The multi-trillion dollar global real estate market is getting flipped on its head.

Business model innovation, data accessibility and the proliferation of mobile, SaaS and other cloud-native software have already given rise to a cohort of tech unicorns that sit amongst the world’s most influential real estate companies. Emerging technologies and growing capabilities across machine learning, 5G, IoT and more — coupled with fast-moving regulations and dramatic cost structure changes — have opened up opportunities for the next wave of innovation across a wide set of multi-billion dollar real estate verticals and sub-verticals.

And despite WeWork’s implosion garnering countless headlines in the real estate and technology worlds, venture dollars are continuing to spill into real estate tech (or proptech) companies at a rapidly increasing rate. Just upwards of $16 billion in venture capital has flowed into real estate-related startups in 2019 alone, according to data from Crunchbase and Pitchbook, with major fundraises happening across industrial, commercial, residential, and financial categories.

If we follow the money, it’s clear that more and more leading VCs are turning to real estate tech or proptech for ripe opportunities for juicy returns and disruption on a global scale. Given the countless subsectors where exciting new startups are popping up, we asked more than 20 leading real estate VCs who work at firms that span early to growth stages to share where they see opportunity within the colossal real estate category. For purposes of length and clarity, responses have been edited and split up into part one and part two of this survey (in no particular order). In part one of our survey, we hear from:

• Zach Aarons, MetaProp
• Pete Flint, NFX
• Ryan Freedman, Corigin Ventures
• Constance Freedman, Moderne Ventures
• Tyler Sosin, Menlo Ventures
• Jeff Crowe, Norwest Venture Partners
• Micah Kotch, URBAN-X
• Merritt Hummer, Bain Capital Ventures
• Kia Nejatian, Plug and Play
• MJ Cootsona, Plug and Play
• Robin Godenrath, Picus Capital

Answers have been edited for length and clarity.

Zach Aarons, MetaProp

What trends are you most excited in real estate tech from an investing perspective?

We like to track trends that play out in the broader real estate markets. Due to low interest rates and cap rate compression, real estate investors are now looking for yield through investments in non-traditional asset types. Industrial real estate has performed very well over the last few years, and we see a push toward workforce housing, medical real estate, and senior housing. We are looking at investing in technologies that benefit processes within these non-traditional asset classes.

How much time are you spending on real estate tech right now? Is the market under-heated, over-heated, or just right?

We spend 100% of our time on real estate tech (proptech). The market is definitely hot, but the addressable markets are enormous and adoption is still relatively low and accelerating. We believe that now is a good time to invest in early-stage proptech, provided it’s done prudently.

Are there startups that you wish you would see in the industry but don’t?

We would love to see more startups in the material sciences sector. Innovations like steel, bricks, timber, glass and reinforced concrete are hardly new, and they are still the predominant building materials of today. There have been minor advances like cross-laminated timber; however, we are looking for fundamentally new materials to bring into the building trades.

Plus any other thoughts you want to share with TechCrunch readers.

Proptech is the most fun sector in the world. No other sector shares the complexities and idiosyncrasies of technology that has to be applied to the built world. We are very lucky we get to do what we do.

Pete Flint, NFX

Real estate is the biggest asset class in the world by far, but the products available and service proposition surrounding it are still in the early stages of tech adoption. I see at least three major areas of opportunity for startups in real estate tech.

First is the real estate transaction process. Starting around 2005, companies like Trulia and Zillow, transformed the consumer research experience and home buyers increasingly began their search online. But the transaction itself spanning brokerage, financing and closing remains largely analog, complicated and inefficient. There’s an opportunity for startups to provide innovative solutions to help simplify and digitize the transaction process. Example companies in this area are Ribbon and Modus.

Second is the rise of alternative (or professionalized) living arrangements. I see a big opportunity for startups with a strong technology component to provide solutions for the mismatch between the way consumers want to live today and the aging housing supply that was built for a previous era with different needs and demographics. Companies like Lyric and Zeus are building alternative living solutions with a vertically-integrated short term rental strategy, while co-living startups are providing long-term rentals with value-added services.

Third is spend around the home. The large costs in time, effort, and money of designing, building, and maintaining a home provide an opportunity for tech-enabled solutions in construction, home management, and home maintenance. For example, Setter is providing a better consumer experience for requesting home maintenance services while Constru is bringing AI and machine vision to lower prices and reduce schedule overrun on construction sites. I see many more opportunities for startups like these in this space.

While these are big opportunities, the challenge with investing in real estate tech is to find startups with teams that not only have world-class product and software capabilities, but also world-class knowledge of finance, real estate, and operations. And with the recent WeWork debacle, we have seen a renewed emphasis on the failings of low-margin businesses. So for PropTech startups that are looking for funding today, there’s an increased need to demonstrate good unit economics and long-term margin potential.

Ryan Freedman, Corigin Ventures

At a high level, I believe we are still in the early innings of proptech – maybe 3rd or 4th inning. I always like to make the comparison to fintech. Technically speaking, real estate is a larger asset class than financial services. Between 2013-2017, fintech had cumulative funding of $62.4B vs. proptech’s $10.1B. Even though proptech has ramped up the last few years, we still have a long way to go prior to catching up. In addition, you may recall that PropTech used to be a “sub-sector” of fintech prior to being its own behemoth category. There are several subsectors within PropTech today, that I think a few years from now will be their own categories – construction tech is one of those.

From an investment perspective, we’re spending a lot of time in construction tech right now. From a macro standpoint, we feel there is a supply-demand mismatch with respect to the size of the market and the amount of funding in the space. Construction accounts for ~$10T annual spend globally and employs ~7% of the global workforce. In addition, it’s one of the most antiquated industries in the world. This summer we spent a ton of time digging into the space and have now made a handful of investments. We’re big believers of founder-market-fit, and this category in particular requires category expertise to navigate a very old-school industry.

Another area we’re spending time in is broker-tech. We’ve seen the “tech-enabled brokerage” model be effective in a ton of different industries including PropTech. A lot of investors believe this space is “crowded” – which is true in some sub-sectors (i.e. residential) – but when you look closely within the commercial real estate industry, we believe there is a massive opportunity to disrupt traditional real estate capital markets firms.

Source: Tech Crunch Startups | Where top VCs are investing in real estate and proptech (Part 1 of 2)

Back in September, endurance events marketplace Let’s Do This (a YC alumni) raised a $5 million seed round from a number of U.S. investors, including Olympic star Usain Bolt and tennis star Serena Williams. As much as I’d like to get excited, this is slightly par for the course for a lot of sports-oriented startups that catch the eye of a celebrity. Not that they are without merit, of course.

Suffice it to say, their sports stars, plus a strong push to get funding from Silicon Valley, has landed the startup with a $15 million Series A round led by European/U.S. VC EQT, with participation of the previous investors, including Trulia founder Pete Flint, Y Combinator, alongside, yes, you guessed it, Usain Bolt and Serena Williams .

The platform lists 30,000 races of all distances and disciplines and claims to be the largest marketplace for endurance events in the world, offering key information about the races and exclusive booking perks for members, such as free cancellation protection. It recently agreed to a partnership with Hearst to power all race listings across Runner’s World, Men’s Health and Women’s Health in the U.S. and the U.K.

The startup is set to expand its team of sport enthusiasts across its San Francisco and London offices. The company was founded by University of Cambridge graduates Alex Rose and Sam Browne — both passionate runners and cyclists who had experienced the arduous process of discovering and entering events.

The Let’s Do This algorithm uses data points from fitness tracking, race history, social connections and more to personalize race recommendations. Part of the marketing story is that people are 12.5 times more likely to develop a fitness habit after 12 months from signing up to a race than from joining a gym.

Serena Williams, the 22-time Grand Slam Champion, commented: “I’ve seen firsthand the incredible impact these events can have on making people fitter, healthier and happier. I love that Let’s Do This is not only making events like these more accessible but also helping to support athletes of all different fitness levels. Women are especially less likely to participate in marathons and obstacle races, so it’s really important there’s a platform encouraging people to step out of their comfort zones and make a positive difference in their lives.”

Usain Bolt said in a statement: “Throughout my career I’ve been lucky enough to inspire people to follow their dreams, get off the couch and get exercising… It’s a really natural fit with what I care about and what I believe in, so I am very happy to be supporting their mission to inspire more people to have epic experiences.”

Founder Sam Browne says the quick fundraising has come about in part because “The market’s big, affluent and we’re already the dominant marketplace in it.”

Source: Tech Crunch Startups | Backed by Serena Williams and Usain Bolt, Let’s Do This raises M from EQT

E-commerce accounts for around 11% of all retail sales in the U.S., but it’s growing much faster than brick-and-mortar sales, going up 14.8% this year versus a mere 1.9% for physical retail, according to eMarketer. So to better compete today and in the future, retailers are now investing in more advanced tools not just to figure out more about what’s selling best, when and where, but how to serve individuals better — in essence, to provide the same kind of help, recommendations, discounts and communication with shoppers that online portals like Amazon provides.

Punchh, a company that got its start in loyalty cards (hence the name) but has since expanded into a wider world of analytics and customer personalization to tap into that trend, is today announcing that it has raised $40 million to continue expanding its business. The funding is being led by Adams Street Partners and Sapphire Ventures (which also led its previous round of $30 million in April 2018), with AllianceBernstein also participating.

To date, Punchh has raised around $73 million, with its valuation over $300 million. (To be clear, CEO and founder Shyam Rao said the exact number wasn’t being disclosed, but he did say it was “well north” of multiples of its last valuation, which was around $100 million. PitchBook has filled in the blanks: A first close of this round this summer, for just over $35 million, came in at a pre-money valuation of $300 million, which would make this about $340 million.)

Punchh has built most of its business up to now in the restaurant industry. Its customers include companies like Yum Brands (the Pizza Hut, Taco Bell, KFC giant), Denny’s and other big and smaller operations, where it provides not just app-based loyalty card services, but ways to link up people’s payment cards with their purchasing history to better track what they are buying, and the ability to build subsequent discount and other promotional campaigns around that. Altogether, Rao tells me that it has data on some 125 million customers globally, covering some 80,000 locations.

“We get access to 100% of all transactions at those locations, working out to 3 billion transactions per month,” Rao said. That data in turn trains Punchh’s AI models to feed the bigger recommendation and analytics engine.

For the last year, Punchh has been slowly expanding into other retail areas, such as convenience stores and more: Its most recent customer win, a deal with Casey’s General Stores, Inc. with 2,100 stores in 16 states in the Midwest, is a sign that the strategy is working.

The opportunity that Punchh is targeting is somewhat ironic — the level of personalization that it’s building into the brick-and-mortar customer experience used to be a cornerstone of what it meant to be a “regular customer” at a local or favorite store, bar or restaurant.

These days — in part because of the decline of the small business, in part because our spending habits have changed, in part because everything has been digitised and retailers are looking for ways to actually downsize human-based customer relations — you don’t typically get that kind of experience anymore.

On the online front, online stores like Amazon have leveraged the model of personalization and seized the opportunity to use data to offer it in their own style: by recommending products to you when you come to their virtual storefronts, based on what you’ve bought or browsed for already online. So while old days of brick-and-mortar personalization have disappeared, they’ve been quickly replaced online — but not so in the physical world.

That’s now slowly changing in part because of innovations from companies like Punchh, which also takes into account cash purchases, as its technology is integrated at the point of sale.

“When you buy something in cash, we may not know who you are but we do know that you come in at, say, 8am and what you bought,” he said. “We can still use that to predict lifetime value and to generate a coupon.” 

Ironically, while the model was pioneered in brick and mortar, it was honed online, and is now again being improved and advanced, Punchh supporters say, back in the physical — not online — world, which is, after all, still accounting for more sales overall.

“Punchh is the undisputed leader in this category. They work with the biggest brands, have the most sophisticated technology, and drive real results for their customers,” said Robin Murray, partner at Adams Street Partners, in a statement. “While everyone else got distracted by maximizing ecommerce, Punchh took the best technologies and practices from that space and applied them to physical retail. Now the world is coming back around – just look at Amazon’s purchase of Whole Foods – and Punchh is already 10 steps ahead of the game.”

Source: Tech Crunch Startups | Punchh lands M to give physical retailers Amazon-style analytics

1Password has been around for 14 years, and the founders grew the company the old-fashioned way — without a dime of venture capital. But when it decided to take venture help, it went all in. Today, the company announced a $200 million Series A from Accel, the largest single investment in the firm’s 35-year history.

Dave Teare says he and his co-founder Roustem Karimov were resolving a major pain point for users around password creation and management when they launched in 2005, and that the Toronto company has been profitable from day one. That’s not something you hear from startups all that often.

Today, Jeff Shiner is CEO. He helped grow the company from 20 employees when he came on board in 2012 to 174 today. He says that as he helped foster this growth, he saw a tremendous market opportunity in front of him. That’s when he decided to finally take the plunge into venture investing.

“We’ve got the sophisticated business tooling that we built over the last five years, so that we can really go out there and just double and triple down on what we’ve been doing, and drive that much faster and further into the market, and again that market is honestly from consumers all the way up to enterprises,” Shiner explained.

While he is confident in his company’s ability to build a product people want and its support for its customers, it needs help with other aspects of the business to grow faster and take advantage of the market potential. “We have far less experience with things like go-to-market programs, with sales, marketing and finance teams — and things like that. And we need to grow, and grow aggressively, which is not just hiring people, but also getting the right partners, finding the right leaders to help us with that growth,” he said.

Accel has a history of investing in mature companies that haven’t taken funding before, so what it’s doing with this round isn’t all that unusual for the firm. Arun Mathew, a partner at Accel, says he doesn’t come across companies like 1Password all that often. “Like Atlassian and Qualtrics, the 1Password team impressed us by building a business that’s not only scaling extremely quickly but also has been profitable since day one — and that’s why today we’re making the biggest single investment in Accel’s 35-year history,” Mathew said in a statement.

The founders actually stumbled onto the idea of 1Password in 2005. They were running a web development consultancy when they decided to resolve a long-standing problem of logging into multiple websites, a particularly acute issue given their day jobs.

They decided to build a tool to help, and when they put it out in the world, they found lots of other people had the same problem. They ended up closing the web consultancy to build 1Password, and the rest, as they say, is history.

Source: Tech Crunch Startups | Fourteen years after launching, 1Password takes a 0M Series A

Moveworks, a startup using AI to help resolve help desk tickets in an automated fashion, announced a $75 million Series B investment today.

The round was led by Iconiq Capital, Kleiner Perkins and Sapphire Ventures. Existing investors Lightspeed Venture Partners, Bain Capital Ventures and Comerica Bank also participated. The round also included a personal investment from John W. Thompson, a partner at LightSpeed Venture Partners and chairman at Microsoft. Today’s investment brings the total raised to $105 million, according to the company.

That’s a lot of money for an early-stage company, but CEO and co-founder Bhavin Shah says his company is solving a common problem using AI. “Moveworks is a machine learning platform that uses natural language understanding to take tickets that are submitted by employees every day to their IT teams for stuff they need, and we understand [the content of the tickets], interpret them, and then we take the actions to resolve them [automatically],” Shah explained.

He said the company decided to focus on help desk tickets because they saw data when they were forming the company that suggested a common set of questions, and that would make it easier to interpret and resolve these issues. In fact, they are currently able to resolve 25-40% of all tickets autonomously.

He says this should lead to greater user satisfaction because some of their problems can be resolved immediately, even when IT personnel aren’t around to help. Instead of filing a ticket and waiting for an answer, Moveworks can provide the answer, at least part of the time, without human intervention.

Aditya Agrawal, a partner at Iconiq, says that the company really captured his attention. “Moveworks is not just transforming IT operations, they are building a more modern and enlightened way to work. They’ve built a platform that simplifies and streamlines every interaction between employees and IT, enabling both to focus on what matters,” he said in a statement.

The company was founded in 2016, and in the early days was only resolving 2% of the tickets autonomously, so it has seen major improvement. It already has 115 employees and dozens of customers (although Shah didn’t want to provide an exact number).

Source: Tech Crunch Startups | Moveworks snags M Series B to resolve help desk tickets with AI

Livin’ la vida loca pretty much sums up the early-stage startup life. We understand just how crazy-busy life gets, but we’re here to remind all the last-minute mavens that you have just 48 hours to take advantage of early-bird prices to Disrupt Berlin 2019. Depending on the type of pass you buy, you can save up to €500.

The early-bird pricing ends at 11:59 p.m. (CEST) this Friday, 15 November. Hit the brakes on livin’ la vida loca long enough to beat the deadline, buy your early-bird pass and save.

Now that you’ve saved a tidy sum, why not get a jump on planning your time at Disrupt Berlin? If networking’s your game, you’ll want to take advantage of CrunchMatch. Our free business-matching platform combines the best of two worlds — automation and curation — to help you zero in on the people who align with your business goals. Cut through the noise and spend your valuable time talking to the right people. Read about how CrunchMatch works.

Curious about the latest innovations happening across the tech spectrum? Set your GPS for Startup Alley, our exhibition floor, where you’ll find hundreds of early-stage startups displaying their products, platforms and services. Whether you’re an investor, founder or developer — or play some other role in the startup world — you’ll find something new and exciting in Startup Alley.

When you’re in Startup Alley, be sure to check out our TC Top Picks. TechCrunch editors chose these early-stage startups because they represent the best of their respective tech categories. Which startups won this coveted designation? Meet our TC Top Picks for Disrupt Berlin 2019.

Want to see top-notch startups in action? Grab a seat for the world-famous, always-epic Startup Battlefield pitch competition. Between 15-20 teams of startup founders will pitch to a tough panel of veteran VCs and technologists. Every competitor has what it takes, but which one will take it all — the Disrupt Cup, $50,000 in equity-free cash and intense investor and media exposure?

There’s more to experience at Disrupt Berlin, including interviews, fireside chats and panel discussions with world-class speakers. You can go deeper on a specific topic by attending Q&A Sessions, and you can check out what some of the world’s best coders created at the Hackathon. The finalists will pitch their products on the Extra Crunch Stage. Don’t miss what matters most to you — check out the Disrupt Berlin agenda.

Disrupt Berlin 2019 takes place on 11-12 December. You have only 48 hours left to get the best possible price on tickets. You can live la vida loca and still beat the deadline. Buy your early-bird pass before Friday, 15 November at11:59 p.m. (CEST).

Is your company interested in sponsoring or exhibiting at Disrupt Berlin 2019? Contact our sponsorship sales team by filling out this form.

Source: Tech Crunch Startups | 48 hours left to save up to €500 on passes to Disrupt Berlin 2019

One of the bigger trends in enterprise software has been the emergence of startups building tools to make the benefits of artificial intelligence technology more accessible to non-tech companies. Today, one that has built a platform to apply power of machine learning and natural language processing to massive documents of unstructured data has closed a round of funding as it finds strong demand for its approach.

Eigen Technologies, a London-based startup whose machine learning engine helps banks and other businesses that need to extract information and insights from large and complex documents like contracts, is today announcing that it has raised $37 million in funding, a Series B that values the company at around $150 million – $180 million.

The round was led by Lakestar and Dawn Capital, with Temasek and Goldman Sachs Growth Equity (which co-led its Series A) also participating. Eigen has now raised $55 million in total.

Eigen today is working primarily in the financial sector — its offices are smack in the middle of The City, London’s financial center — but the plan is to use the funding to continue expanding the scope of the platform to cover other verticals such as insurance and healthcare, two other big areas that deal in large, wordy documentation that is often inconsistent in how its presented, full of essential fine print, and is typically a strain on an organisation’s resources to be handled correctly, and is often a disaster if it is not.

The focus up to now on banks and other financial businesses has had a lot of traction. It says its customer base now includes 25% of the world’s G-SIB institutions (that is, the world’s biggest banks), along with others who work closely with them like Allen & Overy and Deloitte. Since June 2018 (when it closed its Series A round), Eigen has seen recurring revenues grow sixfold with headcount — mostly data scientists and engineers — double. While Eigen doesn’t disclose specific financials, you can the growth direction that contributed to the company’s valuation.

The basic idea behind Eigen is that it focuses what co-founder and CEO Lewis Liu describes as “small data”. The company has devised a way to “teach” an AI to read a specific kind of document — say, a loan contract — by looking at a couple of examples and training on these. The whole process is relatively easy to do for a non-technical person: you figure out what you want to look for and analyse, find the examples using basic search in two or three documents, and create the template which can then be used across hundreds or thousands of the same kind of documents (in this case, a loan contract).

Eigen’s work is notable for two reasons. First, typically machine learning and training and AI requires hundreds, thousands, tens of thousands of examples to “teach” a system before it can make decisions that you hope will mimic those of a human. Eigen requires a couple of examples (hence the “small data” approach).

Second, an industry like finance has many pieces of sensitive data (either because its personal data, or because it’s proprietary to a company and its business), and so there is an ongoing issue of working with AI companies that want to “anonymise” and ingest that data. Companies simply don’t want to do that. Eigen’s system essentially only works on what a company provides, and that stays with the company.

Eigen was founded in 2014 by Dr. Lewis Z. Liu (CEO) and Jonathan Feuer (a managing partner at CVC Capital technologies who is the company’s chairman), but its earliest origins go back 15 years earlier, when Liu — a first-generation immigrant who grew up in the US — was working as a “data entry monkey” (his words) at a tire manufacturing plant in New Jersey, where he lived, ahead of starting university at Harvard.

A natural computing whizz who found himself building his own games when his parents refused to buy him a games console, he figured out that the many pages of printouts that he was reading and re-entering into a different computing system could be sped up with a computer program linking up the two. “I put myself out of a job,” he joked.

His educational life epitomises the kind of lateral thinking that often produces the most interesting ideas. Liu went on to Harvard to study not computer science, but physics and art. Doing a double major required working on a thesis that merged the two disciplines together, and Liu built “electrodynamic equations that composed graphical structures on the fly” — basically generating art using algorithms — which he then turned into a “Turing test” to see if people could detect pixelated actual work with that of his program. Distil this, and Liu was still thinking about patterns in analog material that could be re-created using math.

Then came years at McKinsey in London (how he arrived on these shores) during the financial crisis where the results of people either intentionally or mistakenly overlooking crucial text-based data produced stark and catastrophic results. “I would say the problem that we eventually started to solve for at Eigen became for tangible,” Liu said.

Then came a physics PhD at Oxford where Liu worked on X-ray lasers that could be used to bring down the complexity and cost of making microchips, cancer treatments and other applications.

While Eigen doesn’t actually use lasers, some of the mathematical equations that Liu came up with for these have also become a part of Eigen’s approach.

“The whole idea [for my PhD] was, ‘how do we make this cheeper and more scalable?’” he said. “We built a new class of X-ray laser apparatus, and we realised the same equations could be used in pattern matching algorithms, specifically around sequential patterns. And out of that, and my existing corporate relationships, that’s how Eigen started.”

Five years on, Eigen has added a lot more into the platform beyond what came from Liu’s original ideas. There are more data scientists and engineers building the engine around the basic idea, and customising it to work with more sectors beyond finance. 

There are a number of AI companies building tools for non-technical business end-users, and one of the areas that comes close to what Eigen is doing is robotic process automation, or RPA. Liu notes that while this is an important area, it’s more about reading forms more readily and providing insights to those. The focus of Eigen in more on unstructured data, and the ability to parse it quickly and securely using just a few samples.

Liu points to companies like IBM (with Watson) as general competitors, while startups like Luminance is another taking a similar approach to Eigen by addressing the issue of parsing unstructured data in a specific sector (in its case, currently, the legal profession).

Stephen Nundy, a partner and the CTO of Lakestar, said that he first came into contact with Eigen when he was at Goldman Sachs, where he was a managing director overseeing technology, and the bank engaged it for work.

“To see what these guys can deliver, it’s to be applauded,” he said. “They’re just picking out names and addresses. We’re talking deep, semantic understanding. Other vendors are trying to be everything to everybody, but Eigen has found market fit in financial services use cases, and it stands up against the competition. You can see when a winner is breaking away from the pack and it’s a great signal for the future.”

Source: Tech Crunch Startups | Eigen nabs M to help banks and others parse huge documents using natural language and ‘small data’