Now valued at $5.6 billion, zero-fee stock trading app and cryptocurrency exchange Robinhood is starting preparations to go public. Just a year and a half ago, it was still largely under the radar. But then it raised a $110 million Series C at a $1.3 billion valuation in April 2017 and then just a year later scored a $363 million Series D, both led by Russian-backed firm DST Global. Combined with the growth of its premium subscription for trading on margin called Robinhood Gold, the startup now has the firepower and revenue to make a viable Wall Street debut.

Today during Robinhood CEO Baiju Bhatt’s talk at TechCrunch Disrupt SF, he revealed that his company is on the path to an IPO and has begun its search for a chief financial officer. It’s also undergoing constant audits from the SEC, FINRA and its security team to make sure everything is kosher and locked up tight.

The CFO hire could help the five-year-old Silicon Valley startup pitch itself as the cheaper youthful alternative to E*Trade and traditional stock brokers. They’d also have to convince potential investors that even though cryptocurrency prices are in a downturn, allowing people to trade them for cheaper than competitors like Coinbase is a powerful user acquisition funnel.

Robinhood now has 5 million customers tracking, buying and selling stocks, options, ETFs, American depositary slips receipts of international companies and cryptos like Bitcoin and Ethereum. That’s twice as many customers as its incumbent competitor E*Trade despite it having 4,000 employees compared to Robinhood’s 250.

The startup has raised a total of $539 million to date from prestigious investors like Andreessen Horowitz, Kleiner Perkins, Sequoia and Google’s Capital G, allowing it to rapidly roll out products before its rivals can react. This rapid rise in valuation can go to some founders’ heads, or crush them under the pressure, but Bhatt cited “friendship” with his co-CEO Vlad Tenev as what keeps him sane.

The startup has three main monetization streams. First, it earns interest on money users keep in their Robinhood account. Second, it sells order flow to stock exchanges that want more liquidity for their traders. And it sells Robinhood Gold subscriptions which range from $10 per month for $2,000 in extra buying power to $200 per month for $50,000 in margin trading, with a 5 percent APR charged for borrowing over that. Gold was growing its subscriber count at 17 percent per month earlier this year, showing the potential of giving trades away for free and then charging for extra services.

But Robinhood is also encountering renewed competition as both startups and incumbents wise up. European banking app Revolut is building a commission-free stock trading, and Y Combinator startup Titan just launched its app that lets you buy into a  managed portfolio of top stocks. Finance giant JP Morgan now gives customers 100 free trades in hopes of not being undercut by Robinhood.

Over on the crypto side, Coinbase continues to grow in popularity despite its 1.4 percent to 4 percent fees on trades. It’s rapidly expanding its product offering and the two fintech startups are destined to keep clashing. Robinhood may also be suffering from the crypto downturn, which is likely dissuading the mainstream public from dumping cash into tokens after seeing people lose fortunes as Bitcoin and Ethereum’s prices tumbled this year.

There’s also the persistent risk of a security breach that could tank Robinhood’s brand. Meanwhile, the startup uses both human and third-party software-based systems to moderate its crypto chat rooms to make sure pump and dump schemes aren’t running rampant. Bhatt says he’s proud of making cryptocurrency more accessible, though he didn’t say he felt responsible for prices plummeting, which could mean many of Robinhood Crypto’s users have lost money.

Fundamentally, Robinhood is using software to make the common but expensive behavior of stock trading much cheaper and more accessible to a wider audience. Traditional banks and brokers have big costs for offices and branches, trading execs and TV commercials. Robinhood has managed to replace much of that with a lean engineering team and viral app that grows itself. Once it finds its CFO, that could give it an efficiency and growth rate that has Wall Street seeing green.

Building a B2B AI startup is hard enough between struggling to obtain training data and fighting with major tech companies to secure talent. Building a B2B AI startup held to the well-established software-as-a-service (SaaS) metrics is even harder. While many AI businesses deliver value via software monetized by a recurring subscription like their SaaS counterparts, the similarities between the two types of businesses end there.

AI startups are a different animal

SaaS products built without data and AI offer generalized solutions to their customers. AI businesses more closely resemble a services business or consultancies because they provide solutions that become tailored to that customer’s specific needs. Like services providers or consultants, an AI product improves as it knows a customer better (as in, as it collects more data from customers with continued usage), and as it serves a broader customer base, from which it can collect best practices and make better predictions over a bigger data set.

Services revenue has been the antithesis of venture-style growth because it yields lower margins and lacks repeatability and scalability; as your services business brings on more customers, you will need to scale headcount accordingly to support those accounts, which keeps margins low. Palantir, a big data analytics unicorn, is one company mired in services demands. Unlike services providers, AI businesses have the potential to deliver that targeted and greater ROI at scale.

AI businesses are not scalable right out of the gate: AI models take time and require data to train. Moreover, not all AI businesses will scale. Here are the metrics we use to tell the difference early on.

AI metrics

Intervention ratio
Hype will make enterprise customers trigger-happy to pilot AI solutions, but at the end of the day, enterprise buyers buy the best solution available to address their problems and don’t care whether that solution comes in the form of SaaS software, a consultancy or an AI product. It is very difficult to build a high-performing MVP version of an AI model without data from customers. In order to demonstrate value right out of the box and be competitive against other vendors, you might automate which processes you can right off the bat using a rules engine, and provide a human operator to perform the rest of the work while simultaneously labeling the collecting data in order to train the AI.

As the AI improves over time, the human operator will offload more of the work and only jump in to intervene when the AI falls below a predetermined accuracy or confidence threshold. This enables you to serve an increasing number of customers with a limited number of staff. Lilt, which provides machine translation for enterprise, uses professional translators in this role. The translation AI automatically translates a text excerpt from one language to another. A human translator goes over the text looking for errors in translation or contextual corrections. As the translation AI improves, the human translator will have to make fewer corrections per translation task. More generally, the ratio of human interventions over total automated tasks should be decreasing.

ROI curve
As with SaaS products, exactly how that compounding AI performance increase is tied to bringing value for the customer is key to the startup’s long-term stickiness. The key difference with AI products is once the AI’s performance ramps up, it could very quickly exhaust all low-hanging fruit opportunities. If the AI cannot continue to provide value to the customer, the difference in value from one renewal cycle to the next may seem stark to the customer, who may decide to not renew.

Choosing the right applications of AI to enable long-term payoffs and avoiding hitting a wall with ROI is key. Typically, applications that improve the customer’s bottom line face finite opportunities for improvement, and applications that improve the customer’s top line have no ceiling on opportunities to grow. For example, once an AI improves the operating efficiency of a production line to the point where it is rate-limited by the time it takes for the raw materials to chemically react, the AI can no longer find value for the customer for that specific application.

There are only so many opportunities to take out costs before you are constrained by the laws of physics. An AI that helps customers find new opportunities for revenue like, Constructor.io, which provides AI-powered site search as a service and helps customers such as Jet.com increase cart conversions, will not hit that wall.

You should closely track the cumulative ROI for each customer over time to make sure the curve does not plateau and lead the customer to churn. Sometimes the long-term application is harder to sell because the value is difficult to demonstrate immediately, and you might get a foot in the door with the cost take-out value proposition. Understanding its ROI curve would enable you to design a longer contract period so that the AI has time to ramp on new problems before it exhausts the initial application. To ensure customer retention, you should make sure that the customer ROI increases over time and not plateau or taper off.

Rev-up costs
Deploying an AI product is a complicated process that leaves you at the mercy of each customer’s idiosyncratic tech stack and org chart. AI needs data to train, so an AI product may take more time than a SaaS product to deliver value. Acquiring or creating data for the AI model, integrating the product into the customer’s tech stack and workflows and getting the product to deliver value before the model is sufficiently trained on the customer’s data may significantly impact your own bottom line.

Many sectors have only recently begun to digitize, and valuable data might be in difficult-to-extract formats, such as handwritten notes, unstructured observation logs or PDFs. In order to capture this data, you may have to spend significant manpower on low-margin data preparation services before AI systems can be deployed. Depending on how the data is captured and organized, your deployment engineer may have to build new integrations to a data source before the model can be fully functional.

The way data is structured might also vary from one customer to the next, requiring AI engineers to spend additional hours normalizing the data or converting it to a standardized schema so the AI model can be applied. Over time, these costs may decrease as you build up a library of reusable integrations and ETL pipelines.

Products sold by SaaS companies either work or they don’t. AI performance is not binary; it works less well out of the box and improves with more data. Each application and each customer will accept a different minimum algorithmic performance (MAP). The deployment process should make sure to get the product to that customer’s specific MAP, and you might revert back to Wizard of Oz stop-gap approaches to deliver MAP until the model can perform at MAP on its own.

If you are selling to customers that allow you to pool anonymized data or use a model trained on their data with other customers, the AI product will perform better “out of the box” with each subsequent customer. Inside sales customers, for example, can get immediate suggestions on how to optimally target a sales lead using its sales acceleration platform thanks to that data pooled from its customer network.

AI products incur more significant rev-up costs than a typical SaaS product rollout and may have as much impact on margins as customer acquisition costs (CAC). You should carefully track how much time these rollouts and ramp-ups take, and how much it costs for each new customer. If there are true data network effects, these numbers should decrease over time.

Data moat
Unlike SaaS businesses that compete on new features, AI startups have an opportunity to build long-term defensibility. The AI startups that can scale will kick off a virtuous loop where the better the product performs, the more customers come on board to contribute and generate data, which improves the product’s performance. This reinforcement loop builds a compounding defensibility that was previously unheard of for SaaS businesses.

It’s too simplistic to merely aim for the largest volume of data. A defensible data strategy takes into account whether the appropriate data is being collected at a pace that is appropriate for the problem at hand. Ask yourselves these questions about your data to determine where you can strengthen your data strategy on the following dimensions:

Accessibility: how easy was it to get?Time: how quickly can the data be amassed and used in the model?Cost: how much money is needed to acquire and/or label this data?Uniqueness: is similar data widely available to others who could then build a model and achieve the same result?Dimensionality: how many different attributes are described in a data set?Breadth: how widely do the values of attributes vary, such that they may account for edge cases and rare exceptions?Perishability: will the data be useful for a long time?

AI models perform better with more data, but that performance may plateau over time. You should take care to track the time and volume of data necessary to achieve an incremental unit of value for your customer, to make sure that the data moat continues to grow. In short, how much time, and how much data, would a copycat need to match your level of performance?

SaaS metrics aren’t enough

The higher upfront work necessary to launch an AI business means that most will look more like services businesses or will appear to underperform when they are evaluated under the framework of SaaS metrics. A small subset of AI startups will resemble SaaS businesses from the beginning, before AI is deployed in the product. In order to collect data for their AI models, some businesses first sell SaaS workflow tools and can even achieve meaningful revenue from that workflow tool alone. By SaaS metrics, that company may be blowing the competition out of the water. Without the reinforcement loop generating a compounding volume of data and an increasingly powerful AI over time, however, that company’s product remains vulnerable to copycats and will eventually be commoditized.

AI metrics captures this difference. AI offers the opportunity to deliver the customized and specialized ROI of a services business with the scalability of software, with the ability to defend against copycats. The high start-up costs of this approach to company-building may mean you will realize smaller profits and build the company prioritizing different elements than what has worked before. Vertical AI is so new as a category that many companies are not yet tracking these metrics, so we don’t yet have enough data points to establish benchmarks. In the meantime, these numbers will serve as helpful barometers for you to monitor the health and performance of this new type of company.

Anshu Sharma: Every niche of a market is part of a bigger niche. Forget about software and enterprise software, because it may be hard for people to understand what I’m saying. Let’s say someone...

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MasterClass, the website that brings celebrity-taught classes to the public, like tennis lessons from Serena Williams and photography instruction from Annie Leibovitz, has raised $80 million to expand internationally.

The Series D funding, led by IVP, with participation from Javelin Ventures, NEA, Advancit Capital, Atomico and Evolution Media, will also be used to bring more celebrities to MasterClass. The company currently offers 39 classes, with plans to exceed 50 by the end of the year.

In the last year, MasterClass has added a writing class with Margaret Atwood, a comedy lesson from Judd Apatow and more. Co-founder and CEO David Rogier told TechCrunch this morning that he hopes to bring Elon Musk, LinkedIn founder Reid Hoffman and J.K. Rowling on board one day.

MasterClass’ sales more than doubled from 2016 to 2017 and are on track to do the same this year. That puts the company on pace to match Udacity and Coursera — a pair of edtech heavyweights — in revenue, according to Rogier, who would not disclose MasterClass’ financials but made the comparison. Udacity has said publicly that it increased revenue to $70 million last year, up from $29 million in 2016. Coursera, for its part, is reportedly “within striking distance of $100 million dollars in annual revenue.”

Udacity was founded in 2011 and garnered a $1 billion valuation in 2015. Coursera, founded in 2012, was valued at $800 million last year. Three-year-old MasterClass declined to disclose a valuation.

To thrust itself ahead of its competitors, MasterClass also recently rolled out a new subscription model that allows customers to pay an annual fee of $180 for access to all MasterClass lessons, which are otherwise $90 each. It’s been a huge success so far, counting for 80 percent of the company’s revenue.

On top of that, MasterClass released its first-ever mobile app this April. Before that, all the company’s growth came from desktop.

“To our investors, that was a shock and a surprise,” Rogier said. “It’s really rare and amazing that you could drive that amount of growth without being on those platforms.”

San Francisco-based MasterClass previously raised $54.5 million in venture capital funding. Rogier says they ultimately decided to raise again once they had the data to show how impactful their classes were for customers.

“One-fourth of our students say that taking these classes transformed their life,” he said.

Bumble doesn’t want you to delete your account when you get into a relationship, go on vacation or just need a break from your phone. So today it’s launching a Snooze button that lets you stop showing up to people swiping through potential matches for a day, three days, a week or indefinitely. You’ll also get to select an away message, like “I’m traveling,” “I’m on a digital detox,” “I’m focusing on work” or “I’m prioritizing myself,” that will show up with existing matches with whom you’re chatting.

The feature could ensure that Bumble’s 50 million registered users (announced today) aren’t flirting with an empty vacuum if their match goes AWOL from Bumble temporarily. And for users who turn it on, Snooze could reduce their FOMO about potentially missing out on a match or looking like they ignored someone’s message.

“The impact of social media, especially on young women, has the potential to be very harmful and we have a responsibility to give our users the power to disconnect on their own terms whenever they see fit,” writes Bumble founder and CEO Whitney Wolfe Herd. “We know Snooze will allow them to come back to us feeling refreshed and more open to new connections.”

Tinder has its own Pause button, but it’s bundled alongside the account deletion button and has less intention and flexibility behind it. You can merely turn it on or off. Without the proper away messages, matches could think you’re just trying to ghost them.

When Bumble and non-Bumble users were recently surveyed, more than 60 percent of women ages 18 to 24 said they felt overwhelmed by social media. Sixty percent of women surveyed also spend more than two hours a day on social media. Bumble’s in-house sociologist, Dr. Jessica Carbino, writes that “On social media, young women can develop unrealistic perceptions of what they should be or how others see them. These unrealistic expectations may ultimately have negative consequences for their physical and emotional well-being.”

Wolfe Herd explains that “Yes, we are absolutely social media and with that comes both healthy and unhealthy behaviors. That’s exactly why we developed snooze as a feature to give our users a break for self care on their own terms. If you don’t invest in your users, you’ll lose them.”

Dating apps are subject to high churn rates as people find long-time partners or age out of different apps. They must do everything they can to keep people on the app to both maximize the potential match pool and their chances of selling premium services to their users. Snooze feels as much like a retention trick as a benevolent offering, but if it means people can take a break from their phones in peace, it’s nice to have.

For more on Snooze and Bumble, check out its CEO’s talk today at TechCrunch Disrupt SF.

Future Family, the startup offering more affordable plans for fertility services like IVF and egg freezing, is switching its model from small loans for these services to subscriptions.

Fertility treatments are out of reach for most middle-income people in the U.S. The typical costs range from $12,000 to $20,000 for IVF, plus another few thousand for the genetic testing involved to ensure the fetus is chromosomally normal. To help, Future Family started out offering monthly payment plans for these services. However, after hearing from customers, the company has decided to switch to a subscription plan where customers can choose from several offerings and tailor a package that fits their needs.

You might be wondering what the difference is: Either you get a loan for the services you want or you sign up to pay a certain amount as a subscription for x many months for the services you want. Either way, you get the services you want with an affordable way to pay for them.

What’s new is the ability to pick the services you want, both upfront and and as you go. So, for example, if you go through egg retrieval and later realize you want to add genetic testing, you can now fold that option into your subscription plan.

“We have now moved from a financing product with concierge, to a full subscription model that offers the flexibility of other consumer subscriptions,” a spokesperson for the company told TechCrunch. “Contrast this with other financing products that have no flexibility and no customization, and do not even include services like genetic testing.”

Future Family was co-founded by former Solar City executive Claire Tomkins after she went through six rounds of IVF and spent more than $100,000 to finally get her baby, so Tomkins had some understanding of what someone might go through and how much they could rack up before seeing results.

In the past year, the company has also added male fertility testing and expanded it’s ‘Touchpoint’ fertility program to include more than 200 clinics, and it has doubled its user base in the last six months. While we don’t have firm numbers on just how many have used the company’s services, it did tell TechCrunch it has helped “tens of thousands of women, men, and couples in all 50 states.”

Subscription packages last over the course of five years and start at $150 per month for egg freezing. What you’ll get with that beginner plan is the procedure itself plus concierge care, fertility planning, clinic matching and on-boarding to the company’s digital health platform. You can see other plans for IVF on the site here.

“Subscription fertility is stress-free fertility. We want to transform people’s fertility experiences from what is currently a costly, isolating and confusing experience, to one that is affordable, easy to navigate, and supported at every step of the journey,” Tomkins said.

Yesterday was a blast, but there’s no reason to rest on our laurels. Disrupt SF 2018 Day 2 holds plenty in store for us.

We’ll hear from Priscilla Chan, Dara Khosrowshahi, Reid Hoffman, Doug Leone and many more.

First up, Dieter May from BMW with a global product announcement.

Then, this afternoon, we’ll check out the rest of the Startup Battlefield companies.

The full agenda is right here.

Enjoy!

Sramana Mitra: Given what you just said and if you’ll then look back on the deal flow that you have seen, I have a different question which is slightly off-center. Obviously we are at a time in...

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Today’s 413th FREE online 1Mby1M roundtable for entrepreneurs is starting NOW, on Thursday, September 6, at 8:00 a.m. PDT/11:00 a.m. EDT/8:30 p.m. India IST. Click here to join. All are welcome!

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Today’s 413th FREE online 1Mby1M roundtable for entrepreneurs is starting in 30 minutes, on Thursday, September 6, at 8:00 a.m. PDT/11:00 a.m. EDT/8:30 p.m. India IST. Click here to join. All...

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A market research conducted last year expects the $34.3 billion MarTech market in the US and UK to grow 10% in 2018. While the market is dominated by players like Adobe Systems, Oracle, Salesforce,...

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Sramana Mitra: Some examples in your current portfolio. Jeremy Schneider: There’s many. For example, PagerDuty is a company that we’re huge fans of and feel very lucky to work with. We met them...

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The large amounts of cash that is being invested in challenger banks in the U.K., whether that be startups with a fully fledged banking license or those using the less burdensome e-money regulations, shows no signs of abating. The latest banking fintech to raise a substantial new round is Monese.

The London and Tallinn-based company, which provides a mobile-only current account targeting customers with a ‘thin’ credit file or who are newly arrived in a country, has secured $60 million in Series B funding. Leading the round is Kinnevik, with participation from PayPal, European investor Augmentum Fintech, and International Airlines Group via its loyalty and data business Avios Group Ltd. Existing investors, including Investec’s INVC Fund, also followed on.

Launched in 2015 and claiming nearly 600,000 sign ups in the U.K. and elsewhere in Europe, Monese consists of a mobile-based current account and accompanying debit card. It offers most of the things you’d expect of a current account, such as account number and cash deposits and withdrawals. In addition, international money transfer and direct debits are supported.

It offers a free tier, with charges for some transactions, as a way of testing the water. Two monthly paid plans, starting from £4.99 per month, offer reduced or free transactions and a number of other perks.

The headline sell is that a Monese account can be opened in as little as 2 minutes, with technology driving the necessary background checks and KYC procedures. This also makes it attractive to recent migrants or other customers that don’t have a full financial history and therefore may find it more cumbersome to apply for an account with a high street bank.

In fact, as explained in a call with Monese founder Norris Koppel late yesterday afternoon, Monese wants to be the default current account option for customers with a thin credit file, from which it can offer a range of best-in-class financial services in partnership with other financial institutions, including incumbent banks and other fintechs.

That’s similar to other challenger banks and fintechs that want to become your financial control centre or hub, although in this instance Koppel is keen to stress that Monese “isn’t trying to kill banks” but wants to work with them.

Koppel also says that because the majority of Monese customers use the banking app as a primary account, including receiving salaries and paying rent, the company will be able to leverage this transaction data to help them better access credit and other financial services without solely relying on traditional credit score companies, such as Experian, which don’t have anything like the full picture.

Meanwhile, with monthly new customers tripling since the end of 2017, and Monese available in 20 European countries, Koppel tells me the watch word for this new round of funding is scale. He says the bigger vision is to have Monese the first banking option in any country a new or existing Monese customer lands in, with local account numbers instantly available.

Related, the company plans to hire an additional 100 employees across its existing U.K. and Estonian offices as well as a third new office in Portugal by the end of the year.

South Korean home cleaning service Miso wants to leave its competition in the dust after raising an $8 million Series A. Led by AddVenture, with participation from returning investors Y Combinator, FundersClub and Strong Ventures, and new backer Social Capital, the funding will be used on marketing and entering new Asian countries.

The Y Combinator alum, which was the third startup from South Korea to participate in the accelerator program, has now raised over $10.5 million in total. When TechCrunch first profiled Miso in June 2016, it was processing about 5,000 bookings a month. Now co-founder and CEO Victor Ching says the platform processes about 50,000 to 60,000 cleanings a month.

The company claims that it has processed over 750,000 bookings since it was founded in 2015 and made more than $40 million in gross merchandise value over the last three years. It has served a total of 110,000 customers and currently has 15,000 cleaners on its platform, which is accessible through mobile apps and its website.

When they launched, Miso and competitors like WaHome and Daeri Jubu represented a shift in how home cleaners work in South Korea, where demand for their services is growing thanks to the increase in dual-income households. As Ching explains to TechCrunch, cleaners previously had to pay a monthly fee to join an agency and were often required to check in at its office to wait for bookings, even though work wasn’t guaranteed. Cleaning apps give customers and cleaners more convenience and flexibility, as well as a rating system for transparency.

Ching says that when he and co-founder Haksu Lee started Miso, they assumed most cleaners would want the equivalent of full-time work, or about 30 to 40 hours a week. In reality, however, only about 30% of its providers want to work that many hours, while the rest clean on a part-time basis or to supplement their income. Full time cleaners on the platform typically earn up to about $2,000 a month (in comparison, the monthly minimum wage for full-time work in South Korea is about $1,400).

To stand out from competitors, Miso has focused on developing scale over the last two years, says Ching, who was chief product officer at food delivery startup Yogiyo before it was acquired by Delivery Hero in 2014. Ching’s experience handling food delivery logistics helped him develop Miso’s backend so that when bookings began to increase, it was able to arrange shorter commutes for cleaners. This in turn allowed the company to offer quicker bookings of about 2 to 3 hours, expanding its customer base (it initially only offered four- or eight-hour sessions). Its services also now include air conditioner and washing machine cleanings, as well as same-day bookings in some markets.

Miso’s logistics system also helps match cleaners and customers. About half of its customer base are subscribers, which mean they typically book a cleaning once a week. Most prefer to have the same person come over every week, but that means Miso needs to pair them with a cleaner who is willing to go over regularly. Miso’s platform takes into account the preferences of both customers and providers and also tries to match jobs in the same building or apartment complex with one cleaner. Ching says this is an important advantage Miso has over competitors, because its focus on convenience keeps cleaners loyal to the platform.

Estonian ride-hailing company Taxify will compete with Bird and Lime in Europe with its new brand of e-scooters, called Bolt, launching in Paris on Thursday.

The company has rolled the scooter sharing service into its mobile app, which has attracted 10 million users in 25 countries since it launched in August 2013.

A spokesperson for the company told TechCrunch it plans to release scooters in several other European and Australian cities where their app is already established, but will also launch in new markets where they’ve been unable to offer ride-hailing services because of regulatory roadblocks, including Germany and Spain.

As of now, Taxify has no plans to scoot into the US market.

“One in five Taxify rides are less than 3 km, which is the perfect distance to cover with an electric scooter,” Taxify CEO and co-founder Markus Villig said in a statement. “It’s likely that some of our ride-hailing customers will now opt for scooters for shorter distances, but we’ll also attract a whole new group of customers with different needs. This means we’ll be able to help more people with their daily transportation problems.”

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A Bolt scooter ride will cost 15 cents a minute, with a minimum fare of €1. Just like other e-scooter startups, you unlock the GPS tracked scooters by scanning the QR-code on the scooter using the Taxify app. Taxify will collect the scooters in the evenings for recharging.

Lime e-scooters went live in Paris at the end of June. About a month later, Bird’s fleet did the same, rolling into Paris and Tel Aviv as part of its international launch. GoBee Bike, Obike, Ofo and Mobike — all dockless bike providers — have also launched in Paris. GoBee has since exited after failing to compete with heavyweights like Mobike, which is owned by the multi-billion dollar Chinese company Meituan.

Taxify, for its part, is a favorite among private investors. In May, the company brought in $175 million from Daimler, Didi Chuxing and others. The financing brought the company to the $1 billion valuation mark, where it joined fellow ride-hailing giants Lyft, Uber, Careem and more in the unicorn club.

Whether e-scooters will be as popular in Europe as they’ve been in the US remains to be seen. It’s likely they’ll run into the same regulatory headaches they faced in several US cities as they continue to crop up in new markets.

Taxify, as a European company battling a pair of US-based mobility startups, may have the upper hand.

Origami Labs wants to bring voice assistants right to your ear without requiring you to wear a device like a Bluetooth headset or Apple AirPods. Instead, the startup is using a ring on your finger combined with bone conduction technology to allow you to use your smartphone’s built-in assistant – whether that’s Google Assistant or Siri – in an all-new way.

Origami Labs’ device is the Orii, a smart ring that works with an app on your phone, allowing you to physically touch your finger to your ear to either speak to or listen to your voice assistant.

This involves the use of bone conduction technology, which allows you to hear sounds through the vibration of bones in your face, bypassing the outer and middle ears to stimulate the inner ear directly.

That means you can use Orii to do things like listen to your text messages, send a WhatsApp message to a friend, take a phone call, get information like the time or weather, use reminders, or anything else that Siri or Google Assistant could do.

The ring alerts you with a vibration, then you listen (or speak to its microphone) by raising your finger to your ear.

The company presented its device on stage at TechCrunch Disrupt SF 2018 today, after winning a “wildcard” spot that allowed it to enter the Startup Battlefield competition.

The Hong Kong-based startup was founded by Marcus Leung-Shea and Kevin Wong in 2015.

Wong’s father is visually impaired, which makes using a smartphone more difficult.

“That’s where we got started – just to create a device that helps visually impaired people,” Marcus explains. “But through building the product and launching a Kickstarter, it became clear that this screen-free way of interacting with technology is something that actually a lot of people are looking for. It taps into this sense that we’re spending too much time looking at our devices,” he says.

With other Bluetooth devices, like AirPods, there’s a limit to how long they can be worn comfortably.

Plus, there’s the aesthetics to consider – not everyone wants to be seen wearing their AirPods all the time, out of a sense of style. AirPods and other Bluetooth devices in the ear are also often used as a signal others that you don’t want to be bothered.

Meanwhile, using the assistant through the speaker on the phone isn’t very private.

The startup ran crowdfunding campaigns last year to raise its initial seed round. On Kickstarter, the Orii had 4,000 backers – enough to prove there’s at least some consumer interest in this kind of product, the founders believe.

The first version of the Orii is shipping to its early backers who paid $99 to $150 for the device. It’s a bit large, in comparison to even costume rings, but that’s a solvable problem at scale. A second version of the device, shipping in Q2 2019, will be about 25 percent to 30 percent smaller, Marcus says. This one will come in different colors and enable new features. The company is also working on Alexa integration.

Orii has generated some interest from businesses and consumers. Specifically, luxury hotels and retailers want to test the product as a team communication system because they don’t want their staff looking at screens, which could come across as rude.

Mobile operators in Hong Kong, where the 14-person team is based, are also interested in selling Orii as a bundle with their phones. But all these discussions are in the early stages, Marcus notes.

Origami Labs is backed by its crowdfunding and seed investment from the Alibaba Entrepreneurs Seed Fund.

Groq has raised $52.3 million of a $60 million round, per an SEC filing. Social Capital co-founder and former Facebook executive Chamath Palihapitiya, who’s listed on the filing, has participated in the funding.

Palihapitiya confirmed Social Capital’s participation in the round to TechCrunch and said a few other undisclosed investors participated as well. Social Capital, which has been experiencing a boatload of personnel changes as of late, also led Groq’s $10 million investment in April 2017.

Groq is developing a tensor processing unit — which is an integrated circuit developed for machine learning specifically. There’s not much other info out there; the company doesn’t have much of a website or any promotional materials available for public viewing.

In addition to Palihapitiya, two other names are listed on the most recent filing. That’s the company’s CTO Jonathan Ross, who spent about five years as a hardware engineer at Google and co-founded the search giant’s Tensor Processing Unit (TPU), which is responsible for its custom ML chip.

The other name is Douglas Wightman, a former software engineer at Google. His LinkedIn profile says he’s Groq’s CEO.

Palihapitiya has spoken publicly about the project before, telling CNBC last year that he was “really excited about Groq.”

“It’s too early to talk specifics, but we think what they’re building could become a fundamental building block for the next generation of computing,” he said.

The company has reportedly poached several people from Google’s TPU team.

Vitamins are proving to be a lucrative industry in the United States. Just last year vitamin sales pulled in roughly $37 billion for the U.S. economy. That’s up from $28 billion in 2010. To cash in on this growing market, several startups have popped up in the last few years — including Nutrigene, a startup combining the vitamin business with another lucrative avenue of revenue in consumer DNA analysis.

Nutrigene believes your genes may hold the secret to what you might be missing in your diet. The company will send you tailor-made liquid vitamin supplements based on a lifestyle quiz and your DNA. You get your analysis by filling out an assessment on the startup’s website, choosing a recommended package such as “essentials,” “improve performance” or “optimize gut health.” After that you can also choose to upload your DNA profile from 23andMe, then Nutrigene will send you liquid supplements built just for you.

Founder Min FitzGerald launched the startup out of Singularity and later accepted a Google fellowship for the idea. Nutrigene then went on to Y Combinator’s winter 2018 class. FitzGerald’s co-founder and CTO Van Duesterberg comes from a biotech and epigenetics background and holds a PhD from Stanford.

PhDs and impressive resumes aside, the vitamin and genetics industries are not without controversy. For every study showing that those who eat a balanced diet don’t benefit from supplements, there are just as many highlighting the benefits of taking your vitamins. Also, coupling vitamin therapy with your DNA seems at a glance dubious. However, Dawn Barry, former VP at Illumina and now president of Luna DNA, a biotech company powered by the blockchain, says it could have some scientific underpinnings. But, she cautioned, nutrigenetics is still an early science.

Amir Trabelsi, founder of genetic analysis platform Genoox, agrees. We interviewed both Trabelsi and Barry previously when Nutrigene first came on our radar. Trabelsi pointed out these types of companies don’t need to provide any proof.

“That doesn’t mean it’s completely wrong,” he told TechCrunch. “But we don’t know enough to say this person should use Vitamin A, for example… There needs to be more trials and observation.”

Nutrigene acknowledges the best supplementation for performance goes beyond just a genetic profile. Our lifestyles, where we live, what we do and what we put in our bodies (or don’t) all can contribute to a deficiency. For better nutritional accuracy, Nutrigene will send you a blood test kit in the mail to test for things like Vitamin D deficiency (a common deficiency in Silicon Valley, according to my doctor). You also can choose to go to a blood testing center to find out what sort of nutritional supplements you’ll need for optimal performance.

One other twist — Nutrigene’s vitamins come in liquid form for what FitzGerald says is the optimum delivery method.

I tried out the program for myself earlier this year, though not for more than a few days as I was pregnant at the time and wanted to stick with the prenatal vitamins I’d been taking. Nothing I saw on the packaging from Nutrigene was dangerous for pregnant women, just run-of-the-mill stuff like vitamin B12, which my genetic analysis said I was prone to be deficient in. But I had already been taking some pretty good prenatal vitamins from New Chapter and a DHA supplement from Nordic Naturals for a year leading up to getting pregnant. I had a very healthy, nearly 9.5 pound baby boy in March. My own doctor, who tested my nutritional levels at the beginning of my pregnancy through a blood sample, did not tell me I had any deficiencies.

That’s not to say it wouldn’t be great for someone else looking for optimal nutrition and wanting a boost through supplementation. It’s also a great industry to get into if you know how to market your products. Though crowded, there’s plenty of room to grow and billions of dollars in the vitamin industry for those who can make their products stand out. DNA analysis and liquid supplementation might just be the thing.

FitzGerald tells TechCrunch that Nutrigene has already shipped 8,500 personalized dosages to customers since launching earlier this year.

For those interested in trying out Nutrigene, you can do so by ordering on the website. Package pricing varies and depends on nutritional needs, but starts at around $85 per month.

Forethought, a 2018 TechCrunch Disrupt Battlefield participant, has a modern vision for enterprise search that uses AI to surface the content that matters most in the context of work. Its first use case involves customer service, but it has a broader ambition to work across the enterprise.

The startup takes a bit of an unusual approach to search. Instead of a keyword-driven experience we are used to with Google, Forethought uses an information retrieval model driven by artificial intelligence underpinnings that they then embed directly into the workflow, company co-founder and CEO Deon Nicholas told TechCrunch. They have dubbed their answer engine “Agatha.”

Much like any search product, it begins by indexing relevant content. Nicholas says they built the search engine to be able to index millions of documents at scale very quickly. It then uses natural language processing (NLP) and natural language understanding (NLU) to read the documents as a human would.

“We don’t work on keywords. You can ask questions without keywords and using synonyms to help understand what you actually mean, we can actually pull out the correct answer [from the content] and deliver it to you,” he said.

One of first use cases where they are seeing traction in is customer support. “Our AI, Agatha for Support, integrates into a company’s help desk software, either Zendesk, Salesforce Service Cloud, and then we [read] tickets and suggest answers and relevant knowledge base articles to help close tickets more efficiently,” Nicholas explained. He claims their approach has increased agent efficiency by 20-30 percent.

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The plan is to eventually expand beyond the initial customer service use case into other areas of the enterprise and follow a similar path of indexing documents and embedding the solution into the tools that people are using to do their jobs.

When they reach beta or general release, they will operate as a cloud service where customers sign up, enter their Zendesk or Salesforce credentials (or whatever other products happen to be supported at that point) and the product begins indexing the content.

The founding team, all in their mid-20s, have had a passion for artificial intelligence since high school. In fact, Nicholas built an AI program to read his notes and quiz him on history while still in high school. Later, at the University of Waterloo, he published a paper on machine learning and had internships at Palantir, Facebook and Dropbox. His first job out of school was at Pure Storage. All these positions had a common thread of working with data and AI.

The company launched last year and they debuted Agatha in private beta four months ago. They currently have six companies participating, the first of which has been converted to a paying customer.

They have closed a pre-seed round of funding too, and although they weren’t prepared to share the amount, the investment was led by K9 Ventures. Village Global, Original Capital and other unnamed investors also participated.