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Mobile messaging financial advisory service Stackin’ adds banking features and raises cash

When Stackin’ initially pitched itself as part of the Techstars Los Angeles accelerator program two years ago, the company was a video platform for financial advice targeting a millennial audience too savvy for traditional advisory services.

Now, nearly two years later, the company has pivoted from video to text-based financial advice for its millennial audience and is offering a new spin on lead generation for digital banks.

The company has launched a new, no-fee, checking and savings account feature in partnership with Radius Bank, which offers users a 1% annual percentage yield on deposits.

And Stackin’ has raised $4 million in new cash from Experian Ventures, Dig Ventures and Cherry Tree Investments, along with supplemental commitments from new and previous investors including Social Leverage, Wavemaker Partners and Mucker Capital.

“Stackin’ has a unique and highly effective approach to connect and communicate with an entire generation of younger consumers around finance,” said Ty Taylor, group president of Global Consumer Services at Experian, in a statement.

Founded two years ago by Scott Grimes, the former founder of Uproxx Media, and Kyle Arbaugh, who served as a senior vice president at Uproxx, Stackin’ initially billed itself as the Uproxx of personal finance.

It turns out that consumers didn’t want another video platform.

“Stackin’ is fundamentally changing the shape and context of what a financial relationship means by creating a fun, inclusive and judgement free environment that empowers our users to learn and take action through messaging,” said Scott Grimes, CEO and co-founder of Stackin’, in a statement. “This funding allows us to build out new features around banking and investing that will enhance the relationship with our customers.”

Later this fall the company said it would launch a new investment feature that will encourage Stackin’ users to participate in the stock market. It’s likely that this feature will look something like the Acorns model, which encourages users to invest in diversified financial vehicles to get them acquainted with the stock market before enabling individual trades on stocks.

According to Grimes, the company made the switch from video to text in March 2018 and built a custom messaging platform on Twilio to service the company’s 500,000 users.

“In a short time, we have built a large customer base with a demographic that is typically hard to reach. Having financial institutions like Experian come on board as an investor is a testament that this model is working,” Grimes wrote in an email.

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Microsoft acquires data privacy and governance service BlueTalon

Microsoft today announced that it has acquired BlueTalon, a data privacy and governance service that helps enterprises set policies for how their employees can access their data. The service then enforces those policies across most popular data environments and provides tools for auditing policies and access, too.

Neither Microsoft nor BlueTalon disclosed the financial details of the transaction. Ahead of today’s acquisition, BlueTalon had raised about $27.4 million, according to Crunchbase. Investors include Bloomberg Beta, Maverick Ventures, Signia Venture Partners and Stanford’s StartX fund.

BlueTalon Policy Engine How it works

“The IP and talent acquired through BlueTalon brings a unique expertise at the apex of big data, security and governance,” writes Rohan Kumar, Microsoft’s corporate VP for Azure Data. “This acquisition will enhance our ability to empower enterprises across industries to digitally transform while ensuring right use of data with centralized data governance at scale through Azure.”

Unsurprisingly, the BlueTalon team will become part of the Azure Data Governance group, where the team will work on enhancing Microsoft’s capabilities around data privacy and governance. Microsoft already offers access and governance control tools for Azure, of course. As virtually all businesses become more data-centric, though, the need for centralized access controls that work across systems is only going to increase and new data privacy laws aren’t making this process easier.

“As we began exploring partnership opportunities with various hyperscale cloud providers to better serve our customers, Microsoft deeply impressed us,” BlueTalon CEO Eric Tilenius, who has clearly read his share of “our incredible journey” blog posts, explains in today’s announcement. “The Azure Data team was uniquely thoughtful and visionary when it came to data governance. We found them to be the perfect fit for us in both mission and culture. So when Microsoft asked us to join forces, we jumped at the opportunity.”

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As FTC cracks down, data ethics is now a strategic business weapon

Daniel Wu
Contributor

Dan Wu is a privacy counsel and legal engineer at Immuta. He holds a JD from Harvard University, and is a PhD candidate for Social Policy and Sociology at The Harvard Kennedy School.

Five billion dollars. That’s the apparent size of Facebook’s latest fine for violating data privacy. 

While many believe the sum is simply a slap on the wrist for a behemoth like Facebook, it’s still the largest amount the Federal Trade Commission has ever levied on a technology company. 

Facebook is clearly still reeling from Cambridge Analytica, after which trust in the company dropped 51%, searches for “delete Facebook” reached 5-year highs, and Facebook’s stock dropped 20%.

While incumbents like Facebook are struggling with their data, startups in highly-regulated, “Third Wave” industries can take advantage by using a data strategy one would least expect: ethics. Beyond complying with regulations, startups that embrace ethics look out for their customers’ best interests, cultivate long-term trust — and avoid billion dollar fines. 

To weave ethics into the very fabric of their business strategies and tech systems, startups should adopt “agile” data governance systems. Often combining law and technology, these systems will become a key weapon of data-centric Third Wave startups to beat incumbents in their field. 

Established, highly-regulated incumbents often use slow and unsystematic data compliance workflows, operated manually by armies of lawyers and technology personnel. Agile data governance systems, in contrast, simplify both these workflows and the use of cutting-edge privacy tools, allowing resource-poor startups both to protect their customers better and to improve their services.

In fact, 47% of customers are willing to switch to startups that protect their sensitive data better. Yet 80% of customers highly value more convenience and better service. 

By using agile data governance, startups can balance protection and improvement. Ultimately, they gain a strategic advantage by obtaining more data, cultivating more loyalty, and being more resilient to inevitable data mishaps. 

Agile data governance helps startups obtain more data — and create more value 

With agile data governance, startups can address their critical weakness: data scarcity. Customers share more data with startups that make data collection a feature, not a burdensome part of the user experience. Agile data governance systems simplify compliance with this data practice. 

Take Ally Bank, which the Ponemon Institute rated as one of the most privacy-protecting banks. In 2017, Ally’s deposits base grew 16%, while those of incumbents declined 4%.

One key principle to its ethical data strategy: minimizing data collection and use. Ally’s customers obtain services through a personalized website, rarely filling out long surveys. When data is requested, it’s done in small doses on the site — and always results in immediate value, such as viewing transactions. 

This is on purpose. Ally’s Chief Marketing Officer publicly calls the industry-mantra of “more data” dangerous to brands and consumers alike.

A critical tool to minimize data use is to use advanced data privacy tools like differential privacy. A favorite of organizations like Apple, differential privacy limits your data analysts’ access to summaries of data, such as averages. And by injecting noise into those summaries, differential privacy creates provable guarantees of privacy and prevents scenarios where malicious parties can reverse-engineer sensitive data. But because differential privacy uses summaries, instead of completely masking the data, companies can still draw meaning from it and improve their services. 

With tools like differential privacy, organizations move beyond governance patterns where data analysts either gain unrestricted access to sensitive data (think: Uber’s controversial “god view”) or face multiple barriers to data access. Instead, startups can use differential privacy to share and pool data safely, helping them overcome data scarcity. The most agile data governance systems allow startups to use differential privacy without code and the large engineering teams that only incumbents can afford.

Ultimately, better data means better predictions — and happier customers.

Agile data governance cultivates customer loyalty

According to Deloitte, 80% of consumers are more loyal to companies they believe protect their data. Yet far fewer leaders at established, incumbent companies — the respondents of the same survey — believed this to be true. Customers care more about their data than the leaders at incumbent companies think. 

This knowledge gap is an opportunity for startups. 

Furthermore, big enterprise companies — themselves customers of many startups — say data compliance risks prevent them from working with startups. And rightly so. Over 80% of data incidents are actually caused by errors from insiders, like third party vendors who mishandle sensitive data by sharing it with inappropriate parties. Yet over 68% of companies do not have good systems to prevent these types of errors. In fact, Facebook’s Cambridge Analytica firestorm — and resulting $5 billion fine — was sparked by third party inappropriately sharing personal data with a political consulting firm without user consent. 

As a result, many companies — both startups and incumbents — are holding a ticking time bomb of customer attrition. 

Agile data governance defuses these risks by simplifying the ethical data practices of understanding, controlling, and monitoring data at all times. With such practices, startups can prevent and correct the mishandling of sensitive data quickly.

Cognoa is a good example of a Third Wave healthcare startup adopting these three practices at a rapid pace. First, it understands where all of its sensitive health data lies by connecting all of its databases. Second, Cognoa can control all connected data sources at once from one point by using a single access-and-control layer, as opposed to relying on data silos. When this happens, employees and third parties can only access and share the sensitive data sources they’re supposed to. Finally, data queries are always monitored, allowing Cognoa to produce audit reports frequently and catch problems before they escalate out of control. 

With tools that simplify these three practices, even low-resourced startups can make sure sensitive data is tightly controlled at all times to prevent data incidents. Because key workflows are simplified, these same startups can maintain the speed of their data analytics by sharing data safely with the right parties. With better and safer data sharing across functions, startups can develop the insight necessary to cultivate a loyal fan base for the long-term.

Agile data governance can help startups survive inevitable data incidents

In 2018, Panera mistakenly shared 37 million customer records on its website and took 8 months to respond. Panera’s data incident is a taste of what’s to come: Gartner predicts that 50% of business ethics violations will stem from data incidents like these. In the era of “Big Data,” billion dollar incumbents without agile data governance will likely continue to violate data ethics. 

Given the inevitability of such incidents, startups that adopt agile data governance will likely be the most resilient companies of the future. 

Case in point: Harvard Business Review reports that the stock prices of companies without strong data governance practices drop 150% more than companies that do adopt strong practices. Despite this difference, only 10% of Fortune 500 companies actually employ the data transparency principle identified in the report. Practices include clearly disclosing data practices and giving users control over their privacy settings. 

Sure, data incidents are becoming more common. But that doesn’t mean startups don’t suffer from them. In fact, up to 60% of startups fold after a cyber attack. 

Startups can learn from WebMD, which Deloitte named as one standout in applying data transparency. With a readable privacy policy, customers know how data will be used, helping customers feel comfortable about sharing their data. More informed about the company’s practices, customers are surprised less by incidents. Surprises, BCG found, can reduce consumer spending by one-third. On a self-service platform on WebMD’s site, customers can control their privacy settings and how to share their data, further cultivating trust. 

Self-service tools like WebMD’s are part of agile data governance. These tools allow startups to simplify manual processes, like responding to customer requests to control their data. Instead, startups can focus on safely delivering value to their customers. 

Get ahead of the curve

For so long, the public seemed to care less about their data. 

That’s changing. Senior executives at major companies have been publicly interrogated for not taking data governance seriously. Some, like Facebook and Apple, are even claiming to lead with privacy. Ultimately, data privacy risks significantly rise in Third Wave industries where errors can alter access to key basic needs, such as healthcare, housing, and transportation.

While many incumbents have well-resourced legal and compliance departments, agile data governance goes beyond the “risk mitigation” missions of those functions. Agile governance means that time-consuming and error-prone workflows are streamlined so that companies serve their customers more quickly and safely.

Case in point: even after being advised by an army of lawyers, Zuckerberg’s 30,000-word Senate testimony about Cambridge Analytica included “ethics” only once, and it excluded “data governance” completely.

And even if companies do have legal departments, most don’t make their commitment to governance clear. Less than 15% of consumers say they know which companies protect their data the best. Startups can take advantage of this knowledge gap by adopting agile data governance and educate their customers about how to protect themselves in the risky world of the Third Wave.

Some incumbents may always be safe. But those in highly-regulated Third Wave industries, such as automotive, healthcare, and telecom should be worried; customers trust these incumbents the least. Startups that adopt agile data governance, however, will be trusted the most, and the time to act is now. 

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Indian PM Narendra Modi’s reelection spells more frustration for US tech giants

Amazon and Walmart’s problems in India look set to continue after Narendra Modi, the biggest force to embrace the country’s politics in decades, led his Hindu nationalist Bharatiya Janata Party to a historic landslide re-election on Thursday, reaffirming his popularity in the eyes of the world’s largest democracy.

The re-election, which gives Modi’s government another five years in power, will in many ways chart the path of India’s burgeoning startup ecosystem, as well as the local play of Silicon Valley companies that have grown increasingly wary of recent policy changes.

At stake is also the future of India’s internet, the second largest in the world. With more than 550 million internet users, the nation has emerged as one of the last great growth markets for Silicon Valley companies. Google, Facebook, and Amazon count India as one of their largest and fastest growing markets. And until late 2016, they enjoyed great dynamics with the Indian government.

But in recent years, New Delhi has ordered more internet shutdowns than ever before and puzzled many over crackdowns on sometimes legitimate websites. To top that, the government recently proposed a law that would require any intermediary — telecom operators, messaging apps, and social media services among others — with more than 5 million users to introduce a number of changes to how they operate in the nation. More on this shortly.

Growing tension

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Equity Shot: Uber’s IPO terms and Slack’s S-1

Hello and welcome back to Equity, TechCrunch’s venture capital-focused podcast, where we unpack the numbers behind the headlines.

Kate and Alex are back (again), bringing you the latest on the IPO front. As Friday is coming to a close, we’ll keep this post short to leave plenty of room for you to dig into the audio. Welcome to the weekend.

Up first we dug into Uber’s latest S-1 filing. This time, the company set a price range for itself (TechCrunch’s coverage here), valuing itself at $84 billion and also detailing estimates of its first-quarter results (Crunchbase News’s notes here).

We suspect Uber will ultimately price a top that range. Time will tell.

And then we turned to Slack, who’s direct listing will help set the historical tone for the unicorn era; screw your money, Slack says, we have our own. Well maybe not, but the company has impressive growth, killer margins, and, to our surprise, larger GAAP deficits than we expected. The company’s filing was fascinating.

But worry not, we can figure out how to value Slack. It’s Uber that left us scratching our heads. Expect next week to be another blizzard of news and numbers.

Thanks as always for listening to the show. We’ve never had more downloads than these last few weeks. It means a lot that you want to hang out with us. Don’t forget that we have an email address (equitypod@techcrunch.com), and a hashtag that Alex needs to learn to use: #equitypod.

Equity drops every Friday at 6:00 am PT, so subscribe to us on Apple PodcastsOvercast, Pocket Casts, Downcast and all the casts.

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Why Daimler moved its big data platform to the cloud

Like virtually every big enterprise company, a few years ago, the German auto giant Daimler decided to invest in its own on-premises data centers. And while those aren’t going away anytime soon, the company today announced that it has successfully moved its on-premises big data platform to Microsoft’s Azure cloud. This new platform, which the company calls eXtollo, is Daimler’s first major service to run outside of its own data centers, though it’ll probably not be the last.

As Daimler’s head of its corporate center of excellence for advanced analytics and big data Guido Vetter told me, the company started getting interested in big data about five years ago. “We invested in technology — the classical way, on-premise — and got a couple of people on it. And we were investigating what we could do with data because data is transforming our whole business as well,” he said.

By 2016, the size of the organization had grown to the point where a more formal structure was needed to enable the company to handle its data at a global scale. At the time, the buzz phrase was “data lakes” and the company started building its own in order to build out its analytics capacities.

Electric lineup, Daimler AG

“Sooner or later, we hit the limits as it’s not our core business to run these big environments,” Vetter said. “Flexibility and scalability are what you need for AI and advanced analytics and our whole operations are not set up for that. Our backend operations are set up for keeping a plant running and keeping everything safe and secure.” But in this new world of enterprise IT, companies need to be able to be flexible and experiment — and, if necessary, throw out failed experiments quickly.

So about a year and a half ago, Vetter’s team started the eXtollo project to bring all the company’s activities around advanced analytics, big data and artificial intelligence into the Azure Cloud, and just over two weeks ago, the team shut down its last on-premises servers after slowly turning on its solutions in Microsoft’s data centers in Europe, the U.S. and Asia. All in all, the actual transition between the on-premises data centers and the Azure cloud took about nine months. That may not seem fast, but for an enterprise project like this, that’s about as fast as it gets (and for a while, it fed all new data into both its on-premises data lake and Azure).

If you work for a startup, then all of this probably doesn’t seem like a big deal, but for a more traditional enterprise like Daimler, even just giving up control over the physical hardware where your data resides was a major culture change and something that took quite a bit of convincing. In the end, the solution came down to encryption.

“We needed the means to secure the data in the Microsoft data center with our own means that ensure that only we have access to the raw data and work with the data,” explained Vetter. In the end, the company decided to use the Azure Key Vault to manage and rotate its encryption keys. Indeed, Vetter noted that knowing that the company had full control over its own data was what allowed this project to move forward.

Vetter tells me the company obviously looked at Microsoft’s competitors as well, but he noted that his team didn’t find a compelling offer from other vendors in terms of functionality and the security features that it needed.

Today, Daimler’s big data unit uses tools like HD Insights and Azure Databricks, which covers more than 90 percents of the company’s current use cases. In the future, Vetter also wants to make it easier for less experienced users to use self-service tools to launch AI and analytics services.

While cost is often a factor that counts against the cloud, because renting server capacity isn’t cheap, Vetter argues that this move will actually save the company money and that storage costs, especially, are going to be cheaper in the cloud than in its on-premises data center (and chances are that Daimler, given its size and prestige as a customer, isn’t exactly paying the same rack rate that others are paying for the Azure services).

As with so many big data AI projects, predictions are the focus of much of what Daimler is doing. That may mean looking at a car’s data and error code and helping the technician diagnose an issue or doing predictive maintenance on a commercial vehicle. Interestingly, the company isn’t currently bringing to the cloud any of its own IoT data from its plants. That’s all managed in the company’s on-premises data centers because it wants to avoid the risk of having to shut down a plant because its tools lost the connection to a data center, for example.

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Humio raises $9M Series A for its real-time log analysis platform

Humio, a startup that provides a real-time log analysis platform for on-premises and cloud infrastructures, today announced that it has raised a $9 million Series A round led by Accel. It previously raised its seed round from WestHill and Trifork.

The company, which has offices in San Francisco, the U.K. and Denmark, tells me that it saw a 13x increase in its annual revenue in 2018. Current customers include Bloomberg, Microsoft and Netlify .

“We are experiencing a fundamental shift in how companies build, manage and run their systems,” said Humio CEO Geeta Schmidt. “This shift is driven by the urgency to adopt cloud-based and microservice-driven application architectures for faster development cycles, and dealing with sophisticated security threats. These customer requirements demand a next-generation logging solution that can provide live system observability and efficiently store the massive amounts of log data they are generating.”

To offer them this solution, Humio raised this round with an eye toward fulfilling the demand for its service, expanding its research and development teams and moving into more markets across the globe.

As Schmidt also noted, many organizations are rather frustrated by the log management and analytics solutions they currently have in place. “Common frustrations we hear are that legacy tools are too slow — on ingestion, searches and visualizations — with complex and costly licensing models,” she said. “Ops teams want to focus on operations — not building, running and maintaining their log management platform.”

To build this next-generation analysis tool, Humio built its own time series database engine to ingest the data, with open-source tools like Scala, Elm and Kafka in the backend. As data enters the pipeline, it’s pushed through live searches and then stored for later queries. As Humio VP of Engineering Christian Hvitved tells me, though, running ad-hoc queries is the exception, and most users only do so when they encounter bugs or a DDoS attack.

The query language used for the live filters is also pretty straightforward. That was a conscious decision, Hvitved said. “If it’s too hard, then users don’t ask the question,” he said. “We’re inspired by the Unix philosophy of using pipes, so in Humio, larger searches are built by combining smaller searches with pipes. This is very familiar to developers and operations people since it is how they are used to using their terminal.”

Humio charges its customers based on how much data they want to ingest and for how long they want to store it. Pricing starts at $200 per month for 30 days of data retention and 2 GB of ingested data.

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Forget Watson, the Red Hat acquisition may be the thing that saves IBM

With its latest $34 billion acquisition of Red Hat, IBM may have found something more elementary than “Watson” to save its flagging business.

Though the acquisition of Red Hat  is by no means a guaranteed victory for the Armonk, N.Y.-based computing company that has had more downs than ups over the five years, it seems to be a better bet for “Big Blue” than an artificial intelligence program that was always more hype than reality.

Indeed, commentators are already noting that this may be a case where IBM finally hangs up the Watson hat and returns to the enterprise software and services business that has always been its core competency (albeit one that has been weighted far more heavily on consulting services — to the detriment of the company’s business).

Also read as IBM taps out on Watson as its growth engine and returns to basics ie financial engineering and distribution https://t.co/nD7gHyYhQf

— Sunil Rawat (@_sunilrawat) October 28, 2018

Watson, the business division focused on artificial intelligence whose public claims were always more marketing than actually market-driven, has not performed as well as IBM had hoped and investors were losing their patience.

Critics — including analysts at the investment bank Jefferies (as early as one year ago) — were skeptical of Watson’s ability to deliver IBM from its business woes.

As we wrote at the time:

Jefferies pulls from an audit of a partnership between IBM Watson and MD Anderson as a case study for IBM’s broader problems scaling Watson. MD Anderson cut its ties with IBM after wasting $60 million on a Watson project that was ultimately deemed, “not ready for human investigational or clinical use.”

The MD Anderson nightmare doesn’t stand on its own. I regularly hear from startup founders in the AI space that their own financial services and biotech clients have had similar experiences working with IBM.

The narrative isn’t the product of any single malfunction, but rather the result of overhyped marketing, deficiencies in operating with deep learning and GPUs and intensive data preparation demands.

That’s not the only trouble IBM has had with Watson’s healthcare results. Earlier this year, the online medical journal Stat reported that Watson was giving clinicians recommendations for cancer treatments that were “unsafe and incorrect” — based on the training data it had received from the company’s own engineers and doctors at Sloan-Kettering who were working with the technology.

All of these woes were reflected in the company’s latest earnings call where it reported falling revenues primarily from the Cognitive Solutions business, which includes Watson’s artificial intelligence and supercomputing services. Though IBM chief financial officer pointed to “mid-to-high” single digit growth from Watson’s health business in the quarter, transaction processing software business fell by 8% and the company’s suite of hosted software services is basically an afterthought for business gravitating to Microsoft, Alphabet, and Amazon for cloud services.

To be sure, Watson is only one of the segments that IBM had been hoping to tap for its future growth; and while it was a huge investment area for the company, the company always had its eyes partly fixed on the cloud computing environment as it looked for areas of growth.

It’s this area of cloud computing where IBM hopes that Red Hat can help it gain ground.

“The acquisition of Red Hat is a game-changer. It changes everything about the cloud market,” said Ginni Rometty, IBM Chairman, President and Chief Executive Officer, in a statement announcing the acquisition. “IBM will become the world’s number-one hybrid cloud provider, offering companies the only open cloud solution that will unlock the full value of the cloud for their businesses.”

The acquisition also puts an incredible amount of marketing power behind Red Hat’s various open source services business — giving all of those IBM project managers and consultants new projects to pitch and maybe juicing open source software adoption a bit more aggressively in the enterprise.

As Red Hat chief executive Jim Whitehurst told TheStreet in September, “The big secular driver of Linux is that big data workloads run on Linux. AI workloads run on Linux. DevOps and those platforms, almost exclusively Linux,” he said. “So much of the net new workloads that are being built have an affinity for Linux.”

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Zenefits’ Parker Conrad returns with Rippling to kill HR & IT busywork

Parker Conrad likes to save time, even though it’s gotten him in trouble. The former CEO of Zenefits was pushed out of the $4.5 billion human resources startup because he built a hack that let him and employees get faster insurance certifications. But 2.5 years later, he’s back to take the busy work out of staff onboarding as well as clumsy IT services like single sign-on to enterprise apps. Today his startup Rippling launches its combined employee management system, which Conrad calls a much larger endeavor than the minimum viable product it announced while in Y Combinator’s accelerator 18 months ago.

“It’s not an HR system. It’s a level below that,” Conrad tells me. “It’s this unholy, crazy mashup of three different things.” First, it handles payroll, benefits, taxes and PTO across all 50 states. “Except Syria and North Korea, you can pay anyone in the world with Rippling,” Conrad claims. That makes it a competitor with Gusto… and Zenefits.

Second, it’s a replacement for Okta, Duo and other enterprise single-sign on security apps that authenticate staffers across partnered apps. Rippling bookmarklets make it easy to auth into over 250 workplace apps, like Gmail, Slack, Dropbox, Asana, Trello, AWS, Salesforce, GitHub and more. When an employee is hired or changes teams, a single modification to their role in Rippling automatically changes all the permissions of what they can access.

And third, it handles computer endpoint security like Jamf. When an employee is hired, Rippling can instantly ship them a computer with all the right software installed and the hard drive encrypted, or have staffers add the Rippling agent that enforces the company’s security standards. The system is designed so there’s no need for an expert IT department to manage it.

“Distributed, fragmented systems of record for employee data are secretly the cause of almost all the annoying administrative work of running a company,” Conrad explains. “If you could build this system that ties all of it together, you could eliminate all this crap work.” That’s Rippling. It’s opening up to all potential clients today, charging them a combined subscription or à la carte fees for any of the three wings of the product.

Conrad refused to say how much Rippling has raised total, citing the enhanced scrutiny Zenefits’ raises drew. But he says a Wall Street Journal report that Rippling had raised $7 million was inaccurate. “We haven’t raised any priced VC rounds. Just a bunch of seed money. We raised from Initialized Capital, almost all the early seed investors at Zenefits and a lot of individuals.” He cited Y Combinator, YC Growth Fund, YC’s founder Jessica Livingston and president Sam Altman, other YC partners, as well as DFJ and SV Angel.

“Because we were able to raise a bunch of money and court great engineers . . . we were able to spend a lot of time building this fundamental technology,” Conrad tells me. Rippling has about 50 team members now, with about 40 of them being engineers, highlighting just how thoroughly Conrad wants to eradicate manual work about work, starting with his own startup.

The CEO refused to discuss details of exactly what went down at Zenefits and whether he thought his ejection was fair. He was accused of allowing Zenefits’ insurance brokers to sell in states where they weren’t licensed, and giving some employees a macro that let them more quickly pass the online insurance certification exam. Conrad ended up paying about $534,000 in SEC fines. Zenefits laid off 430 employees, or 45 percent of its staff, and moved to selling software to small-to-medium sized businesses through a network of insurance brokers.

But when asked what he’d learned from Zenefits, Conrad looked past those troubles and instead recalled that “one of the mistakes that we made was that we did a lot stuff manually behind the scenes. When you scale up, there are these manual processes, and it’s really hard to come back later when it’s a big hard complicated thing and replace it with technology. You get upside down on margins. If you start at the beginning and never let the manual processes creep in . . . it sort of works.”

Perhaps it was trying to cut corners that got Conrad into the Zenefits mess, but now that same intention has inspired Rippling’s goal of eliminating HR and IT drudgery with an all-in-one tool.

“I think I’m someone who feels the pain of that kind of stuff particularly strongly. So that’s always been a real irritant to me, and I saw this problem. The conventional wisdom is ‘don’t build something like this, start with something much smaller,’ ” Conrad concludes. “But I knew if I didn’t do this, that no one else was gong to do it and I really wanted this system to exist. This is a company that’s all about annoying stuff and making that fucking annoying stuff go away.”

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Gamalon leverages the work of an 18th century reverend to organize unstructured enterprise data

Red and white dice casting shadows on grey surface It’s hard to fathom that the work of Reverend Thomas Bayes is still coming back to drive cutting edge advancements in AI, but that’s exactly what’s happening. DARPA-backed Gamalon is the latest carrier of the Bayesian baton, launching today with a solution to help enterprises better manage their gnarly unstructured data. The world of enterprise is full of… Read More

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