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Automation is the name of the game in enterprise IT at the moment: we now have a plethora of solutions on the market to speed up your workflow, simplify a process, and perform more repetitive tasks without humans getting involved. Now, a startup that is helping non-technical people get more directly involved in how to make automation work better for their tasks is announcing some funding to seize the opportunity.

Bryter — a no-code platform based in Berlin that lets workers in departments like accounting, legal, compliance and marketing who do not have any special technical or developer skills build tools like chatbots, trigger automated database and document actions and risk assessors — is today announcing that it has raised $ 16 million. This is a Series A round and it’s being co-led by Accel and Dawn Capital, with Notion Capital and Chalfen Ventures also participating.

The funding comes less than a year after Bryter raised a seed round — $ 6 million in November 2019 — and it was oversubscribed, with term sheets coming in from many of the bigger VCs in Europe and the US. With this funding, the company has now raised around $ 25 million, and while the valuation is considerably up on the last round, Bryter is not disclosing what it is.

Michael Grupp, the CEO who co-founded the company with Micha-Manuel Bues and Michael Hübl (pictured below), said that the whole Series A process took no more than a month to initiate and close, an impressive turnaround considering the chilling effect that the COVID-19 health pandemic has had on dealmaking.

Part of the reason for the enthusiasm is because of the traction that Bryter has had since launching in 2018. Its 50 enterprise customers include the likes of McDonalds, Telefónica, banks, healthcare and industrial companies, and professional services firms PwC, KPMG and Deloitte (who in turn use it for themselves as well as for clients). (Note: because of its target users being large enterprises, the company doesn’t publish per-person pricing on its site as such.)

Bryter’s been seeing a lot of attention from customers and investors because its platform speaks to a big opportunity within the wider world of software today.

Enterprise IT has long been thought of as the less-fun end of technology: it’s all about getting work done, and a lot of the software used in a business environment is complex and often requires technical knowledge to implement, use, fix and adapt in any way.

This may still the case for a lot of it, especially for the most sophisticated tools, but at the same time we have seen a lot of “consumerization” come into IT, where user-friendly hardware and software built for consumers — specifically non-technical consumers — either inspires new enterprise services, or are simply directly imported into the workplace environment.

No-code software — like automation, another big trend in enterprise IT right now — plays a big role in how enterprise tools are becoming more user-friendly. One of the biggest roadblocks in a lot of office environments is that when workers identify things that don’t work, or could work much better than they do, they need to file tickets and get IT teams — also often overworked — to do the fixing for them. No-code platforms can help circumvent some of that work — so long as the roadblock of IT approves the use, that is.

Bryter’s conception and existence comes out of the no-code trend. It plays on the same ideas as IFTTT or Zapier but is very firmly aimed at users who might use pieces of enterprise software as part of their jobs, but have never had to delve into figuring out how they actually work.

There are already a lot of “low-code” (minimal coding) and other no-code on the market today for business (not consumer) use cases. They include Blender.io, Zapier, Tray.io (a London-founded startup that itself raised a big round last autumn), n8n (also German, backed by Sequoia), and also biggies like MuleSoft (acquired by Salesforce in 2018 at a $ 6.5 billion valuation).

Bryter’s contention is that many of these actually need more technical know-how than they initially claim. Grupp pointed out that the earliest automation tools for enterprise have been around for decades at this point, but even most of the very modern descendants of those “will require some coding.” Bryter’s toolbox essentially lets users create dialogues with users — which they can program based on the expertise that they will have in their particular fields — which then sources data they can then plug into other software via the Bryter platform in order to “perform” different tasks more quickly.

Grupp’s contention is that while these kinds of tools have long been used, they will be in even more demand going forward.

“After COVID-19 workers will be even more distributed,” he said. “Teams and individuals will need to access information in a faster way, and the only way for big organizations to distribute that knowledge is through more digital tools.” The idea is that Bryter can essentially help bridge those gaps in a more efficient way.

Bryter’s target user and its approach underscores why investors like Accel see accessible, no-code solutions as a big opportunity.

“No-code software is really reducing the barriers of adoption,” Luca Bocchio, a partner at Accel, said in an interview. “If people like you and I can use the software, then that means demand can multiply by big numbers.” That’s in contrast to a lot of enterprise software today, which very limited in how it can grow, he added. “Plus, enterprises these days want to see more future visibility in terms of the products they adopt. They want to make sure something will stick around, and so they tend not to want to work with super young startups. But it’s happening for Bryter, and the is a testament to Bryter and to the market potential.”


TechCrunch

Enterprise startups UIPath and Scale have drawn huge attention in recent years from companies looking to automate workflows, from RPA (robotic process automation) to data labeling.

What’s been overlooked in the wake of such workflow-specific tools has been the base class of products that enterprises are using to build the core of their machine learning (ML) workflows, and the shift in focus toward automating the deployment and governance aspects of the ML workflow.

That’s where MLOps comes in, and its popularity has been fueled by the rise of core ML workflow platforms such as Boston-based DataRobot. The company has raised more than $ 430 million and reached a $ 1 billion valuation this past fall serving this very need for enterprise customers. DataRobot’s vision has been simple: enabling a range of users within enterprises, from business and IT users to data scientists, to gather data and build, test and deploy ML models quickly.

Founded in 2012, the company has quietly amassed a customer base that boasts more than a third of the Fortune 50, with triple-digit yearly growth since 2015. DataRobot’s top four industries include finance, retail, healthcare and insurance; its customers have deployed over 1.7 billion models through DataRobot’s platform. The company is not alone, with competitors like H20.ai, which raised a $ 72.5 million Series D led by Goldman Sachs last August, offering a similar platform.

Why the excitement? As artificial intelligence pushed into the enterprise, the first step was to go from data to a working ML model, which started with data scientists doing this manually, but today is increasingly automated and has become known as “auto ML.” An auto-ML platform like DataRobot’s can let an enterprise user quickly auto-select features based on their data and auto-generate a number of models to see which ones work best.

As auto ML became more popular, improving the deployment phase of the ML workflow has become critical for reliability and performance — and so enters MLOps. It’s quite similar to the way that DevOps has improved the deployment of source code for applications. Companies such as DataRobot and H20.ai, along with other startups and the major cloud providers, are intensifying their efforts on providing MLOps solutions for customers.

We sat down with DataRobot’s team to understand how their platform has been helping enterprises build auto-ML workflows, what MLOps is all about and what’s been driving customers to adopt MLOps practices now.

The rise of MLOps


TechCrunch

The pace of malicious hacks and security breaches is showing no signs of slowing down, and spend among enterprises to guard against that is set to reach $ 124 billion this year. That’s also having a knock-on effect on the most innovative cybersecurity startups, which continue to raise big money to grow and meet that demand.

In the latest development, a New York startup called BlueVoyant — which provides managed security, professional services and most recently threat intelligence — has picked up $ 82.5 million in a Series B round of funding at a valuation in excess of $ 430 million.

The funding is coming from a range of new and existing investors that includes Fiserv, the fintech giant that’s acquiring First Data for $ 22 billion. (The startup is not disclosing any other names at this time, it said.) It has raised $ 207.5 million to date.

BlueVoyant has a notable pedigree that goes some way also to explaining how the idea for the startup first germinated.

Co-founder and CEO Jim Rosenthal met his co-founder Tom Glocer (the former CEO of Thomson Reuters) when Rosenthal was COO of Morgan Stanley and Glocer was a director at the financial services giant (Glocer is still on the board). Glocer said that in 2012 and 2013, a fair amount of Rosenthal’s work involved cyber defense, and he came into close contact there with Glocer, who was chairing the operations and technology committee at the time.

“Here was an incredibly strategic, smart fellow in charge of operations,” he said of Rosenthal. “When it came time for him to retire, he told me he wanted to do one more big thing, but in a more entrepreneurial fashion. I suggested to him that the next step could be to work on [cybersecurity], which we were focusing on at Morgan Stanley.”

Glocer noted that the bank was spending some $ 300 million annually on cybersecurity at the time. It effectively had all the resources of the world at its disposal to invest in tackling the risks, but the two were all too aware of how even that could prove not to be enough — and of course for any company with fewer resources, or that wasn’t build as a tech company or with technology as part of its DNA.

BlueVoyant was built with those kinds of challenges in mind.

The startup has amassed talent from the world of private enterprise, but also a number of government organizations such as the NSA, FBI, GCHQ and Unit 8200 — which are alternately renowned and somewhat notorious for their work in cybersecurity and hacking. Its offices span a multitude of geographies that speaks to the customers that it has picked up in its quiet growth to date (which also gives some color to its valuation, too). In addition to the US, it has operatoins in Israel, the United Kingdom, Spain and the Philippines.

Tapping that talent pool, the company focuses on three areas of service for its customers: threat intelligence, managed security and professional services (with the latter focused specifically on those related to security implementations and operations).

Within these, Rosenthal said in an interview that it both builds its own IP, and also brings in software from a range of trusted partners (which include many of the biggest security software companies around today). Key to the proposition, though, is also the implementation of that technology. The theory is that technology will only get a company so far: you need a multi-level strategy when it comes to cybersecurity, and part of that will involve people able to identify vulnerabilities and figuring out how to fix or defend around them.

BlueVoyant believes the opportunity for it is twofold: targeting small and medium enterprises — the pitch being that it can provide the same kind of software and level of services that large enterprises enjoy; and targeting larger enterprises that may already have large IT budgets and teams tasked with cybersecurity, but could still use supplementary work from a world-class team of experts that would be a challenge to amass directly.

“My view is that for firms with very good cyber defenses, external cyber intelligence is important because you can’t defend everything equally,” Rosenthal said. “Having good actionable defense makes it better.

“Then for firms that are unable to afford an excellent cyber defense instructed by themselves and may not be able to attract the talent necessary, a managed security service is the right and important answer,” he continued. “That kind of managed security now needs to be available to companies of all sizes, not just the big ones but small and medium organizations, too. We have created a tech stack and level of talent capable of providing those.”

The formula appears to be working. Since launching the first tranche of its offering, managed services, in 2018, BlueVoyant has picked up some 150 customers in verticals like financial services, manufacturing, municipal government and education.

Working with partners is one way that BlueVoyant plans to expand that customer base over time. Fiserv is backing the startup as a strategic investment and the two will collaborate on providing respective services to each other’s clients. Specifically, Glocer noted that many of the banks that Fiserv currently works with are typical targets: businesses that have a lot to lose in a breach, but may lack the size to ever adequately secure its infrastructure and other assets.

“The strategic alliance between Fiserv and BlueVoyant brings advanced cyber defense capabilities to banks and credit unions of all sizes,” said Byron Vielehr, Chief Administrative Officer of Fiserv. “Our continued investment in BlueVoyant underscores the value these capabilities can bring to our clients.”

BlueVoyant is not the only big security startup to raise at a high valuation in recent times. Auth0 raised $ 103 million at a $ 1 billion valuation last week. In April, Bitglass closed a $ 70 million round. 2018 had seen a high water mark for security funding, with startups raking in a record $ 5.3 billion in the year: it will be worth watching to see whether the ongoing march of breaches will see those figures rise again this year.


TechCrunch

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