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There was a lot of money placed today, not least on health-tech. Here’s a quick round-up of funding stories for April 10.

Welltok wrangles $18.7M to make health plans better

Social health management startup Welltok has raised $18.7 million in its second round of funding with a goal of expanding into new markets, hiring new employees, and boosting product development.

Bypass catches $3.5M to help sports fans drink more beer

Bypass has raised $3.5 million to address the issue of food lines at sports games are frustrating. Getting up for a beer can mean missing an entire inning, and indulging your craving for garlic fries could result in missing the biggest play of the game, because if there is one thing in this world to be afraid of, it’s angry, thirsty sports fans.

All the details here.

Optimizely gets $28M, boasts 400% revenue growth

Web optimization startup Optimizely has closed a $28 million funding round led by Benchmark Capital. As part of the funding, Benchmark’s Peter Fenton will join the company’s board. Bain Capital Ventures, InterWest Partners, and Google Ventures participated in the round.

More details in our story.

Wandera raises $7M for mobile data optimization service for enterprises

Wandera announced it has received $7 million in funding from global venture capital firm Bessemer Venture Partners to fund its launch and global expansion. The company also announced the launch of its Mobile Data Optimization (MDO) service that helps businesses manage the explosion of mobile data usage in their organizations. Wandera’s cloud platform utilizes adaptive data compression and real-time processing to dramatically reduce a company’s mobile data usage and spend by up to 60 percent.

CompStak raises nearly $5 million from Canaan Partners

CompStak, which says it is the first-ever comprehensive database of commercial lease information, announced a $5 million Series A round of funding, led by Canaan Partners and with participation from 500 Startups, Founder Collective, and Expansion VC.

Rally Software to IPO on Friday

Rally Software is a provider of cloud-based solutions for managing Agile software development with 168,000 paid users and more than 1,000 customers, including 34 of the Fortune 100 companies. The company plans to IPO on Friday to raise $69 million at a market capitalization of $270 million.

photo credit: Matthias Rhomberg via photopin cc

A Moneyball-style revolution is taking place in venture capital.

Just as the renegade general manager of the Oakland A’s flouted assumptions about baseball and replaced gut feelings and outdated statistics with more effective quantitative analysis, a new breed of venture capital firms are throwing out their Magic 8-balls and are using computer-based models to make smarter investments.

“The bottom line is that the game has changed … and there is a lot of digital exhaust out there,” said Chris Farmer, a partner at General Catalyst, which is considered one of the more progressive of the older VC firms.

Before it pours thousands of dollars into researching a potential investment (work typically performed by a well-paid associate), a small cadre of venture firms are using analytics tools to pull in megabytes of relevant data, whether it’s a game’s performance in the various mobile app stores or conversations about a new e-commerce site on Facebook and Twitter.

Relying on instinct simply isn’t good enough anymore.

If algorithms can predict the results of elections, why not the success or failure of a tech startup? Washington D.C. woke up to the power of data when numbers-cruncher Nate Silver proved critics wrong and delivered a gut punch to traditional punditry by accurately predicting the outcome of the presidential election.

In Silicon Valley, new firms are going a step further by creating an entire investment thesis around data. “Algorithms will be the heart and soul of due diligence — it’s not just a sanity-check mechanism,” said Matt Oguz, the managing partner of new investment firm Palo Alto Venture Science. “It’s the only way to cut through human bias.”

Oguz is taking a cue from Wall Street, which has been using algorithms for years to track the rise and fall of stock, and the macro-shifts in the financial markets. According to him, it’s only a matter of time before this algorithmic approach seeps into the private investment market like osmosis.

He is one of a growing number of investors developing algorithms. Some are vocal about their research, while others are keeping it quiet to prevent competing firms from following suit.

This next generation of venture capitalists are fixated on a billion-dollar question: Can an algorithm predict whether a tech startup will succeed or fail?

Venture capital is a numbers game

I recently received an invitation to meet a partner of a leading venture capital firms at a San Francisco coffee shop. The investor popped open his laptop to reveal a snippet of a “stealth” project he’s been working on for years.

At face value, it did not appear to me much more than a series of nondescript charts and graphs. However, he explained that this is the nascent research behind an algorithm that can take much of the guesswork out of venture capital.

In response to my befuddled gaze, he traced his finger over a graph that charts the rapid ascent of Facebook. At a certain point (marked in red on the graph), the algorithm triggers an alert: Facebook has become its own market. At that point, it is wise to invest in a company that would make money by piggy-backing off the social network, like Buddy Media. This is the most basic approximation of how the data might work to his advantage — but it illustrates the point.

This investor requested to remain anonymous. He is in no rush to pass on his research to competing firms with budget to throw at the problem.

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“I want to find the next Facebook when it’s just Mark Zuckerberg.”

That statement from Kevin Rose pretty much sums up his life’s ambition these days. The Diggnation poster boy of yore is gone, and a young VC ravenous for the Next Big Thing has taken his place.

Like anyone who’s spent the majority of his adult life online and in some degree of limelight, he’s had to do a lot of maturation in the public eye, and the result of this is a thick skin and an accurate assessment of what he brings to the table.

Related: read our in-depth analysis of Google Ventures.

I’m meeting Rose in a tea shop. Tea is part of his iconography. The shop we’re meeting at even has a “Kevin Rose Collection” of the young entrepreneur’s favorite teas.

After some preliminary chatter about lapsang souchong, we settle in to talk about another aspect of Rose’s idiom: entrepreneurship, especially in the earliest stages of building a company.

Rose, as it turns out, is quite self-aware. He’s been roundly criticized in the days leading up to Digg’s sale and relaunch for any number of his failings as a chief executive and founder, and he knows his weaknesses. His strengths are closely related, and he’s aware of those, too.

Rose is great at startups, especially early-stage ones; both he and I readily acknowledge this fact. He currently works at Google Ventures, where he meets with entrepreneurs and sees new products in their first, nascent incarnations. Since the Google Ventures team has a hands-on approach to investment, Rose will also be spending lots of time working one-on-one (or one-on-several) with founders, doing what he does best: Taking a great idea and fast-tracking it, blowing it up, and turning it out.

“It’s really easy to find Series A and Series B companies that are already on a path to success, then you invest in them and double down,” he says. ”The most exciting thing to me is when it’s just in the wireframe stage. It’s just a seed of an idea, and it’s the boldest thing you can do in investing.”

While Rose gets his kicks from this most embryonic form of companies, he might not be so great at the long, monotonous haul between early, rapid development and a successful exit. The process can take years, and I don’t know many startup founders who have the patience for it (hence the Silicon Valley dictum “founders gotta found”). Even those who wait out an acquisition are off to the entrepreneurial races again as soon as humanly possible.

In Rose’s own career, one example of this difficulty is his slowly backing away from Digg. The company (and arguably Rose himself) pretty much peaked in 2008, when it fielded hefty acquisition offers and took in a nearly $30 million round of capital. But as its users revolted over and over again after product revisions, Rose left the leadership of the company in other hands and sidestepped to start something new, a mobile app shop called Milk. It’s a common theme for product-fiend founders; Twitter’s band of three (Ev Williams, Jack Dorsey, and Biz Stone) gave the keys to the company to Dick Costolo and took off to run different shows just as Twitter was getting its real-business sea legs.

But at Google, Rose’s strengths will work to his advantage, and his weaknesses will work in his favor. He’ll get to be as intellectually promiscuous (fellow Google Ventures partner Joe Kraus’s phrase) as he likes, and as an early-stage investor, he’ll only be involved in what are, for him, the most exciting parts of building a startup.

Early-stage investments are cheaper by a long shot than later-stage deals, but they also carry more risk. Rose isn’t intimidated by this in the slightest; in fact, he seems to get a rush from it. The wilder the idea, the better.

“I like the big, bold, crazy ideas,” he says. “Even if the idea doesn’t work out, when people go back and look over your portfolio, they go, ‘Wow, he’s really invested in some interesting stuff.’”

The product fiend

But on his way to making those big, wild deals, Rose has to take a ton of meetings. Today, he’s been in a string of pitch meetings and is leaving to head to more. He’s working at a frantic pace. But far from being exhausted, he seems energized by it.

“It’s this back-and-forth interactive brainstorming session between you and the entrepreneur. I just love that stuff,” he says. ”This morning I met with a startup that’s doing a dating service … a mobile app for people meeting each other. The first time I met with them, we just talked high-level about the app and the idea, what he was trying to accomplish. Three weeks later, he had a working prototype on his iPhone. He pushed it over to me and said, ‘Play with it.’”

In those early stages, Rose comes in as an experienced product lead with an eye for populist features and usable designs. He’s a fresh pair of eyes seeing for the first time an app or service that the entrepreneur has sweated over for months, or even years, in some cases.

And Rose, who, like every other product guy, has worked on his fair share of bombs, can spot a failure from a mile away — or from across a tea shop table, as the case may be. “Most likely because I personally wouldn’t use the product,” he says, “I get no internal feeling of excitement. If you notice any common theme among my investments, every single one of them is something I would use and be an advocate for. That’s the key gut call that’s always been with me.”

But he’s not just looking at apps and making product suggestions. “Sixty percent of the time, it’s product,” he says of the questions that come from entrepreneurs during these meetings. “The rest of the time, it’s little, tactical things. Terms on their convertible note, little questions. … They’re afraid to ask because it’s their first time at the rodeo.”

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Joe Kraus isn’t just a Google Ventures partner. He’s also a poker player, and I think he knows that both pursuits involve a certain amount of gambling, regardless of how much skill you think you have.

“In poker, if my analysis doesn’t agree with my gut, I’ll usually go with my gut,” he tells me in his corner office in the Google Ventures building in Mountain View.

“As an angel investor, I made a bunch of one-meeting investments based on feeling. In the venture world, that doesn’t work. … You have a gut read in your first meeting, then you do all of this analysis, and it either confirms your gut or not.”

Related: Read our in-depth interview with Google Ventures partner Kevin Rose.

In our meeting, I wouldn’t have taken Kraus for a gut-feeling risk-chaser. As he speaks, he is incredibly thoughtful and deliberate. He’ll close his eyes, take a breath, introduce a pause in the conversation. I can imagine him in a board room or at a poker table the same way — deliberate, rational, always with a balance in his hand to weigh fact, emotion, ideas, timing, circumstance, and luck. Everything, every word, is measured.

His manner is a good match for the philosophies behind Google Ventures. It has a Googley provenance of big data-meets-brain trust, and its partners operate somewhat differently than other VCs I’ve met in Silicon Valley.

Google Ventures is a separate entity from Google, Inc. It operates on the same campus but in different buildings, and while it pulls its talent and knowledge resources from the Google pool, it’s very much its own beast. The fund kicked off in 2009 with a goal of investing $100 million each year. Its known portfolio companies currently number 115; if you look for themes among them, you’ll find they range so widely across any criteria you choose that finding such themes is nearly impossible.

Aside from the Google connection, the firm and its partners are obviously different from anything else in their league in a few major ways.

For one thing, Google Ventures partners don’t really put as much emphasis on the almighty picker: the magic 8-ball in every VC’s back pocket that tells him whether or not a company is a good bet. Primarily because such a device doesn’t exist.

“Picking plays a role, don’t get me wrong. But people walk around the venture world thinking they’re such good pickers,” Kraus says. “It’s like Lake Woebegone, where everyone thinks their children are above average.

“We believe helping companies plays more of a role than most people give it credit for.”

Meet the brain trust

And when Google decides it wants to help a young tech company, the resources it puts behind the effort are mammoth.

Working on artificial intelligence? Google Ventures will likely call one of its advisors, Peter Norvig, an AI expert who used to head up computational sciences at a NASA research center. If your startup is more about energy efficiency, the firm could tap Kenneth Davies to help out; he heads up Google.org’s clean-tech work and the company’s data center energy procurement. Google Ventures also has serial entrepreneur Don Dodge on its list of advisors. It can call up the best of the best hackers, open-source activists, data scientists, you name it.

Part of that is Kraus’s fault. His wiki company, JotSpot, was acquired by Google in 2006, and by 2009 (the year Google Ventures began), he was ready to cash out and go start a new company. In fact, he had a spreadsheet of all the other Googlers he wanted to poach for his next startup.

Instead, Google convinced him to help get Google Ventures off the ground, and his dream-team spreadsheet ended up becoming his first stop for recruiting new Google Ventures team members, people he considered as the best Google had to offer in marketing, design, engineering, and so on.

We’ve all heard those great stories about well-connected angels and VCs making incredible introductions and changing the course of a young company’s fate. But that effect is multiplied many times over for Google Ventures.

“The No. 1 resource is our networks,” says Carrie Farrell, the GV team’s recruitment chief. Farrell spent the better part of a decade fine-tuning Google’s own recruitment process, and in an industry where finding and hiring engineers and designers has practically become a contact sport, she brings some of the most valuable secret sauce of all to the Google Ventures goulash.

“The value-add is immediate,” she said. Looking for a Java developer? “We can give a founder 50 Java resumes in a day.”

“Our biggest problem was recruiting,” said another Google Ventures partner, new kid on the block Kevin Rose. His last company, Milk, had closed a round of funding when it hit a hiring snag.

“We’d had an open spot for an engineer for four or five months, and we just couldn’t fill it,” the Digg founder said. “The candidate flow we got [from Google Ventures], you don’t see that at other VC firms. It was unique enough that I decided to open our round up again.”

That kind of power helps a Google-backed company hire its first five employees and then teach the founders how to hire their next 20. The Google Ventures team keeps a close eye on culture to ensure candidates are a good fit for the growing startup, while prevetting design and engineering candidates with veteran Googlers.

Farrell is just one of the all-stars working on the Google Ventures team. Adam Ghobarah is another. A stats Ph.D with a penchant for big data, his presence saves these startups from having to hire a Ph.D of their own “to tell them where the million-dollar mistakes are.”

After all, he said, “You don’t always need a Ph.D to get value out of the data. But these are complicated things, and it helps to have experience.”

Ghobarah said it’s a “dirty secret in the data community” that the quality of data in these big data sets falls apart due to the way it’s gathered by sensors, server logs, and other machines. “You end up finding patterns that aren’t really there.” But he also says that data quality and insights from the info can prevent startups from flashing in the pan, so he and his big-data cohorts work with 100 percent of the firm’s portfolio companies.

As I learn through spending more time with more Google Ventures folks, this is the firm’s method: Do a lot of hands-on, teach-a-man-to-fish work with founders; dig deep into everyone’s vast networks to get the best help that can be found; and keep pumping time and effort into the portfolio companies, willing them to succeed and generate a return for the firm.

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Chad Hurley and Steve Chen (pictured), founders of YouTube, have just received a cash infusion for their new company, AVOS.

The funding is the duo’s first institutional round, and it was led by (no surprise) Google Ventures and NEA, with participation from Madrone Capital and Chinese incubator Innovation Works. The terms of the deal were not disclosed, but we do know that AVOS will be using the money for flashy hires and strategic acquisitions.

Given that tidbit along with the team’s all-star provenance, we can say with confidence this wasn’t some small-potatoes “pity round,” but a robust injection of cash for some of the best minds in Silicon Valley.

Alex Kinnier at NEA and Gideon Yu, former YouTube CFO, Facebook CFO, and current San Francisco 49ers president, will both be joining the AVOS board. Stay tuned for more news from AVOS on the acquisitions and hiring front.

The latest product put forth by the startup is Zeen. Still a relatively stealthy project, Zeen will take consumers into the glossy, high-design world of digital magazine creation, publication, and discovery.

The AVOS team has also been working on a new version of Delicious, the beleaguered bookmarking service. The startup recently launched a Chinese version of the site, called Mei.fm.

“As their success at YouTube has clearly demonstrated, Chad and Steve have an amazing gift for connecting people to the content that matters to them,” said Google Ventures partner David Krane in a statement released this morning.

“We’re delighted to be working with the AVOS team again, and look forward to helping grow AVOS and its technology properties.”

With Humanoid developers can harness the strength of crowd-sourcing and get accurate results, not currently available from existing solutions such as Amazon’s Mechanical Turk, where people around the world can complete small tasks for payment, or outsourcing hubs like oDesk or Elance. Imagine a 20,000-person workforce at your fingertips completing tasks for $4.99 per hour.

Humanoid founder Matt Mireles wanted to build the API to solve a problem he ran into at his video-transcription company, SpeakerText. ”We launched SpeakerText, and it took us about a year and a half to get actual quality results from Mechanical Turk,” Mireles told VentureBeat. The problem, Mireles said, is that it was extremely difficult to ensure the quality of an anonymous, distributed workforce. For every dollar the team spent on labor on Mechanical Turk, it had to spend two dollars on quality assurance and cleanup. Everyone is trying to game the system, because there’s no accountability.

“Mechanical Turk is a marketplace with no sheriff,” Mireles said.

Humanoid operates like a good boss and does what bosses have done since the beginning of time, Mireles said. When someone is new, the boss pays closer attention to them and ensures that they’re producing quality work. As the quality improves, there is less need for scrutiny, and the employee can operate with more autonomy. This has never been possible before, because there wasn’t a software program focused on assuring quality.

“Businesses demand accuracy, and quality, but they can’t get it, because they have to manage the teams themselves,” Mireles said. In the case of SpeakerText, that meant hiring people to manage the quality of the work produced by the teams doing jobs from Mechanical Turk, a problem that is remarkarkably widespread.

Using statistics to predict how accurately a task will be completed based on a worker’s past performance, Humanoid is able to judge whether a worker is showing signs of fatigue, or if other factors could be interfering with the completion of a task. When these warning signs arise, the job is rerouted to another distributed worker who can meet the company’s standards, so no time is lost fixing work that is not up to snuff.

SpeakerText will live on as a feature of Humanoid and will continue to serve existing customers as needed. Mireles and team previously received funding from Mitch Kapor  and 500 Startups for SpeakerText. Humanoid has received funding from Google Ventures.