Banks aren’t as stupid as enterprise AI and fintech entrepreneurs think

Simon Moss Contributor

Simon Moss is CEO of Symphony AyasdiAI, an enterprise artificial intelligence company for financial services.

Announcements like Selina Finance’s $53 million raise and another $64.7 million raise the next day for a different banking startup spark enterprise artificial intelligence and fintech evangelists to rejoin the debate over how banks are stupid and need help or competition.

The complaint is banks are seemingly too slow to adopt fintech’s bright ideas. They don’t seem to grasp where the industry is headed. Some technologists, tired of marketing their wares to banks, have instead decided to go ahead and launch their own challenger banks.

But old-school financiers aren’t dumb. Most know the “buy versus build” choice in fintech is a false choice. The right question is almost never whether to buy software or build it internally. Instead, banks have often worked to walk the difficult but smarter path right down the middle — and that’s accelerating.

Two reasons why banks are smarter

That’s not to say banks haven’t made horrendous mistakes. Critics complain about banks spending billions trying to be software companies, creating huge IT businesses with huge redundancies in cost and longevity challenges, and investing into ineffectual innovation and “intrapreneurial” endeavors. But overall, banks know their business way better than the entrepreneurial markets that seek to influence them.

First, banks have something most technologists don’t have enough of: Banks have domain expertise. Technologists tend to discount the exchange value of domain knowledge. And that’s a mistake. So much abstract technology, without critical discussion, deep product management alignment and crisp, clear and business-usefulness, makes too much technology abstract from the material value it seeks to create.

Second, banks are not reluctant to buy because they don’t value enterprise artificial intelligence and other fintech. They’re reluctant because they value it too much. They know enterprise AI gives a competitive edge, so why should they get it from the same platform everyone else is attached to, drawing from the same data lake?

Competitiveness, differentiation, alpha, risk transparency and operational productivity will be defined by how highly productive, high-performance cognitive tools are deployed at scale in the incredibly near future. The combination of NLP, ML, AI and cloud will accelerate competitive ideation in order of magnitude. The question is, how do you own the key elements of competitiveness? It’s a tough question for many enterprises to answer.

If they get it right, banks can obtain the true value of their domain expertise and develop a differentiated edge where they don’t just float along with every other bank on someone’s platform. They can define the future of their industry and keep the value. AI is a force multiplier for business knowledge and creativity. If you don’t know your business well, you’re wasting your money. Same goes for the entrepreneur. If you can’t make your portfolio absolutely business relevant, you end up being a consulting business pretending to be a product innovator.

Who’s afraid of who?

So are banks at best cautious, and at worst afraid? They don’t want to invest in the next big thing only to have it flop. They can’t distinguish what’s real from hype in the fintech space. And that’s understandable. After all, they have spent a fortune on AI. Or have they?

It seems they have spent a fortune on stuff called AI — internal projects with not a snowball’s chance in hell to scale to the volume and concurrency demands of the firm. Or they have become enmeshed in huge consulting projects staggering toward some lofty objective that everyone knows deep down is not possible.

This perceived trepidation may or may not be good for banking, but it certainly has helped foster the new industry of the challenger bank.

Challenger banks are widely accepted to have come around because traditional banks are too stuck in the past to adopt their new ideas. Investors too easily agree. In recent weeks, American challenger banks Chime unveiled a credit card, U.S.-based Point launched and German challenger bank Vivid launched with the help of Solarisbank, a fintech company.

What’s going on behind the curtain

Traditional banks are spending resources on hiring data scientists too — sometimes in numbers that dwarf the challenger bankers. Legacy bankers want to listen to their data scientists on questions and challenges rather than pay more for an external fintech vendor to answer or solve them.

This arguably is the smart play. Traditional bankers are asking themselves why should they pay for fintech services that they can’t 100% own, or how can they buy the right bits, and retain the parts that amount to a competitive edge? They don’t want that competitive edge floating around in a data lake somewhere.

From banks’ perspective, it’s better to “fintech” internally or else there’s no competitive advantage; the business case is always compelling. The problem is a bank is not designed to stimulate creativity in design. JPMC’s COIN project is a rare and fantastically successful project. Though, this is an example of a super alignment between creative fintech and the bank being able to articulate a clear, crisp business problem — a Product Requirements Document for want of a better term. Most internal development is playing games with open source, with the shine of the alchemy wearing off as budgets are looked at hard in respect to return on investment.

A lot of people are going to talk about setting new standards in the coming years as banks onboard these services and buy new companies. Ultimately, fintech firms and banks are going to join together and make the new standard as new options in banking proliferate.

Don’t incur too much technical debt

So, there’s a danger to spending too much time learning how to do it yourself and missing the boat as everyone else moves ahead.

Engineers will tell you that untutored management can fail to steer a consistent course. The result is an accumulation of technical debt as development-level requirements keep zigzagging. Laying too much pressure on your data scientists and engineers can also lead to technical debt piling up faster. A bug or an inefficiency is left in place. New features are built as workarounds.

This is one reason why in-house-built software has a reputation for not scaling. The same problem shows up in consultant-developed software. Old problems in the system hide underneath new ones and the cracks begin to show in the new applications built on top of low-quality code.

So how to fix this? What’s the right model?

It’s a bit of a dull answer, but success comes from humility. It needs an understanding that big problems are solved with creative teams, each understanding what they bring, each being respected as equals and managed in a completely clear articulation on what needs to be solved and what success looks like.

Throw in some Stalinist project management and your probability of success goes up an order of magnitude. So, the successes of the future will see banks having fewer but way more trusted fintech partners that jointly value the intellectual property they are creating. They’ll have to respect that neither can succeed without the other. It’s a tough code to crack. But without it, banks are in trouble, and so are the entrepreneurs that seek to work with them.

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Box benefits from digital transformation as it raises its growth forecast

Box has always been a bit of an enigma for Wall Street and perhaps for enterprise software in general. Unlike vendors who shifted tools like HR, CRM or ERP to the cloud, Box has been building a way to manage content in the cloud. It’s been a little harder to understand than these other enterprise software stalwarts, but slowly but surely Box has shifted into a more efficient, and dare we say, profitable public company.

Yesterday the company filed its Q2021 earnings reports and it was solid. In fact, the company reported revenue of $192.3 million. That’s an increase of 11% year over year and it beat analyst’s expectations of $189.6 million, according to the company. Meanwhile the guidance looked good too moving from a range of $760 to $768 million for the year to a range of $767 to $770 million.

All of this points to a company that is finding its footing. Let’s not forget, Starboard Value bought a 7.5% stake in the company a year ago, yet the activist investor has mostly stayed quiet and Box seems to be rewarding its patience as the pandemic acts as a forcing function to move customers to the cloud faster– and that seems to be working in Box’s favor.

Let’s get profitable

Box CEO Aaron Levie has not been shy about talking about how the pandemic has pushed companies to move to the cloud much more quickly than they probably would have. He said as a digital company, he was able to move his employees to work from home and remain efficient because of tools like Slack, Zoom, Okta, and yes, Box were in place to help them do that.

All of that helped keep the business going, and even thriving, through the extremely difficult times the pandemic has wrought. “We’re fortunate about how we’ve been able to execute in this environment. It helps that we’re 100% SaaS, and we’ve got a great digital engine to perform the business,” he said.

He added, “And at the same time, as we’ve talked about, we’ve been driving greater profitability. So the efficiency of the businesses has also improved dramatically, and the result was that overall we had a very strong quarter with better growth than expected and better profitability than expected. As a result, we were able to raise our targets on both revenue growth and profitability for the rest of the year,” Levie told TechCrunch.

Let’s get digital

Box is seeing existing customers and new customers alike moving more rapidly to the cloud, and that’s working in its favor. Levie believes that companies are in the process of reassessing their short and longer term digital strategy right now, and looking at what workloads they’ll be moving to the cloud, whether that’s cloud infrastructure, security in the cloud or content.

“Really customers are going to be trying to find a way to be able to shift their most important data and their most important content to the cloud, and that’s what we’re seeing play out within our customer base,” Levie said.

He added,”It’s not really a question anymore if you’re going to go to the cloud, it’s which cloud are you going to go to. And we’ve obviously been very focused on trying to build that leading platform for companies that want to be able to move their data to a cloud environment and be able to manage it securely, drive workflows on it, integrate it across our applications and that’s what we’re seeing,” he said.

That translated into a 60% increase quarter over quarter on the number of large deals over $100,000, and the company crossed 100,000 customers globally on the platform in the most recent quarter, so the approach seems to be working.

Let’s keep building

As with Salesforce a generation earlier, Box decided to build its product set on a platform of services. It enabled customers to tap into these base services like encryption, workflow and metadata and build their own customizations or even fully functional applications by taking advantage of the tools that Box has already built.

Much like Salesforce president and COO Bret Taylor told TechCrunch recently, that platform approach has been an integral part of its success, and Levie sees it similarly for Box. calling it fundamental to his company’s success, as well.

“We would not be here without that platform strategy,” he said. “Because we think about Box as a platform architecture, and we’ve built more and more capabilities into that platform, that’s what is giving us this strategic advantage right now,” he said.

And that hasn’t just worked to help customers using Box, it also helps Box itself to develop new capabilities more rapidly, something that has been absolutely essential during this pandemic when the company has had to react quickly to rapidly changing customer requirements.

Levie is 15 years into his tenure as CEO of Box, but he still sees a company and a market that is just getting started. “The opportunity is only bigger, and it’s more addressable by our product and platform today than it has been at any point in our history. So I think we’re still in the very early stages of digital transformation, and we’re in the earliest stages for how document and content management works in this modern era.”

Aaron Levie: ‘We have way too many manual processes in businesses’

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Will automation eliminate data science positions?

Michael Li Contributor

Tianhui Michael Li is founder of The Data Incubator, an eight-week fellowship to help PhDs and postdocs transition from academia into industry. Previously, he headed monetization data science at Foursquare and has worked at Google, Andreessen Horowitz, J.P. Morgan and D.E. Shaw.

More posts by this contributor

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“Will automation eliminate data science positions?”

This is a question I’m asked at almost every conference I attend, and it usually comes from someone from one of two groups with a vested interest in the answer: The first is current or aspiring practitioners who are wondering about their future employment prospects. The second consists of executives and managers who are just starting on their data science journey.

They have often just heard that Target can determine whether a customer is pregnant from her shopping patterns and are hoping for similarly powerful tools for their data. And they have heard the latest automated-AI vendor pitch that promises to deliver what Target did (and more!) without data scientists. We argue that automation and better data science tooling will not eliminate or even reduce data science positions (including use cases like the Target story). It creates more of them!

Here’s why.

What’s different about hiring data scientists in 2020?

Understanding the business problem is the biggest challenge

The most important question in data science is not which machine learning algorithm to choose or even how to clean your data. It is the questions you need to ask before even one line of code is written: What data do you choose and what questions do you choose to ask of that data?

What is missing (or wishfully assumed) from the popular imagination is the ingenuity, creativity and business understanding that goes into those tasks. Why do we care if our customers are pregnant? Target’s data scientists had built upon substantial earlier work to understand why this was a lucrative customer demographic primed to switch retailers. Which datasets are available and how can we pose scientifically testable questions of those datasets?

Target’s data science team happened to have baby registry data tied to purchasing history and knew how to tie that to customer spending. How do we measure success? Formulating nontechnical requirements into technical questions that can be answered with data is amongst the most challenging data science tasks — and probably the hardest to do well. Without experienced humans to formulate these questions, we would not be able to even start on the journey of data science.

Making your assumptions

After formulating a data science question, data scientists need to outline their assumptions. This often manifests itself in the form of data munging, data cleaning and feature engineering. Real-world data are notoriously dirty and many assumptions have to be made to bridge the gap between the data we have and the business or policy questions we are seeking to address. These assumptions are also highly dependent on real-world knowledge and business context.

In the Target example, data scientists had to make assumptions about proxy variables for pregnancy, realistic time frame of their analyses and appropriate control groups for accurate comparison. They almost certainly had to make realistic assumptions that allowed them to throw out extraneous data and correctly normalize features. All of this work depends critically on human judgment. Removing the human from the loop can be dangerous as we have seen with the recent spate of bias-in-machine-learning incidents. It is perhaps no coincidence that many of them revolve around deep learning algorithms that make some of the strongest claims to do away with feature engineering.

So while parts of core machine learning are automated (in fact, we even teach some of the ways to automate those workflows), the data munging, data cleaning and feature engineering (which comprises 90% of the real work in data science) cannot be safely automated away.

A historical analogy

There is a clear precedent in history to suggest data science will not be automated away. There is another field where highly trained humans are crafting code to make computers perform amazing feats. These humans are paid a significant premium over others who are not trained in this field and (perhaps not surprisingly) there are education programs specializing in training this skill. The resulting economic pressure to automate this field is equally, if not more, intense. This field is software engineering.

Indeed, as software engineering has become easier, the demand for programmers has only grown. This paradox — that automation increases productivity, driving down prices and ultimately driving up demand is not new — we’ve seen it again and again in fields ranging from software engineering to financial analysis to accounting. Data science is no exception and automation will likely drive up demand for this skillset, not down.

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The H-1B visa ban is creating nearshore business partnership opportunities

Andrés Vior Contributor

Andrés Vior is the VP and country manager for Argentina at intive. A computer engineer who graduated from the University of Buenos Aires (UBA), he is also a member of the Chamber of Software and Computer Services Companies of Argentina (CESSI).

In June, President Donald Trump signed an executive order temporarily suspending work visas for H-1B holders, which includes skilled workers like software developers.

Considering that 71% of workers in Silicon Valley and other tech hubs are international, the order poses a number of logistical and business challenges for startups.

While nearshoring was an option before the virus struck, the urgency to nearshore due to the visa ban, combined with the remote revolution taking place, has meant companies are reconsidering it as a solution. As a result, the suspension presents an opportunity for companies to bring on board software development capabilities from abroad.

Nearshoring is a way to hire teams in locations that share similar time zones and are easily accessible. Nearshoring also enables U.S. companies to utilize services from close locations, where the talent, working conditions, and salaries are more favorable. In fact, it can save businesses up to 80% on costs, while providing employees with flexibility, autonomy and better career development pathways.

Not only is nearshoring a pragmatic response to the visa ban, it has the potential to be a long-term hiring alternative for businesses. Here’s how:

Laying the groundwork for remote teams

Amid the pandemic, demand for developers has remained high, no doubt due to companies needing teams to build, maintain and optimize digital platforms as they transition to online services. The visa ban means that businesses in foreign markets can help meet such demand, particularly as tech talent from other countries comes with a fresh, different skill set that empowers companies to solve problems in new ways.

In the past, moving to the U.S. and living the American Dream oriented many foreign businesses’ professional paths. However, the trend has changed. The appeal of the United States was slipping prior to the virus — it ranked 46th out of 66 for “perceived friendliest to expats” — and post-COVID-19 may be even more detrimental.

In a more connected world, businesses and individuals can reap the benefits of U.S. opportunities — top technology stack, access to exciting companies and world-class research — without having to actually live in the country. In this respect, nearshoring means foreign teams have the best of both worlds: the comfort of home and ties to an international powerhouse.

The remote shift is demonstrating that teams can function well at a distance; some studies have even revealed that employee productivity and happiness benefit from remote work. In the global remote shift, nearshoring is being seen as an accepted and advantageous model. Companies that opt to nearshore in response to the visa ban can take advantage of the changing tides and use this time to lay the groundwork for best practices within remote teams. For instance, by devising policies for things like communication, tracking progress, vacation and development plans according to the new conditions and specific mission statements. As a result, businesses can seamlessly build professional partnerships.

Another advantage of nearshoring is that the flexible teams contribute to a ready-to-scale model for startups. By having development partners located in different countries, companies can network on a wider level and grow faster among local markets. Rather than start from scratch when expanding, nearshoring gives companies a presence — no matter how small — across regions, which can later be built upon.

Attracting fresh investment

Similar to having a readiness to scale, the H-1B visa suspension positions nearshoring as a viable way to strategically partner with foreign development studios. In contrast to offshoring, nearshored businesses are often more vested in the projects they work on because they share time zones and are thus able to work more closely and with greater agility. Within startups, such agility is essential to continuously test, iterate and pivot products or services. Outsourced teams often have defined outputs to achieve, while freelancers are split across several projects, so aren’t completely ingrained in companies’ visions.

With nearshoring, startups can target partners that have experience in a particular area of business or with a specific tech feature and accelerate their time to market. Instead of building systems from zero, they can launch into version 2.0 because the wider choice of experts means there’s a higher chance of partnering with teams who already understand how the industry functions. Nearshore partners also have vast knowledge across industrial fields at a level that is impossible for direct hires to have. Companies therefore don’t have to tackle the difficulty of curating a great team, because nearshore partners are an already solid pairing.

When it comes to funding, this synchronicity, agility and preparedness indicates that a startup has momentum. For investors, nearshoring shows that the company has on-the-ground insights about potential markets to disrupt, and that the business model can thrive using remote teams. As the world braces itself to go fully digital, startups that have already adopted remote processes that catalyze growth will no doubt catch the attention of investors.

Promoting greater diversity in teams

Latin America is a clear choice for U.S. businesses looking to nearshore. The region’s proximity, increasing internet penetration, and impressive number of highly skilled developers are all a significant draw.

It’s also worth noting that diversity plays a core role in nearshoring. Currently within tech, Hispanic workers are noticeably underrepresented, making up a mere 16.7% of jobs. Despite the physical distance, nearshoring in Latin America can bring people from different social and economic backgrounds into companies, boosting their visibility in industries as a whole, and setting a firm foundation for equality.

Studies also show that diversity influences creativity among teams, as well as increases company revenue.

Moreover, nearshoring accelerates diversity in a manner that isn’t disruptive. Foreign team members don’t have to sacrifice their home, friends and family to further their professional career. Relocating to the U.S. can be daunting for people who haven’t previously worked abroad, especially when factoring the change in living costs and new culture norms. Nearshoring means teams can work from locations they’re familiar with, so need less time to get up to speed on business processes. They additionally have the emotional support of their social circles nearby, which in the current climate is important for employees’ personal and professional wellbeing.

Leveraging the right partnership

Research is key to successfully find a nearshore company, and startups don’t always have the time and resources to conduct an in-depth analysis of locations and their ecosystems. The most practical manner to nearshore the right talent is with a nearshoring partner that is responsible for scouting, vetting and communicating with foreign developers.

To find an appropriate partner, ensure that they have previous experience in your industry and positive testimonials from startups in your location. They should also have a clear presence in the regions they operate in; try checking online for their press releases, events they sponsor and general content that validates they are active and respected.

Once you’ve found an appropriate nearshore partner, rely on them to know what teams in your preferred locations need in terms of culture. Nearshore partners will essentially be your development partner — you can leverage them to be your whole Research and Development department. They can guide you on the tech side of your business, advise you on the right team at the right time, give you direction on stack and methodology, and curate the right environment for the team to be productive. In contrast, hiring freelancers comes with risks because you won’t necessarily know the specific needs of the location they’re in. Be aware — if there’s a cultural disconnect, you risk not finding a partner, but a vendor that’s buying into a superficial version of your startup, as opposed to your real startup vision.

Once you’ve settled on a well-fitting nearshoring partner, ensure you have detailed contracts with all team members, as well as nondisclosure agreements. Nearshoring requires a level of mutual trust, however, at such an early stage of your company’s lifecycle, you need to know that your processes and data will not be revealed to competitors. Check that your nearshore partner’s financial status is secure and sufficient for a long-term model. Correspondingly, service level agreements will set the parameters for job responsibilities and deliverables. After all the formalities are covered, you can focus on curating fruitful, long-term relationships.

Acclimatizing in the new normal

The COVID-19 crisis has made recruitment a remote-dominated sphere. Traditional modes of hiring are being reassessed, and companies are realizing that teams don’t have to be in an office to be productive. In fact, not having to cover visa and administration fees for foreign employees is much more cost-effective for companies.

As time passes and businesses develop habits best-suited to remote work, nearshoring will become increasingly popular. People are prioritizing joining teams where their career development, well-being and ethics are protected, all of which nearshoring can offer with the added benefit of not completely upheaving workers’ lives.

Startups who embrace nearshoring early on could find themselves competing with top tech firms that struggle because of recruiting limitations. With the end of the pandemic unknown, and thus no hard deadline for the visa ban, tech companies have to look at alternative modes of building teams. Startups have the advantage of revising their remote product development approach without disturbing workflows too severely. They are also known for pioneering fairer and more innovative workplaces that are enticing for a broader scope of employees.

Nearshoring is mutually beneficial because developers don’t have to give up their culture for a great employment opportunity, and businesses can reap the benefits of diversification. Ultimately, the H-1B visa suspension could stimulate true globalization in tech, where companies can achieve their best performance using global resources.

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Muze redesigns mobile messaging as a free-form canvas for creativity

New York-based startup Muze is rethinking mobile messaging. While today’s messaging apps have expanded over the years to include support for sharing photos and videos, voice messages, reactions and more, Muze has fully redesigned the traditional messaging experience as a blank canvas, allowing for more creative interactions. The company’s new mobile app on iOS allows users to add text, pin their photos and GIFs, zoom in and out on content and even draw on the messaging canvas itself using different pen sizes and colors, among other things.

The end result looks nothing like your standard messaging conversation, where back-and-forth chat bubbles are interspersed with the occasional photo, video or link. Instead, a chat in Muze looks like some sort of collaborative art project — a collage of ideas, a meme board or perhaps a sketchpad, depending on how you use the app.

Despite offering a jumble of new features, Muze itself is simple to get started with and fairly easy to use, as well.

Image Credits: Muze, via Apple’s App Store

After signing up for an account on Muze and optionally syncing your contacts, you’re first presented with what otherwise appears to be a fairly typical messaging interface. There’s a text box to type in and buttons that let you quickly access your iPhone Camera or your phone’s photo gallery to add media to your chat.

To the right, you’ll notice a pen icon, as well — the first visual hint that Muze may be doing things differently.

Image Credits: Muze, screenshot via TechCrunch

But as you dig into the features, you realize Muze offers more ways to interact. For instance, when you tap the photo gallery icon, you’ll discover Muze doesn’t only offer access to your own media — you can also search for photos, add GIFs from Giphy or grab one of dozens of custom stickers. These include stickers that let you frame the text, react to messages and decorate the screen, as well as a set of emoji mashups — like a pleading faced-emoji, surrounded by hearts, making the “But I’m Shy” symbol with its fingers (it’s a TikTok thing). The TikTok-favored Eye Mouth Eye emoji set is also plastered across a yellow smiley with open arms and tiny feet.

When you tap into the text box to begin typing, you’re presented with more of Muze’s expanded features. From here, you can tap buttons to change the font, text color or the alignment, or turn on the highlight color (the “bubble” color).

When you’re ready to enter the text, you can drag and drop the chat bubble anywhere on the screen, or make it larger or smaller. You can stick it over the top an image and so on.

The pen, meanwhile, lets you draw on anything on the screen — not just the blank canvas itself, but also on top of text, images, stickers or whatever else you’ve used to decorate your chat.

Image Credits: Muze

There’s only a slight learning curve to the app. For example, when you tap on the pen icon from the main chat screen, you may want to be able to draw underneath the current chat in a blank area of the canvas. But if you try to scroll down, you end up drawing on the screen, much to your surprise. To actually draw beneath the existing chat, you have to instead tap into the text box first, then tap a different pen icon that appears in the gray iOS toolbar. Of course, kids who can manage complex TikTok edits won’t struggle with these sorts of quirks.

Image Credits: Muze

The app has a few other modern features, as well, like the ability to change the app icon from one of several it includes, for example. It also gives you the ability to theme the app not just with light or dark colors, as is now common, but also in shades like millennial pink, mint green, dark teal, forest green, purple and light blue.

Combined, its feature set delivers an app that has a lot of youth appeal — which makes sense, as Muze itself was designed by younger people who are used to communicating online with memes, GIFs and other creative content. Currently, Muze’s co-founders include Douglas Witte, Willem Simons and Grant Davis. Fenner Stevens is Muze’s CEO.

Though new to the market, Muze has already attracted the interest of investors. According to Crunchbase and SEC filings from 2019-2020, Muze has raised around $7 million in outside capital, including both equity and debt. On its AngelList profile, Muze’s backers include Sequoia Capital, Tribe Capital, Maveron, True Ventures, Grand Central Tech, Village Global and Hiten Shah. We understand a handful of other smaller funds and angels have also backed Muze.

The team at Muze declined to be interviewed about their plans for the business going forward, but confirmed the funding. The app is live on the App Store as a free download.

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Our 11 favorite companies from Y Combinator’s S20 Demo Day: Part I

Startup incubator and investment group Y Combinator today held the first of two demo days for founders in its Summer 2020 batch.

So far, this cohort contains the usual mix of bold, impressive and, at times, slightly wacky ideas young companies so often show off.

This was Y Combinator’s second online demo day, its first all-virtual class and the first time that it held live, remote pitches. The event largely went well, with founders dialing in from around the globe to share a few paragraphs of notes and a single slide. There were few technical hiccups, given the sheer number of startups presenting.

But if you are not in the mood to parse through dozens (and dozens) of entries detailing each startup that showed off its problem, solution and growth, the TechCrunch crew has collected our own favorites based on how likely a company seems to succeed and how impressed we were with the creativity of their vision. For each entry, one staffer made the call that the startup in question was among their favorites.

We’re not investors, so we’re not pretending to sort the unicorns from the goats. But if what you need is a digest of some of the day’s best companies to get a good taste of what founders are building, we have your back.

ZipSchool and Hellosaurus

Natasha Mascarenhas

The next wave of edtech startups is entering a market that demands a better remote-learning solution for younger learners. But that’s the obvious product gap, one that is already being tackled by the biggest names in the booming category.

The non-obvious product-market deficit is how teachers, also impacted by the pandemic, are searching for new ways to interact with students. Teachers are collaborating and cross-pollinating on successful lesson plans that work across stale Zoom screens, so why not monetize that same content?

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Restaurant rewards booking app Seated nabs $30M, acquires VenueBook to add events

The restaurant industry has been slammed hard by the coronavirus outbreak, with venues in many cities in the US and beyond shuttered or restricted in how they can serve customers — to say nothing of the comfort level of customers themselves to dine in public venues — in the name of helping contain the spread of infections. But today, a startup that has built a platform to help them manage their bookings business better is announcing a round of funding and an acquisition to help those restauranteurs on the road to recovery.

Seated, which provides a restaurant booking platform that rewards customers with credits for gift cards at selected other retailers like Amazon, Nike, Sephora and Uber when they show up to eat, has raised $30 million in funding, and alongside that it is also announcing that it has acquired another industry startup, VenueBook, a platform for event planners to reserve space at restaurants and other venues. Today VenueBook has some 120,000 event planners using its service across the New York tristate area, Denver, San Francisco and the surrounding Bay Area, and the wider Washington, D.C. region.

The terms of the deal are not being disclosed, nor is the valuation of Seated. The funding is being led by Insight Partners and Craft Ventures, Greycroft (where Seated’s co-founder and executive chairman Bo Peabody is also a venture partner) and Rho Capital Partners are also participating. This appears to be the first funding disclosed by Seated since being founded in 2017 by Peabody and Brice Gumpel, although it had previously raised a seed round.

New York-based Seated had its start in the world of booking tables for in-restaurant eating — a business that has to date racked up some 900,000 reserved seats and $37 million in revenue for its restaurant partners across NYC, Boston, Atlanta and Chicago (covering around 800 independent restaurants in all at the moment), with some additional $7 million in tips for staff.

But in recent months it’s been recalibrating what it does to meet the needs of the moment, which include diversifying beyond providing reservations to in-restaurant individual diners. That’s included the launch of Seated at Home, a takeout service that is positioned as a competitor to the likes of GrubHub and UberEats with a 0% commission on orders. And now, the acquisition of VenueBook adds an event planning service into the mix that takes its booking platform beyond the walls of local eateries.

“We are always looking for new ways to support restaurants’ profitability and longevity, and with the acquisition of VenueBook, Seated Events offers a new way for restaurants to drive demand in yet another revenue stream,” said Gumpel, who is the startup’s CEO, in a statement. “COVID-19 has proved to be one of the toughest challenges the restaurant industry has ever faced and this funding will help us refine our current products to ensure we’re doing whatever we can to help our restaurant partners keep their doors open and remain profitable.”

In terms of just how hard restaurants have been hit, the statistics speak for themselves. Researchers from Harvard Business School noted in a recent essay that 40% of restaurants in the US shuttered two months into the pandemic, putting 8 million people out of work, three times more job losses than any other industry.

And when some started to reopen, they were facing major investments as they retooled their businesses to cater to how people are “eating out” now — significantly more takeout and delivery, and a lot of eating outdoors. Even so, diner numbers in June were down more than 65% versus a year ago, with the National Restaurant Association in the US predicting a drop of $240 billion in revenue for the year, with more than $120 billion during the first three months of the COVID-19 pandemic alone.

Some countries are trying to offset this huge hit: in the UK, the government has started its “Eat Out to Help Out” scheme, which essentially subsidises the cost of meals by up to 50% when people eat out at participating restaurants.

That’s not the case in the US at large, however, with federal government relief programs like the Paycheck Protection Program targeted across industry verticals.

That has opened an opportunity for startups that are building tech to at least make what business opportunities are available more accessible to a wider number of users at both ends of its two-sided marketplace, those looking to eat out or meet in restaurants, and the restaurants (and now, other venues) themselves.

The tech is about measuring footfall, providing analytics and more insights into how to fill venues and kitchen utilisation in a more efficient way, but that is at the backend. On the surface, the startup makes a point of touting how low-tech it is, requiring little more than a smartphone to use it. That sets it apart from a number of other restaurant service startups, which often sell specific tablets and other hardware to be able to use their software.

Indeed, the restaurant business is not known for being high-tech — one reason why you might argue many get taken for a ride by delivery and other startups that promise to handle all the fussy tech stuff on their behalf. So in an industry where typically profits are no more than 4-5% of revenue (and those are the lucky ones), the shift into events is a critical way of improving margins at a time when restaurants’ prime revenue generation has been pulled out from under them. Events are estimated to make up 10-15% of a restaurant’s revenue, and up to 20% of a restaurant’s profit, Seated notes. , Seated Events provides a seamless way for restaurants to begin rebuilding this critical revenue stream, allowing families or smaller groups of people who would like to take extra precautions while dining out to book private rooms.

“Events are not only an important part of a restaurant’s revenue stream, but they’re important for internal operations. Restaurant events help to increase employee retention because both front and back of the house employees are able to exercise creativity and tap into different skill sets while planning and executing events,” said Peabody in a statement (Peabody himself also owned and been on the boards of a number of restaurant businesses, in a long entrepreneurial career that has also included founding Tripod — a verrrry early social network sold to Lycos in 1997 and being the founding chairman of Everyday Health, which was sold to Ziff Davis). “We are thrilled to be able to offer yet another way for restaurants to maximize their profitability. With Seated Events, Seated at Home, and Seated, restaurants can drive demand to their three primary sources of revenue in a single, easy to use rewards platform.”

All this means that even at a time when restaurants feel like a risky bet, investors are interested:

“Restaurants are a vital part of our culture and communities, and the industry has been completely upended by COVID-19. It’s been impressive to watch Seated’s unwavering commitment to help restaurants thrive as they quickly adapted their rewards platform to offer delivery, and now events, in order to continue to meet restaurants’ needs,” said Thilo Semmelbauer, Managing Director at Insight Partners, in a statement. “Seated’s expanded vision is compelling and this one-stop platform will be an important piece of the restaurant industry’s recovery and evolution.”

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Deepfake video app Reface is just getting started on shapeshifting selfie culture

A bearded Rihanna gyrates and sings about shining bright like a diamond. A female Jack Sparrow looks like she’d be a right laugh over a pint. The cartoon contours of The Incredible Hulk lend envious tint to Donald Trump’s awfully familiar cheek bumps.

Selfie culture has a fancy new digital looking glass: Reface (previously Doublicat) is an app that uses AI-powered deepfake technology to let users try on another face/form for size. Aka “face swap videos”, in its marketing parlance.

Deepfake technology — or synthesized media, to give it its less pejorative label — is just getting into its creative stride, according to Roman Mogylnyi, CEO and co-founder of RefaceAI, which makes the eponymous app whose creepily lifelike output you may have noticed bubbling up in your social streams in recent months.

The startup has Ukrainian founders — as well as Mogylnyi, there’s Oles Petriv, Yaroslav Boiko, Dima Shvets, Denis Dmitrenko, Ivan Altsybieiev and Kyle Sygyda — but the business is incorporated in the US. Doubtless it helps to be nearer to Hollywood studios whose video clips power many of the available face swaps. (Want to see Titanic‘s Rose Hall recast with Trump’s visage staring out of Kate Winslet’s body? No we didn’t either — but once you’ve hit the button it’s horribly hard to unsee… )

TechCrunch noticed a bunch of male friends WhatsApp-group-sharing video clips of themselves as scantily clad female singers and figured the developers must be onto something — a la Face App, or the earlier selfie trend of style transfer (a craze that was sparked by Prisma and cloned mercilessly by tech giants).

Reface’s deepfake effects are powered by a class of machine learning frameworks known as GANs (generative adversarial network) which is how it’s able to get such relatively slick results, per Mogylnyi. In a nutshell it’s generating a new animated face using the twin inputs (the selfie and the target video), rather than trying to mask one on top of the other.

Deepface technology has of course been around for a number of years, at this point, but the Reface team’s focus is on making the tech accessible and easy to use — serving it up as a push-button smartphone app with no need for more powerful hardware and near instant transformation from a single selfie snap. (It says it turns selfies into face vectors representing distinguishing user’s facial features — and pledges that uploaded photos are removed from its Google Cloud platform “within an hour”.)

No need for tech expertise nor lots of effort to achieve a lifelike effect. The inexorable social shares flowing from such a user friendly tech application then work to chalk off product marketing.

It was a similar story with the AI tech underpinning Prisma — which left that app open to merciless cloning, though it was initially only transforming photos. But Mogylnyi believes the team behind the video face swaps has enough of a head (ha!) start to avoid a similar fate.

He says usage of Reface has been growing “really fast” since it added high res videos this June — having initially launched with only far grainier GIF face swaps on offer.  In terms of metrics the startup us not disclosing active monthly users but says it’s had around 20 million downloads at this point across 100 countries. (On Google Play the app has almost a full five star rating, off of approaching 150k reviews.)

“I understand that an interest from huge companies might come. And it’s obvious. They see that it’s a great thing — personalization is the next trend, and they are all moving in the same direction, with Bitmoji, Memoji, all that stuff — but we see personalized, hyperrealistic face swapping as the next big thing,” Mogylnyi tells TechCrunch.

“Even for [tech giants] it takes time to create such a technology. Even speaking about our team we have a brilliant team, brilliant minds, and it took us a long time to get here. Even if you spawn many teams to work on the same problems surely you will get somewhere… but currently we’re ahead and we’re doing our best to work on new technologies to keep in pace,” he adds.

Reface’s app is certainly having a moment right now, bagging top download slots on the iOS App Store and Google Play in 100 countries — helped, along the way, by its reflective effects catching the eye of the likes of Elon Musk and Britney Spears (who Mogylnyi says have retweeted examples of its content).

But he sees this bump as just the beginning — predicting much bigger things coming down the sythensized pipe as more powerful features are switched on. The influx of bitesized celebrity face swaps signals an incoming era of personalized media, which could have a profoundly transformative effect on culture.

Mogylnyi’s hope is that wide access to synthensized media tools will increase humanity’s empathy and creativity — providing those who engage with the tech limitless chances to (auto)vicariously experience things they maybe otherwise couldn’t ever (or haven’t yet) — and so imagine themselves into new possibilities and lifestyles.

He reckons the tech will also open up opportunities for richly personalized content communities to grow up around stars and influencers — extending how their fans can interact with them.

“Right now the way influencers exist is only one way; they’re just giving their audience the content. In my understanding in our case we’ll let influencers have the possibility to give their audience access to the content and to feel themselves in it. It’s one of the really cool things we’re working on — so it will be a part of the platform,” he says.

“What’s interesting about new-gen social networks [like TikTok] is that people can both be like consumers and providers at the same time… So in our case people will also be able to be providers and consumers but on the next level because they will have the technology to allow themselves to feel themselves in the content.”

“I used to play basketball in school years but I had an injury and I was dreaming about a pro career but I had to stop playing really hard. I’ll never know how my life would have gone if I was a pro basketball player so I have to be a startup entrepreneur right now instead… So in the case with our platform I actually will have a chance to see how my pro basketball career would look like. Feel myself in the content and life this life,” he adds.

This vision is really the mirror opposite of the concerns that are typically attached to deepfakes, around the risk of people being taken in, tricked, shamed or otherwise manipulated by intentionally false imagery.

So it’s noteworthy that Reface is not letting users loose on their technology in a way that could risk an outpouring of problem content. For example, you can’t yet upload your own video to make into a deepfake — although the ability to do so is coming. For now, you have to pick from a selection of preloaded celebrity clips and GIFs which no one would mistake for the real-deal.

That’s a very deliberate decision, with Mogylnyi emphasizing they want to be responsible in how they bring the tech to market.

User generated video and a lot more — full body swaps are touted, next year — are coming, though. But before they turn on more powerful content generation functionality they’re working on building a counter tech to reliably detect such generated content. Mogylnyi says it will only open up usage once they’re confident of being able to spot their own fakes.

“It will be this autumn, actually,” he says of launching UGC video (plus the deepfake detection capability). “We’ll launch it with our Face Studio… which will be a tool for content creators, for small studios, for small post production studios, maybe some music video makers.”

“We also have five different technologies in our pipeline which we’ll show in the upcoming half a year,” he adds. “There are also other technologies and features based on current tech [stack] that we’ll be launching… We’ll allow users to swap faces in pictures with the new stack and also a couple of mechanics based on face swapping as well, and also separate technologies as well we’re aiming to put into the app.”

He says higher quality video swapping is another focus, alongside building out more technologies for post production studios. “Face Studio will be like an overall tool for people who want full access to our technologies,” he notes, saying the pro tool will launch later this year.

The Ukrainian team behind the app has been honing their deep tech chops for years — starting working together back in 2011 straight out of university and going on to set up a machine learning dev shop in 2013.

Work with post production studios followed, as they were asked to build face swapping technology to help budget-strapped film production studios do more while having to move their actors move around less.

By 2018, with plenty of expertise under their belt, they saw the potential for making deepface technology more accessible and user friendly — launching the GIF version of the app late last year, and going on to add video this summer when they also rebranded the app to Reface. The rest looks like it could be viral face swapping tech history…

So where does all this digital shapeshifting end up? “In our dreams and in our vision we see the app as a personalization platform where people will be able to live different lives during their one lifetime. So everyone can be anyone,” says Mogylnyi. “What’s the overall problem right now? People are scrolling content, not looking deep into it. And when I see people just using our app they always try to look inside — to look deeply into the picture. And that’s what really inspires us. So we understand that we can take the way people are browsing and the way they are consuming content to the next level.”

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