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Build a digital ops toolbox to streamline business processes with hyperautomation

Reliance on a single technology as a lifeline is a futile battle now. When simple automation no longer does the trick, delivering end-to-end automation needs a combination of complementary technologies that can give a facelift to business processes: the digital operations toolbox.

According to a McKinsey survey, enterprises that have likely been successful with digital transformation efforts adopted sophisticated technologies such as artificial intelligence, Internet of Things or machine learning. Enterprises can achieve hyperautomation with the digital ops toolbox, the hub for your digital operations.

The hyperautomation market is burgeoning: Analysts predict that by 2025, it will reach around $860 billion.

The toolbox is a synchronous medley of intelligent business process management (iBPM), robotic process automation (RPA), process mining, low code, artificial intelligence (AI), machine learning (ML) and a rules engine. The technologies can be optimally combined to achieve the organization’s key performance indicator (KPI) through hyperautomation.

The hyperautomation market is burgeoning: Analysts predict that by 2025, it will reach around $860 billion. Let’s see why.

The purpose of a digital ops toolbox

The toolbox, the treasure chest of technologies it is, helps with three crucial aspects: process automation, orchestration and intelligence.

Process automation: A hyperautomation mindset introduces the world of “automating anything that can be,” whether that’s a process or a task. If something can be handled by bots or other technologies, it should be.

Orchestration: Hyperautomation, per se, adds an orchestration layer to simple automation. Technologies like intelligent business process management orchestrate the entire process.

Intelligence: Machines can automate repetitive tasks, but they lack the decision-making capabilities of humans. And, to achieve a perfect harmony where machines are made to “think and act,” or attain cognitive skills, we need AI. Combining AI, ML and natural language processing algorithms with analytics propels simple automation to become more cognitive. Instead of just following if-then rules, the technologies help gather insights from the data. The decision-making capabilities enable bots to make decisions.

 

Simple automation versus hyperautomation

Here’s a story of evolving from simple automation to hyperautomation with an example: an order-to-cash process.

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Opportunity knocks: Exhibit at TC Sessions: Mobility 2021

No matter what slice of the mobility market you’ve claimed as your own — AVs, EVs, data mining, AI, dockless scooters, robotics or the batteries that will charge and change the world — you won’t find a better place to showcase your extraordinary tech and talent than TC Sessions: Mobility 2021.

Buy a Startup Exhibitor Package and virtually plant your early-stage mobility startup in front of a global audience that’s focused exclusively on one of the most complex, rapidly evolving industries. TC Sessions: Mobility, which takes place on June 9, features the top minds and makers, draws thousands of attendees, fosters collaborative community and creates a networking environment ripe with opportunities.

Pro tip: This package is for pre-Series A, early-stage startups only.

The Startup Exhibitor Package costs $380, and it comes with four all-access passes to the event. But wait (insert infomercial voice here), there’s more!

Your virtual expo booth features lead-generation capabilities. You can highlight your pitch deck, run a video loop and/or host live demos. Network with CrunchMatch, our AI-powered platform, to find and connect with the people who can help move your business forward. CrunchMatch lets you host private video meetings — pitch investors, recruit new talent or grow your customer base.

You’ll have access to all the presentations, panel discussions and breakout sessions, too. And video-on-demand means you won’t miss out.

Here’s a peek at just some of the agenda’s great programming you and, thanks to those extra passes, your team can attend — or catch later with VOD:

  • EV Founders in Focus: We sit down with the founders poised to take advantage of the rise in electric vehicle sales. This time, we will chat with Kameale Terry, co-founder and CEO of ChargerHelp! a startup that enables on-demand repair of electric vehicle charging stations.
  • Will Venture Capital Drive the Future of Mobility? Clara Brenner, Quin Garcia and Rachel Holt will discuss how the pandemic changed their investment strategies, the hottest sectors within the mobility industry, the rise of SPACs as a financial instrument and where they plan to put their capital in 2021 and beyond.
  • Driving Innovation at General Motors: GM is in the midst of sweeping changes that will eventually turn it into an EV-only producer of cars, trucks and SUVs. But the auto giant’s push to electrify passenger vehicles is just one of many efforts to be a leader in innovation and the future of transportation. We’ll talk with Pam Fletcher, vice president of innovation at GM, one of the key people behind the 113-year-old automaker’s push to become a nimble, tech-centric company.

TC Sessions: Mobility 2021 takes place June 9. Buy a Startup Exhibitor Package and set yourself up for global exposure and networking success. Show us your extraordinary tech and talent!

Is your company interested in sponsoring or exhibiting at TC Sessions: Mobility 2021? Contact our sponsorship sales team by filling out this form.

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Analytics as a service: Why more enterprises should consider outsourcing

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.

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Technologists: Consider Canada

Tim Bray
Contributor

Tim Bray is a software technologist based in Vancouver, B.C. and a former vice president and Distinguished Engineer at Amazon Web Services.

Iain Klugman
Contributor

Iain Klugman is CEO of Communitech, an innovation hub in Waterloo, Ontario, and a signatory to the Tech for Good Declaration.

America’s technology industry, radiating brilliance and profitability from its Silicon Valley home base, was until recently a shining beacon of what made America great: Science, progress, entrepreneurship. But public opinion has swung against big tech amazingly fast and far; negative views doubled between 2015 and 2019 from 17% to 34%. The list of concerns is long and includes privacy, treatment of workers, marketplace fairness, the carnage among ad-supported publications and the poisoning of public discourse.

But there’s one big issue behind all of these: An industry ravenous for growth, profit and power, that has failed at treating its employees, its customers and the inhabitants of society at large as human beings. Bear in mind that products, companies and ecosystems are built by people, for people. They reflect the values of the society around them, and right now, America’s values are in a troubled state.

We both have a lot of respect and affection for the United States, birthplace of the microprocessor and the electric guitar. We could have pursued our tech careers there, but we’ve declined repeated invitations and chosen to stay at home here in Canada . If you want to build technology to be harnessed for equity, diversity and social advancement of the many, rather than freedom and inclusion for the few, we think Canada is a good place to do it.

U.S. big tech is correctly seen as having too much money, too much power and too little accountability. Those at the top clearly see the best effects of their innovations, but rarely the social costs. They make great things — but they also disrupt lives, invade privacy and abuse their platforms.

We both came of age at a time when tech aspired to something better, and so did some of today’s tech giants. Four big tech CEOs recently testified in front of Congress. They were grilled about alleged antitrust abuses, although many of us watching were thinking about other ills associated with some of these companies: tax avoidance, privacy breaches, data mining, surveillance, censorship, the spread of false news, toxic byproducts, disregard for employee welfare.

But the industry’s problem isn’t really the products themselves — or the people who build them. Tech workers tend to be dramatically more progressive than the companies they work for, as Facebook staff showed in their recent walkout over President Donald Trump’s posts.

Big tech’s problem is that it amplifies the issues Americans are struggling with more broadly. That includes economic polarization, which is echoed in big-tech financial statements, and the race politics that prevent tech (among other industries) from being more inclusive to minorities and talented immigrants.

We’re particularly struck by the Trump administration’s recent moves to deny opportunities to H-1B visa holders. Coming after several years of family separations, visa bans and anti-immigrant rhetoric, it seems almost calculated to send IT experts, engineers, programmers, researchers, doctors, entrepreneurs and future leaders from around the world — the kind of talented newcomers who built America’s current prosperity — fleeing to more receptive shores.

One of those shores is Canada’s; that’s where we live and work. Our country has long courted immigration, but it’s turned around its longstanding brain-drain problem in recent years with policies designed to scoop up talented people who feel uncomfortable or unwanted in America. We have an immigration program, the Global Talent Stream, that helps innovative companies fast-track foreign workers with specialized skills. Cities like Toronto, Montreal, Waterloo and Vancouver have been leading North America in tech job creation during the Trump years, fuelled by outposts of the big international tech companies but also by scaled-up domestic firms that do things the Canadian way, such as enterprise software developer OpenText (one of us is a co-founder) and e-commerce giant Shopify.

“Canada is awesome. Give it a try,” Shopify CEO Tobi Lütke told disaffected U.S. tech workers on Twitter recently.

But it’s not just about policy; it’s about underlying values. Canada is exceptionally comfortable with diversity, in theory (as expressed in immigration policy) and practice (just walk down a street in Vancouver or Toronto). We’re not perfect, but we have been competently led and reasonably successful in recognizing the issues we need to deal with. And our social contract is more cooperative and inclusive.

Yes, that means public health care with no copays, but it also means more emphasis on sustainability, corporate responsibility and a more collaborative strain of capitalism. Our federal and provincial governments have mostly been applauded for their gusher of stimulative wage subsidies and grants meant to sustain small businesses and tech talent during the pandemic, whereas Washington’s response now appears to have been formulated in part to funnel public money to elites.

American big tech today feels morally adrift, which leads to losing out on talented people who want to live the values Silicon Valley used to stand for — not just wealth, freedom and the few, but inclusivity, diversity and the many. Canada is just one alternative to the U.S. model, but it’s the alternative we know best and the one just across the border, with loads of technology job openings.

It wouldn’t surprise us if more tech refugees find themselves voting with their feet.

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Typewise taps $1M to build an offline next word prediction engine

Swiss keyboard startup Typewise has bagged a $1 million seed round to build out a typo-busting, ‘privacy-safe’ next word prediction engine designed to run entirely offline. No cloud connectivity, no data mining risk is the basic idea.

They also intend the tech to work on text inputs made on any device, be it a smartphone or desktop, a wearable, VR — or something weirder that Elon Musk might want to plug into your brain in future.

For now they’ve got a smartphone keyboard app that’s had around 250,000 downloads — with some 65,000 active users at this point.

The seed funding breaks down into $700K from more than a dozen local business angels; and $340K via the Swiss government through a mechanism (called “Innosuisse projects“), akin to a research grant, which is paying for the startup to employ machine learning experts at Zurich’s ETH research university to build out the core AI.

The team soft launched a smartphone keyboard app late last year, which includes some additional tweaks (such as an optional honeycomb layout they tout as more efficient; and the ability to edit next word predictions so the keyboard quickly groks your slang) to get users to start feeding in data to build out their AI.

Their main focus is on developing an offline next word prediction engine which could be licensed for use anywhere users are texting, not just on a mobile device.

“The goal is to develop a world-leading text prediction engine that runs completely on-device,” says co-founder David Eberle. “The smartphone keyboard really is a first use case. It’s great to test and develop our algorithms in a real-life setting with tens of thousands of users. The larger play is to bring word/sentence completion to any application that involves text entry, on mobiles or desktop (or in future also wearables/VR/Brain-Computer Interfaces).

“Currently it’s pretty much only Google working on this (see Gmail’s auto completion feature). Applications such as Microsoft Teams, Slack, Telegram, or even SAP, Oracle, Salesforce would want such productivity increase – and at that level privacy/data security matters a lot. Ultimately we envision that every “human-machine interface” is, at least on the text-input level, powered by Typewise.”

You’d be forgiven for thinking all this sounds a bit retro, given the earlier boom in smartphone AI keyboards — such as SwiftKey (now owned by Microsoft).

The founders have also pushed specific elements of their current keyboard app — such as the distinctive honeycomb layout — before, going down a crowdfunding route back in 2015, when they were calling the concept Wrio. But they reckon it’s now time to go all in — hence relaunching the business as Typewise and shooting to build a licensing business for offline next word prediction.

“We’ll use the funds to develop advanced text predictions… first launching it in the keyboard app and then bringing it to the desktop to start building partnerships with relevant software vendors,” says Eberle, noting they’re working on various enhancements to the keyboard app and also plan to spend on marketing to try to hit 1M active users next year.

“We have more ‘innovative stuff’ [incoming] on the UX side as well, e.g. interacting with auto correction (so the user can easily intervene when it does something wrong — in many countries users just turn it off on all keyboards because it gets annoying), gamifying the general typing experience (big opportunity for kids/teenagers, also making them more aware of what and how they type), etc.”

The competitive landscape around smartphone keyboard tech, largely dominated by tech giants, has left room for indie plays, is the thinking. Nor is Typewise the only startup thinking that way (Fleksy has similar ambitions, for one). However gaining traction vs such giants — and over long established typing methods — is the tricky bit.

Android maker Google has ploughed resource into its Gboard AI keyboard — larding it with features. While, on iOS, Apple’s interface for switching to a third party keyboard is infamously frustrating and finicky; the opposite of a seamless experience. Plus the native keyboard offers next word prediction baked in — and Apple has plenty of privacy credit. So why would a user bother switching is the problem there.

Competing for smartphone users’ fingers as an indie certainly isn’t easy. Alternative keyboard layouts and input mechanism are always a very tough sell as they disrupt people’s muscle memory and hit mobile users hard in their comfort and productivity zone. Unless the user is patient and/or stubborn enough to stick with a frustratingly different experience they’ll soon ditch for the keyboard devil they know.  (‘Qwerty’ is an ancient typewriter layout turned typing habit we English speakers just can’t kick.)

Given all that, Typewise’s retooled focus on offline next word prediction to do white label b2b licensing makes more sense — assuming they can pull off the core tech.

And, again, they’re competing at a data disadvantage on that front vs more established tech giant keyboard players, even as they argue that’s also a market opportunity.

“Google and Microsoft (thanks to the acquisition of SwiftKey) have a solid technology in place and have started to offer text predictions outside of the keyboard; many of their competitors, however, will want to embed a proprietary (difficult to build) or independent technology, especially if their value proposition is focused on privacy/confidentiality,” Eberle argues.

“Would Telegram want to use Google’s text predictions? Would SAP want that their clients’ data goes through Microsoft’s prediction algorithms? That’s where we see our right to win: world-class text predictions that run on-device (privacy) and are made in Switzerland (independent environment, no security back doors, etc).”

Early impressions of Typewise’s next word prediction smarts (gleaned by via checking out its iOS app) are pretty low key (ha!). But it’s v1 of the AI — and Eberle talks bullishly of having “world class” developers working on it.

“The collaboration with ETH just started a few weeks ago and thus there are no significant improvements yet visible in the live app,” he tells TechCrunch. “As the collaboration runs until the end of 2021 (with the opportunity of extension) the vast majority of innovation is still to come.”

He also tells us Typewise is working with ETH’s Prof. Thomas Hofmann (chair of the Data Analytic Lab, formerly at Google), as well as having has two PhDs in NLP/ML and one MSc in ML contributing to the effort.

“We get exclusive rights to the [ETH] technology; they don’t hold equity but they get paid by the Swiss government on our behalf,” Eberle also notes. 

Typewise says its smartphone app supports more than 35 languages. But its next word prediction AI can only handle English, German, French, Italian and Spanish at this point. The startup says more are being added.

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Recent departures hint at turmoil at Quartet Health, a mental health startup backed by GV

Backed with nearly $87 million in venture capital funding from GV, Oak HC/FT and F-Prime Capital, Quartet Health was founded in 2014 by Arun Gupta, Steve Shulman and David Wennberg to improve access to behavioral healthcare. Its mission: “enable every person in our society to thrive by building a collaborative behavioral and physical health ecosystem.”

Recent shakeups within the New York-based company’s c-suite and a perusal of its Glassdoor profile suggest Quartet’s culture is not fully in line with its own philosophy.  

In the last few weeks, chief product officer Rajesh Midha has left the company and president and chief operating officer David Liu is on his way out, TechCrunch has learned and confirmed with Quartet. Founding chief executive officer Arun Gupta, meanwhile, has stepped into the executive chairman role, relinquishing responsibility of the company’s day-to-day operations to former chief science officer David Wennberg, who’s taken over as CEO.

“I’m focusing on our external growth,” Gupta told TechCrunch on Friday. “David has really stepped up as CEO.”

Gupta and Wennberg said Liu’s role was no longer needed because Wennberg had assumed his responsibilities. Liu will formally exit the company at the end of the month. As for its product chief, the pair say Midha had “transitioned out” of the role and that an unnamed internal candidate was tapped to replace him.

When asked whether other employees had left in recent weeks,  Wennberg provided the following indeterminate statement: “We are always having people coming in. I don’t think we’ve had any unusual turnover. We’re hiring and people’s roles change and that’s just part of growth.”

Quartet, which provides a platform that allows providers to collaborate on treatment plans, currently has 150 employees, according to its executives.

In a LinkedIn status update published this week — after TechCrunch’s initial inquiries — Gupta announced his transition to executive chairman:

“Still full-time, though focused largely on our opportunity to further evangelize our mission, [I will] drive the change we want to see in this world, and expand our reach … I have tremendous confidence in David’s ability to lead our many talented Quartetians to deliver this next phase.”

Several former employees seemed less than pleased with Gupta’s performance, writing in a number of Glassdoor reviews that he was “abominable,” “kind of a monster” and “by far the worst executive.”

When asked for comment on those reviews, Gupta and Wennberg shrugged it off: “Glassdoor is Glassdoor.” They agreed its important to pay attention to but impossible to vet.

Gupta began his career as a management consultant at McKinsey and served as a consultant to The World Bank before joining Palantir, Peter Thiel’s data-mining company, as an advisor in 2014. Wennberg, for his part, was the CEO of The High Value Healthcare Collaborative, a consortium of 15 healthcare delivery systems, before co-founding Quartet.

In January, Quartet raised a $40 million Series C to expand throughout the U.S. F-Prime Capital and Polaris Partners led the round, with participation from GV and Oak HC/FT. The financing valued the company at $300 million, according to PitchBook.

As part of the funding, Quartet announced it was adding three new directors to its board: F-Prime’s executive partner Carl Byers; Ken Goulet, an executive vice president at health insurance provider Anthem; and former Rackspace CEO and BuildGroup co-founder Lanham Napier. Other outside board members include Oak HC/FT’s managing partner Annie Lamont, GV partner Krishna Yeshwant, Polaris managing partner Brian Chee and former U.S. Congressman Patrick Kennedy.

Quartet previously raised a $40 million Series B in April 2016 led by GV. The investment marked the venture capital investment arm of Google’s first in a mental health startup. Before that, the startup brought in a $7 million Series A led by Oak HC/FT’s managing partner Annie Lamont.

For now, Quartet remains committed to growth.

“We learn from what we are doing and we continue to learn,” Wennberg said. “That is part of growth. It’s hard and you just keep working and growing because we have a huge mission.”

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