Turing nabs $32M more for an AI-based platform to source and manage engineers remotely

As remote work continues to solidify its place as a critical aspect of how businesses exist these days, a startup that has built a platform to help companies source and bring on one specific category of remote employees — engineers — is taking on some more funding to meet demand.

Turing — which has built an AI-based platform to help evaluate prospective, but far-flung, engineers, bring them together into remote teams, then manage them for the company — has picked up $32 million in a Series B round of funding led by WestBridge Capital. Its plan is as ambitious as the world it is addressing is wide: an AI platform to help define the future of how companies source IT talent to grow.

“They have a ton of experience in investing in global IT services, companies like Cognizant and GlobalLogic,” said co-founder and CEO Jonathan Siddharth of its lead investor in an interview the other day. “We see Turing as the next iteration of that model. Once software ate the IT services industry, what would Accenture look like?”

It currently has a database of some 180,000 engineers covering around 100 or so engineering skills, including React, Node, Python, Agular, Swift, Android, Java, Rails, Golang, PHP, Vue, DevOps, machine learning, data engineering and more.

In addition to WestBridge, other investors in this round included Foundation Capital, Altair Capital, Mindset Ventures, Frontier Ventures and Gaingels. There is also a very long list of high-profile angels participating, underscoring the network that the founders themselves have amassed. It includes unnamed executives from Google, Facebook, Amazon, Twitter, Microsoft, Snap and other companies, as well as Adam D’Angelo (Facebook’s first CTO and CEO at Quora), Gokul Rajaram, Cyan Banister and Scott Banister, and Beerud Sheth (the founder of Upwork), among many others (I’ll run the full list below).

Turing is not disclosing its valuation. But as a measure of its momentum, it was only in August that the company raised a seed round of $14 million, led by Foundation. Siddharth said that the growth has been strong enough in the interim that the valuations it was getting and the level of interest compelled the company to skip a Series A altogether and go straight for its Series B.

The company now has signed up to its platform 180,000 developers from across 10,000 cities (compared to 150,000 developers back in August). Some 50,000 of them have gone through automated vetting on the Turing platform, and the task will now be to bring on more companies to tap into that trove of talent.

Or, “We are demand-constrained,” which is how Siddharth describes it. At the same time, it’s been growing revenues and growing its customer base, jumping from revenues of $9.5 million in October to $12 million in November, increasing 17x since first becoming generally available 14 months ago. Current customers include VillageMD, Plume, Lambda School, Ohi Tech, Proxy and Carta Healthcare.

Remote work = immediate opportunity

A lot of people talk about remote work today in the context of people no longer able to go into their offices as part of the effort to curtail the spread of COVID-19. But in reality, another form of it has been in existence for decades.

Offshoring and outsourcing by way of help from third parties — such as Accenture and other systems integrators — are two ways that companies have been scaling and operating, paying sums to those third parties to run certain functions or build out specific areas instead of shouldering the operating costs of employing, upsizing and sometimes downsizing that labor force itself.

Turing is essentially tapping into both concepts. On one hand, it has built a new way to source and run teams of people, specifically engineers, on behalf of others. On the other, it’s using the opportunity that has presented itself in the last year to open up the minds of engineering managers and others to consider the idea of bringing on people they might have previously insisted work in their offices, to now work for them remotely, and still be effective.

Siddarth and co-founder Vijay Krishnan (who is the CTO) know the other side of the coin all too well. They are both from India, and both relocated to the Valley first for school (post-graduate degrees at Stanford) and then work at a time when moving to the Valley was effectively the only option for ambitious people like them to get employed by large, global tech companies, or build startups — effectively what could become large, global tech companies.

“Talent is universal, but opportunities are not,” Siddarth said to me earlier this year when describing the state of the situation.

A previous startup co-founded by the pair — content discovery app Rover — highlighted to them a gap in the market. They built the startup around a remote and distributed team of engineers, which helped them keep costs down while still recruiting top talent. Meanwhile, rivals were building teams in the Valley. “All our competitors in Palo Alto and the wider area were burning through tons of cash, and it’s only worse now. Salaries have skyrocketed,” he said.

After Rover was acquired by Revcontent, a recommendation platform that competes against the likes of Taboola and Outbrain, they decided to turn their attention to seeing if they could build a startup based on how they had, basically, built their own previous startup.

There are a number of companies that have been tapping into the different aspects of the remote work opportunity, as it pertains to sourcing talent and how to manage it.

They include the likes of Remote (raised $35 million in November), Deel ($30 million raised in September), Papaya Global ($40 million also in September), Lattice ($45 million in July) and Factorial ($16 million in April), among others.

What’s interesting about Turing is how it’s trying to address and provide services for the different stages you go through when finding new talent. It starts with an AI platform to source and vet candidates. That then moves into matching people with opportunities, and onboarding those engineers. Then, Turing helps manage their work and productivity in a secure fashion, and also provides guidance on the best way to manage that worker in the most compliant way, be it as a contractor or potentially as a full-time remote employee.

The company is not freemium, as such, but gives people two weeks to trial people before committing to a project. So unlike an Accenture, Turing itself tries to build in some elasticity into its own product, not unlike the kind of elasticity that it promises its customers.

It all sounds like a great idea now, but interestingly, it was only after remote work really became the norm around March/April of this year that the idea really started to pick up traction.

“It’s amazing what COVID has done. It’s led to a huge boom for Turing,” said Sumir Chadha, managing director for WestBridge Capital, in an interview. For those who are building out tech teams, he added, there is now “No need for to find engineers and match them with customers. All of that is done in the cloud.”

“Turing has a very interesting business model, which today is especially relevant,” said Igor Ryabenkiy, managing partner at Altair Capital, in a statement. “Access to the best talent worldwide and keeping it well-managed and cost-effective make the offering attractive for many corporations. The energy of the founding team provides fast growth for the company, which will be even more accelerated after the B-round.”

PS. I said I’d list the full, longer list of investors in this round. In these COVID times, this is likely the biggest kind of party you’ll see for a while. In addition to those listed above, it included [deep breath] Founders Fund, Chapter One Ventures (Jeff Morris Jr.), Plug and Play Tech Ventures (Saeed Amidi), UpHonest Capital (​Wei Guo, Ellen Ma​), Ideas & Capital (Xavier Ponce de León), 500 Startups Vietnam (Binh Tran and Eddie Thai), Canvas Ventures (Gary Little), B Capital (Karen Appleton P​age, Kabir Narang), Peak State Ventures (​Bryan Ciambella, Seva Zakharov)​, Stanford StartX Fund, Amino C​apital, ​Spike Ventures, Visary Capital (Faizan Khan), Brainstorm Ventures (Ariel Jaduszliwer), Dmitry Chernyak, Lorenzo Thione, Shariq Rizvi, Siqi Chen, Yi Ding, Sunil Rajaraman, Parakram Khandpur, Kintan Brahmbhatt, Cameron Drummond, Kevin Moore, Sundeep Ahuja, Auren Hoffman, Greg Back, Sean Foote, Kelly Graziadei, Bobby Balachandran, Ajith Samuel, Aakash Dhuna, Adam Canady, Steffen Nauman, Sybille Nauman, Eric Cohen, Vlad V, Marat Kichikov, Piyush Prahladka, Manas Joglekar, Vladimir Khristenko, Tim and Melinda Thompson, Alexandr Katalov, Joseph and Lea Anne Ng, Jed Ng, Eric Bunting, Rafael Carmona, Jorge Carmona, Viacheslav Turpanov, James Borow, Ray Carroll, Suzanne Fletcher, Denis Beloglazov, Tigran Nazaretian, Andrew Kamotskiy, Ilya Poz, Natalia Shkirtil, Ludmila Khrapchenko, Ustavshchikov Sergey, Maxim Matcin and Peggy Ferrell.

Fairmarkit lands $30M Series B to modernize procurement

As the pandemic has raged on, it has shone a spotlight on the importance of procurement, especially in certain sectors. Fairmarkit, a Boston startup, is working to bring a modern digital procurement system to the enterprise. Today, the company announced a $30 million Series B.

GGV Capital and Insight Partners led the round with help from existing investors 1984 VC, NewStack and NewFund. Today’s investment brings the total raised to $42 million, according to the company.

Fairmarkit wants to replace large procurement software systems from companies like Oracle and SAP that have been around for decades, says company co-founder and CEO Kevin Frechette. When he looked around a couple of years ago, he saw a space full of these legacy vendors and ripe for disruption.

What’s more, he says that these systems have been designed to track only the biggest purchases over $500,000 or $1 million. Anything under that is what’s known as tail spend. “So procurement really focuses on companies’ biggest purchases, say things over a million, but anything under that size just gets forgotten about and neglected. It’s called tail spend, and it’s still 80% of what they buy, 80% of their vendors and 20% of the budget,” he told me.

This spending accounts for billions of dollars, yet Frechette says, it has lacked a good tracking system. He saw an opportunity, and he and his co-founders built a solution. Its first customer was the MBTA, Boston’s mass transit system (a system that could use all the help it can get in terms of getting more efficient). Today the company has more than 50 customers across a variety of industries.

The system acts as a marketplace for vendors and a central buying system for customers where they can find goods and services at this price point below $1 million. It imports a customer’s vendor data, and then combines this with other data to build a huge database of buying information. From that, they can determine what a customer needs and using AI, find the best prices for a particular order.

Frechette says this not only provides a way to save money — he says customers have been able to cut purchase costs by 10% with his system — it also provides a way to surface diverse vendors, whether that’s businesses owned by women, people of color, veterans, local business or however you define that.

He says too often what happens is that these deals aren’t put under typical procurement department scrutiny and they just get passed through, but Fairmarkit helps surface these companies and give them a shot at the business. “So because the core of our technology is a vendor recommendation engine […], we can help to invite those diverse vendors and really just give them a fair shot,” he said.

The company started the year with 40 employees and have added 30 since. The plan is to double that number next year, and as they do, Frechette hopes to reflect the diversity of the company’s product by building a correspondingly diverse employee base.

“It’s really just keeping it at the forefront. We want to make sure that we’re not just doing surveys around how we are doing for diversity and inclusion, but we’re putting programs in place to help out with it. It’s something I’m very very passionate about because it’s been such a sticking point as well on how we’re helping diverse vendors,” he said.

Frechette says that he has managed to grow the company and build a culture in spite of the pandemic not allowing employees to come into an office. He doesn’t see a world where the office will be a requirement in the future.

“We’ve hit an inflection point this year where there’s no world where we need everyone to be in an office […], which once again only helps to accelerate our business because we’re not constricted by everyone in this one small [geographical] sector. We can operate across the board [from anywhere],” he said.

Payment Processing Giant TSYS: Ransomware Incident “Immaterial” to Company

Payment card processing giant TSYS suffered a ransomware attack earlier this month. Since then reams of data stolen from the company have been posted online, with the attackers promising to publish more in the coming days. But the company says the malware did not jeopardize card data, and that the incident was limited to administrative areas of its business.

Headquartered in Columbus, Ga., Total System Services Inc. (TSYS) is the third-largest third-party payment processor for financial institutions in North America, and a major processor in Europe.

TSYS provides payment processing services, merchant services and other payment solutions, including prepaid debit cards and payroll cards. In 2019, TSYS was acquired by financial services firm Global Payments Inc. [NYSE:GPN].

On December 8, the cybercriminal gang responsible for deploying the Conti ransomware strain (also known as “Ryuk“) published more than 10 gigabytes of data that it claimed to have removed from TSYS’s networks.

Conti is one of several cybercriminal groups that maintains a blog which publishes data stolen from victims in a bid to force the negotiation of ransom payments. The gang claims the data published so far represents just 15 percent of the information it offloaded from TSYS before detonating its ransomware inside the company.

In a written response to requests for comment, TSYS said the attack did not affect systems that handle payment card processing.

“We experienced a ransomware attack involving systems that support certain corporate back office functions of a legacy TSYS merchant business,” TSYS said. “We immediately contained the suspicious activity and the business is operating normally.”

According to Conti, the “legacy” TSYS business unit hit was Cayan, an entity acquired by TSYS in 2018 that enables payments in physical stores and mobile locations, as well as e-commerce.

Conti claims prepaid card data was compromised, but TSYS says this is not the case.

“Transaction processing is conducted on separate systems, has continued without interruption and no card data was impacted,” the statement continued. “We regret any inconvenience this issue may have caused. This matter is immaterial to the company.”

TSYS declined to say whether it paid any ransom. But according to Fabian Wosar, chief technology officer at computer security firm Emsisoft, Conti typically only publishes data from victims that refuse to negotiate a ransom payment.

Some ransomware groups have shifted to demanding two separate ransom payments; one to secure a digital key that unlocks access to servers and computers held hostage by the ransomware, and a second in return for a promise not to publish or sell any stolen data. However, Conti so far has not adopted the latter tactic, Wosar said.

“Conti almost always does steal data, but we haven’t seen them negotiating for leaks and keys separately,” he explained. “For the negotiations we have seen it has always been one price for everything (keys, deletion of data, no leaks etc.).”

According to a report released last month by the Financial Services Information Sharing and Analysis Center (FS-ISAC), an industry consortium aimed at fighting cyber threats, the banking industry remains a primary target of ransomware groups. FS-ISAC said at least eight financial institutions were hit with ransomware attacks in the previous four months. The report notes that by a wide margin, Ryuk continues to be the most prolific ransomware threat targeting financial services firms.

FireEye Breached: Taking Action and Staying Protected

To Our Customers, Prospects, Partners, and the Cybersecurity Community:

It’s not every day we see a fellow cybersecurity company, especially one with a significant presence serving the federal government, as the subject of a breach. On December 8, FireEye disclosed a sophisticated attack which led to the “unauthorized access of their red team tools.” The statement went on to say the company does not know whether the attacker intends to use the stolen tools themselves or publicly disclose them.

We are sad to hear the news; all cybersecurity vendors at some level share a unified purpose of making the world a more secure place. Our thoughts are with our colleagues at FireEye and with their customers. SentinelOne’s commitment to keep customers protected remains unwavering. We innovate to raise the cybersecurity bar to defend our digital way of life.

In this blog, we update on the actions SentinelOne has taken across our SentinelLabs security research team, Vigilance MDR team, and product team in response to the FireEye breach. Our platform is able to detect the known malware samples associated with the FireEye breach. 

Detection is Foundational to Visibility & Protection

We continue to monitor and hunt for relevant IOCs and artifacts related to the breach. We can also confirm that all assets that are seen so far in the wild are detected by the SentinelOne agents, with no upgrade needed. If there are parts of your network that are not protected with SentinelOne, we encourage you to close that gap, even if you need to exceed the number of licenses you have at the moment. We recommend the use of our Rogue system detection to identify the systems that should have an agent deployed. Below this blog, please find a list of hashes based on FireEye’s reporting and our own research that we confirm are covered.

Hunting Pack Released for Every SentinelOne Customer

We’ve already released a bespoke and ready-to-use hunting pack in every customer’s SentinelOne console for retrospective hunting missions. SentinelOne’s industry-leading data retention periods enable lengthy lookbacks for thorough investigations. This customized hunting package enables our customers to know if any of the artifacts related to this breach exist – or have existed – within your enterprise.

We’re Here to Help

SentinelOne is committed to doing the right thing – and we stand by ready to help at no cost. Here are several actionable steps our team suggests:

  1. SentinelOne Customers: if you’re a Core, Control, or Complete customer and desire custom hunting assistance, our Vigilance MDR team and our Customer Success organizations stand ready to assist. If you need additional agents, we’re ready to assist with rapid deployment. Our 24/7/365 team is ready to help via phone or console.
  2. Non-SentinelOne Customers: if you need assistance conducting a risk assessment as it relates to the FireEye breach or securing unprotected devices, SentinelOne is ready. We can deploy in minutes without business interruption or restarts. Our team of experts can help quickly determine if any traces of the FireEye beach are in your environment for compliance and executive briefing purposes.

We’re here to help. We’re here to protect. We’re in this together.

Webinar: Communicating With Your Team & Leadership
The FireEye Breach

Latest FireEye Indicators of Compromise (IOCs)

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Firebolt raises $37M to take on Snowflake, Amazon and Google with a new approach to data warehousing

For many organizations, the shift to cloud computing has played out more realistically as a shift to hybrid architectures, where a company’s data is just as likely to reside in one of a number of clouds as it might in an on-premise deployment, in a data warehouse or in a data lake. Today, a startup that has built a more comprehensive way to assess, analyse and use that data is announcing funding as it looks to take on Snowflake, Amazon, Google and others in the area of enterprise data analytics.

Firebolt, which has redesigned the concept of a data warehouse to work more efficiently and at a lower cost, is today announcing that it has raised $37 million from Zeev Ventures, TLV Partners, Bessemer Venture Partners and Angular Ventures. It plans to use the funding to continue developing its product and bring on more customers.

The company is officially “launching” today but — as is the case with so many enterprise startups these days operating in stealth — it has been around for two years already building its platform and signing commercial deals. It now has some 12 large enterprise customers and is “really busy” with new business, said CEO Eldad Farkash in an interview.

The funding may sound like a large amount for a company that has not really been out in the open, but part of the reason is because of the track record of the founders. Farkash was one of the founders of Sisense, the successful business intelligence startup, and he has co-founded Firebolt with two others who were on Sisense’s founding team, Saar Bitner as COO and Ariel Yaroshevich as CTO.

At Sisense, these three were coming up against an issue: When you are dealing in terabytes of data, cloud data warehouses were straining to deliver good performance to power its analytics and other tools, and the only way to potentially continue to mitigate that was by piling on more cloud capacity.

Farkash is something of a technical savant and said that he decided to move on and build Firebolt to see if he could tackle this, which he described as a new, difficult and “meaningful” problem. “The only thing I know how to do is build startups,” he joked.

In his opinion, while data warehousing has been a big breakthrough in how to handle the mass of data that companies now amass and want to use better, it has started to feel like a dated solution.

“Data warehouses are solving yesterday’s problem, which was, ‘How do I migrate to the cloud and deal with scale?’ ” he said, citing Google’s BigQuery, Amazon’s RedShift and Snowflake as fitting answers for that issue. “We see Firebolt as the new entrant in that space, with a new take on design on technology. We change the discussion from one of scale to one of speed and efficiency.”

The startup claims that its performance is up to 182 times faster than that of other data warehouses. It’s a SQL-based system that works on principles that Farkash said came out of academic research that had yet to be applied anywhere, around how to handle data in a lighter way, using new techniques in compression and how data is parsed. Data lakes in turn can be connected with a wider data ecosystem, and what it translates to is a much smaller requirement for cloud capacity.

This is not just a problem at Sisense. With enterprise data continuing to grow exponentially, cloud analytics is growing with it, and is estimated by 2025 to be a $65 billion market, Firebolt estimates.

Still, Farkash said the Firebolt concept was initially a challenging sell even to the engineers that it eventually hired to build out the business: It required building completely new warehouses from the ground up to run the platform, five of which exist today and will be augmented with more, on the back of this funding, he said.

And it should be pointed out that its competitors are not exactly sitting still either. Just yesterday, Dataform announced that it had been acquired by Google to help it build out and run better performance at BigQuery.

“Firebolt created a SaaS product that changes the analytics experience over big data sets,” Oren Zeev of Zeev Ventures said in a statement. “The pace of innovation in the big data space has lagged the explosion in data growth rendering most data warehousing solutions too slow, too expensive, or too complex to scale. Firebolt takes cloud data warehousing to the next level by offering the world’s most powerful analytical engine. This means companies can now analyze multi Terabyte / Petabyte data sets easily at significantly lower costs and provide a truly interactive user experience to their employees, customers or anyone who needs to access the data.”

AWS expands on SageMaker capabilities with end-to-end features for machine learning

Nearly three years after it was first launched, Amazon Web Services’ SageMaker platform has gotten a significant upgrade in the form of new features, making it easier for developers to automate and scale each step of the process to build new automation and machine learning capabilities, the company said.

As machine learning moves into the mainstream, business units across organizations will find applications for automation, and AWS is trying to make the development of those bespoke applications easier for its customers.

“One of the best parts of having such a widely adopted service like SageMaker is that we get lots of customer suggestions which fuel our next set of deliverables,” said AWS vice president of machine learning, Swami Sivasubramanian. “Today, we are announcing a set of tools for Amazon SageMaker that makes it much easier for developers to build end-to-end machine learning pipelines to prepare, build, train, explain, inspect, monitor, debug and run custom machine learning models with greater visibility, explainability and automation at scale.”

Already companies like 3M, ADP, AstraZeneca, Avis, Bayer, Capital One, Cerner, Domino’s Pizza, Fidelity Investments, Lenovo, Lyft, T-Mobile and Thomson Reuters are using SageMaker tools in their own operations, according to AWS.

The company’s new products include Amazon SageMaker Data Wrangler, which the company said was providing a way to normalize data from disparate sources so the data is consistently easy to use. Data Wrangler can also ease the process of grouping disparate data sources into features to highlight certain types of data. The Data Wrangler tool contains more than 300 built-in data transformers that can help customers normalize, transform and combine features without having to write any code.

Amazon also unveiled the Feature Store, which allows customers to create repositories that make it easier to store, update, retrieve and share machine learning features for training and inference.

Another new tool that Amazon Web Services touted was Pipelines, its workflow management and automation toolkit. The Pipelines tech is designed to provide orchestration and automation features not dissimilar from traditional programming. Using pipelines, developers can define each step of an end-to-end machine learning workflow, the company said in a statement. Developers can use the tools to re-run an end-to-end workflow from SageMaker Studio using the same settings to get the same model every time, or they can re-run the workflow with new data to update their models.

To address the longstanding issues with data bias in artificial intelligence and machine learning models, Amazon launched SageMaker Clarify. First announced today, this tool allegedly provides bias detection across the machine learning workflow, so developers can build with an eye toward better transparency on how models were set up. There are open-source tools that can do these tests, Amazon acknowledged, but the tools are manual and require a lot of lifting from developers, according to the company.

Other products designed to simplify the machine learning application development process include SageMaker Debugger, which enables developers to train models faster by monitoring system resource utilization and alerting developers to potential bottlenecks; Distributed Training, which makes it possible to train large, complex, deep learning models faster than current approaches by automatically splitting data across multiple GPUs to accelerate training times; and SageMaker Edge Manager, a machine learning model management tool for edge devices, which allows developers to optimize, secure, monitor and manage models deployed on fleets of edge devices.

Last but not least, Amazon unveiled SageMaker JumpStart, which provides developers with a searchable interface to find algorithms and sample notebooks so they can get started on their machine learning journey. The company said it would give developers new to machine learning the option to select several pre-built machine learning solutions and deploy them into SageMaker environments.

HealNow raises $1.3 million to bring online payments to pharmacies

As the health tech landscape rapidly evolves, another startup is making its presence known. HealNow has closed a $1.3 million round of funding from SoftBank Opportunity Fund and Alabama Futures Fund.

The company was founded by Halston Prox and Joshua Smith. Prox has worked in healthcare for more than a decade with major organizations such as Providence Health, Mount Sinai and Baylor Scott & White, mostly focused on digitizing health records and designing and implementing software for doctors, nurses, etc. Smith, CTO at the company, has been a developer since 2012.

The duo founded HealNow to become the central nervous system for order and delivery of prescriptions, according to Prox. Your average payments processing system isn’t necessarily applicable to pharmacies large and small because of the complexities of health insurance and the regulatory landscape.

Not only is it costly to facilitate online payments for pharmacies, but they also have their own pharmacy management systems and workflows that can be easily disrupted by moving to a new payments system.

HealNow has built a system that’s specifically tailored to pharmacies of any shape or size, from grocery stores to mom and pop pharmacies and everything in between. It’s a white label solution, meaning that any pharmacy can put their brand language on the product.

“We’re embedded in their current workflows and pharmacies don’t have to do anything manual, even if they’re using a pharmacy management system,” said Prox.

When a user looks to get a prescription from their pharmacy, they are sent a link that allows them to securely answer any questions that may be necessary for the pickup, enter insurance info, make a payment and schedule a curbside pickup or a delivery. The tech also integrates with third-party delivery services for pharmacies that offer deliveries.

This technology has been particularly important during the COVID-19 pandemic, giving smaller pharmacies the chance to compete with bigger chains who have digital solutions already set up that allow for curbside pick up. This is especially true now that Amazon has gotten into the space with the launch of Amazon Pharmacy.

HealNow is a SaaS company, charging a monthly subscription fee for use of the platform, as well as a service fee for prescriptions purchased on the platform. However, that service fee is a flat rate that never changes based on the cost of the prescription.

The space is crowded and growing more crowded, with competitors like NimbleRX and Capsule offering their own spin on simplifying and digitizing the pharmacy. One big difference for HealNow, says Prox, is that the startup has no intention of ever being a pharmacy, but rather serving pharmacies in a way that doesn’t disrupt their current workflow or system.

“We’re not a pharmacy, and we want to enable all these pharmacies to be online,” said Prox. “To do that we have to do that in an unbiased way by focusing on being a complete tech company.”

The funding is going primarily toward building out the sales and marketing arms of the company to continue fueling growth. HealNow has a foothold in the West, Southwest and Middle America, and is opening an office in Birmingham to sprint across the East Coast. Prox says the company is processing thousands of orders a day and tens of thousands of orders each month.

HealNow launched in 2018 after graduating from the Entrepreneurs Roundtable Accelerator .

WorkRamp raises $17M to ramp up its enterprise learning platform

Remote learning and training have become a large priority this year for organizations looking to keep employees engaged and up to date on work practices at a time when many of them are not working in an office — and, in the case of those who have joined in 2020, may have never met any of their work colleagues in person, ever. Today one of the startups that’s built a new, more user-friendly approach to creating and provisioning those learning materials is announcing some funding as it experiences a boost in its growth.

WorkRamp, which has built a platform that helps organizations build their own training materials, and then distribute them both to their workforce and to partners, has raised $17 million, a Series B round of funding that’s being led by OMERS Ventures, with Bow Capital also participating.

Its big pitch is that it has built the tools to make it easy for companies to build their own training and learning materials, incorporating tests, videos, slide shows and more, and by making it easier for companies to build these themselves, the materials themselves become more engaging and less stiff.

“We’re disrupting the legacy LMS [learning management system] providers, the Cornerstones of the world, with our bite-size training platform,” said CEO and founder Ted Blosser in an interview. “We want to do what Peloton did for the exercise market, but with corporate training. We are aiming for a consumer-grade experience.”

The company, originally incubated in Y Combinator, has now raised $27 million.

The funding comes on the back of strong growth for WorkRamp . Blosser said that it now has around 250 customers, with 1 million courses collectively created on its platform. That list includes fast-growing tech companies like Zoom, Box, Reddit and Intercom, as well as Disney, GlobalData and PayPal. As it continues to expand, it will be interesting to see how and if it can also snag more legacy, late adopters who are not as focused on tech in their own DNA.

WorkRamp estimates that there is some $20 billion spent annually by organizations on corporate training. Unsurprisingly, that has meant the proliferation of a number of companies building tools to address that market.

Just Google WorkRamp and you’re likely to encounter a number of its competitors who have bought its name as a keyword to snag a little more attention. There are both big and small players in the space, including Leapsome, Capterra, Lessonly, LearnUpon (which itself recently raised a big round), SuccessFactors and TalentLMS.

The interesting thing about what WorkRamp has built is that it plays on the idea of the “creator,” which really has been a huge development in our digital world. YouTube may have kicked things off with the concept of “user-generated content.” but today we have TikTok, Snapchat, Facebook, Twitter and so many more platforms — not to mention smartphones themselves, with their easy facilities to shoot videos and photos of others, or of yourself, and then share with others — which have made the idea of building your own work, and looking at that of others, extremely accessible.

That has effectively laid the groundwork for a new way of conceiving of even more prosaic things, like corporate training. (Can there really be anything more comedically prosaic than that?) Other startups like Kahoot have also played on this idea, by making it easy for enterprises to build their own games to help train their staff.

This is what WorkRamp has aimed to tap into with its own take on the learning market, to help its customers eschew the idea of hiring outside production companies to make training materials, or expect WorkRamp to build those materials for them: Instead, the people who are going to use the training now have the control.

“I think it’s critical to be able to build your own customer education,” Blosser said. “That’s a big trend for clients that want both to rapidly onboard people but also reduce costs.”

The company’s platform includes user-friendly drag-and-drop functionality, which also lets people build slide shows, flip cards and questions that viewers can answer. The plan is to bring on more “Accenture” style consultants, Blosser said, for bigger customers who may not be as tech savvy to help them take better advantage of the tools. It also integrates with third-party packages like Salesforce.com, Workday and Zoom both to build out training as well as distribute it.

“Since 2000, we have seen three major technology shifts in the enterprise: the transition from on-premise to SaaS, the growth of mobile, and the most recent – sweeping digital transformation across almost every part of every business,” said Eugene Lee of OMERS Ventures, in a statement. “The pandemic has forced adoption of a digital-first approach towards customers and employees across virtually all industries. WorkRamp’s platform is foundational to empowering both of these important audiences today and in the future. We are bullish on the massive opportunity in front of the company and are excited to get involved.” Lee is joining the board with this round.

Arthur.ai snags $15M Series A to grow machine learning monitoring tool

At a time when more companies are building machine learning models, Arthur.ai wants to help by ensuring the model accuracy doesn’t begin slipping over time, thereby losing its ability to precisely measure what it was supposed to. As demand for this type of tool has increased this year, in spite of the pandemic, the startup announced a $15 million Series A today.

The investment was led by Index Ventures with help from newcomers Acrew and Plexo Capital, along with previous investors Homebrew, AME Ventures and Work-Bench. The round comes almost exactly a year after its $3.3 million seed round.

As CEO and co-founder Adam Wenchel explains, data scientists build and test machine learning models in the lab under ideal conditions, but as these models are put into production, the performance can begin to deteriorate under real-world scrutiny. Arthur.ai is designed to root out when that happens.

Even as COVID has wreaked havoc throughout much of this year, the company has grown revenue 300% in the last six months smack dab in the middle of all that. “Over the course of 2020, we have begun to open up more and talk to [more] customers. And so we are starting to get some really nice initial customer traction, both in traditional enterprises as well as digital tech companies,” Wenchel told me. With 15 customers, the company is finding that the solution is resonating with companies.

It’s interesting to note that AWS announced a similar tool yesterday at re:Invent called SageMaker Clarify, but Wenchel sees this as more of a validation of what his startup has been trying to do, rather than an existential threat. “I think it helps create awareness, and because this is our 100% focus, our tools go well beyond what the major cloud providers provide,” he said.

Investor Mike Volpi from Index certainly sees the value proposition of this company. “One of the most critical aspects of the AI stack is in the area of performance monitoring and risk mitigation. Simply put, is the AI system behaving like it’s supposed to?” he wrote in a blog post announcing the funding.

When we spoke a year ago, the company had eight employees. Today it has 17 and it expects to double again by the end of next year. Wenchel says that as a company whose product looks for different types of bias, it’s especially important to have a diverse workforce. He says that starts with having a diverse investment team and board makeup, which he has been able to achieve, and goes from there.

“We’ve sponsored and work with groups that focus on both general sort of coding for different underrepresented groups as well as specifically AI, and that’s something that we’ll continue to do. And actually I think when we can get together for in-person events again, we will really go out there and support great organizations like AI for All and Black Girls Code,” he said. He believes that by working with these groups, it will give the startup a pipeline to underrepresented groups, which they can draw upon for hiring as the needs arise.

Wenchel says that when he can go back to the office, he wants to bring employees back, at least for part of the week for certain kinds of work that will benefit from being in the same space.

Microsoft brings new process mining features to Power Automate

Power Automate is Microsoft’s platform for streamlining repetitive workflows — you may remember it under its original name: Microsoft Flow. The market for these robotic process automation (RPA) tools is hot right now, so it’s no surprise that Microsoft, too, is doubling down on its platform. Only a few months ago, the team launched Power Automate Desktop, based on its acquisition of Softomotive, which helps users automate workflows in legacy desktop-based applications, for example. After a short time in preview, Power Automate Desktop is now generally available.

The real news today, though, is that the team is also launching a new tool, the Process Advisor, which is now in preview as part of the Power Automate platform. This new process mining tool provides users with a new collaborative environment where developers and business users can work together to create new automations.

The idea here is that business users are the ones who know exactly how a certain process works. With Process Advisor, they can now submit recordings of how they process a refund, for example, and then submit that to the developers, who are typically not experts in how these processes usually work.

What’s maybe just as important is that a system like this can identify bottlenecks in existing processes where automation can help speed up existing workflows.

Image Credits: Microsoft

“This goes back to one of the things that we always talk about for Power Platform, which, it’s a corny thing, but it’s that development is a team sport,” Charles Lamanna, Microsoft’s corporate VP for its Low Code Application Platform, told me. “That’s one of our big focuses: how to bring people to collaborate and work together who normally don’t. This is great because it actually brings together the business users who live the process each and every day with a specialist who can build the robot and do the automation.”

The way this works in the backend is that Power Automate’s tools capture exactly what the users do and click on. All this information is then uploaded to the cloud and — with just five or six recordings — Power Automate’s systems can map how the process works. For more complex workflows, or those that have a lot of branches for different edge cases, you likely want more recordings to build out these processes, though.

Image Credits: Microsoft

As Lamanna noted, building out these workflows and process maps can also help businesses better understand the ROI of these automations. “This kind of map is great to go build an automation on top of it, but it’s also great because it helps you capture the ROI of each automation you do because you’ll know for each step how long it took you,” Lamanna said. “We think that this concept of Process Advisor is probably going to be one of the most important engines of adoption for all these low-code/no-code technologies that are coming out. Basically, it can help guide you to where it’s worth spending the energy, where it’s worth training people, where it’s worth building an app, or using AI, or building a robot with our RPA like Power Automate.”

Lamanna likened this to the advent of digital advertising, which for the first time helped marketers quantify the ROI of advertising.

The new process mining capabilities in Power Automate are now available in preview.