are ordering to all eat together, things would not arrive at the same time; if it’s being expensed, it’s more complicated on that front too; and if you’re thinking about carbon footprints, it might also mean a lot less efficiency on that front too.
Stadium’s solution was a platform that provided access to multiple restaurants’ menus, and people could pick from all of them for a single order. The business had been operating for six years and was really starting to take off.
“We were quite well known in the city, and we had plans to expand, and we were on track for March 2020 being our best month ever,” Amin said. Then, COVID-19 hit. “There was no one left in the office,” he said. Revenue disappeared overnight, since the idea of delivering many items to one place instantly stopped being a need.
Amin said that they took a look at the platform they had built to pick many options (and many different costs, and the accounting that came with that) and thought about how to use that for a different end. It turned out that even with people working remotely, companies wanted to give props to their workers, either just to say hello and thanks, or around a specific team event, in the form of food and treats — all the more so since the supply of snacks you typically come across in so many office canteens and kitchens were no longer there for workers to tap.
It’s interesting, but perhaps also unsurprising, that one of the by-products of our new way of working has been the rise of more services that cater (no pun intended) to people working in more decentralised ways, and that companies exploring how to improve rewarding people in those environments are also seeing a bump.
Just yesterday, we wrote about a company called Alyce raising $ 30 million for its corporate gifting platform that is also based on personalization — using AI to help understand the interests of the recipient to make better choices of items that a person might want to receive.
Alyce is taking a somewhat different approach than SnackMagic: it’s not holding any products itself, and there is no warehouse but rather a platform that links buyers with those providing products. And Alyce’s initial audience is different, too: instead of internal employees (the first, but not final, focus for SnackMagic) it is targeting corporate gifting, or presents that sales and marketing people might send to prospects or current clients as a please and thank you gesture.
But you can also see how and where the two might meet in the middle — and compete not just with each other, but the many other online retailers, Amazon and otherwise, plus the consumer goods companies themselves looking for ways of diversifying business by extending beyond the B2C channel.
“We don’t worry about Amazon. We just get better,” Amin said when I asked him about whether he worried that SnackMagic was too easy to replicate. “It might be tough anyway,” he added, since “others might have the snacks but picking and packing and doing individual customization is very different from regular e-commerce. It’s really more like scalable gifting.”
Investors are impressed with the quick turnaround and identification of a market opportunity, and how it quickly retooled its tech to make it fit for purpose.
“SnackMagic’s immediate success was due to an excellent combination of timing, innovative thinking and world-class execution,” said Bryan Rosenblatt, principal investor at Craft Ventures, in a statement. “As companies embrace the future of a flexible workplace, SnackMagic is not just a snack box delivery platform but a company culture builder.”
The Kubernetes project was a major undertaking for the company, Esri Product Managers Trevor Seaton and Philip Heede told me. Traditionally, like so many similar products, ArcGIS was architected to be installed on physical boxes, virtual machines or cloud-hosted VMs. And while it doesn’t really matter to end-users where the software runs, containerizing the application means that it is far easier for businesses to scale their systems up or down as needed.
“We have a lot of customers — especially some of the larger customers — that run very complex questions,” Seaton explained. “And sometimes it’s unpredictable. They might be responding to seasonal events or business events or economic events, and they need to understand not only what’s going on in the world, but also respond to their many users from outside the organization coming in and asking questions of the systems that they put in place using ArcGIS. And that unpredictable demand is one of the key benefits of Kubernetes.”
The team could have chosen to go the easy route and put a wrapper around its existing tools to containerize them and call it a day, but as Seaton noted, Esri used this opportunity to re-architect its tools and break it down into microservices.
“It’s taken us a while because we took three or four big applications that together make up [ArcGIS] Enterprise,” he said. “And we broke those apart into a much larger set of microservices. That allows us to containerize specific services and add a lot of high availability and resilience to the system without adding a lot of complexity for the administrators — in fact, we’re reducing the complexity as we do that and all of that gets installed in one single deployment script.”
While Kubernetes simplifies a lot of the management experience, a lot of companies that use ArcGIS aren’t yet familiar with it. And as Seaton and Heede noted, the company isn’t forcing anyone onto this platform. It will continue to support Windows and Linux just like before. Heede also stressed that it’s still unusual — especially in this industry — to see a complex, fully integrated system like ArcGIS being delivered in the form of microservices and multiple containers that its customers then run on their own infrastructure.
A bit later this month, Esri also plans to launch its new design system to make it easier and faster for developers to create clean and consistent user interfaces. This design system will launch April 22, but the company already provided a bit of a teaser today. As Powell noted, the challenge for Esri is that its design system has to help the company’s partners to put their own style and branding on top of the maps and data they get from the ArcGIS ecosystem.
When UIPath filed its S-1 last week, it was a watershed moment for the robotic process automation (RPA) market. The company, which first appeared on our radar for a $ 30 million Series A in 2017, has so far raised an astonishing $ 2 billion while still private. In February, it was valued at $ 35 billion when it raised $ 750 million in its latest round.
RPA and process automation came to the fore during the pandemic as companies took steps to digitally transform. When employees couldn’t be in the same office together, it became crucial to cobble together more automated workflows that required fewer people in the loop.
RPA has enabled executives to provide a level of workflow automation that essentially buys them time to update systems to more modern approaches while reducing the large number of mundane manual tasks that are part of every industry’s workflow.
When UIPath raised money in 2017, RPA was not well known in enterprise software circles even though it had already been around for several years. The category was gaining in popularity by that point because it addressed automation in a legacy context. That meant companies with deep legacy technology — practically everyone not born in the cloud — could automate across older platforms without ripping and replacing, an expensive and risky undertaking that most CEOs would rather not take.
RPA has enabled executives to provide a level of workflow automation, a taste of the modern. It essentially buys them time to update systems to more modern approaches while reducing the large number of mundane manual tasks that are part of just about every industry’s workflow.
While some people point to RPA as job-elimination software, it also provides a way to liberate people from some of the most mind-numbing and mundane chores in the organization. The argument goes that this frees up employees for higher level tasks.
As an example, RPA could take advantage of older workflow technologies like OCR (optical character recognition) to read a number from a form, enter the data in a spreadsheet, generate an invoice, send it for printing and mailing, and generate a Slack message to the accounting department that the task has been completed.
We’re going to take a deep dive into RPA and the larger process automation space — explore the market size and dynamics, look at the key players and the biggest investors, and finally, try to chart out where this market might go in the future.
Meet the vendors
UIPath is clearly an RPA star with a significant market share lead of 27.1%, according to IDC. Automation Anywhere is in second place with 19.4%, and Blue Prism is third with 10.3%, based on data from IDC’s July 2020 report, the last time the firm reported on the market.
Two other players with significant market share worth mentioning are WorkFusion with 6.8%, and NTT with 5%.