Cisco to acquire silicon photonics chip maker Luxtera for $660 million

As networks get put under increasing pressure from ever-growing amounts of data, network equipment manufacturers are facing huge challenges to increase data transmissions speeds over further distances. As a premiere networking equipment company, Cisco wants to be prepared to meet that demand. Today, it opened up its checkbook and announced its intent to acquire Luxtera for $660 million.

Luxtera, which was founded in 2001 and raised over $130 million, will give Cisco a photonic solution for that data networking problem. Rob Salvagno, head of Cisco’s M&A and venture investment team sees a company that can help modernize Cisco’s networking equipment.

“That’s why today we announced our intent to acquire Luxtera, Inc., a privately-held semiconductor company that uses silicon photonics technology to build integrated optics capabilities for webscale and enterprise data centers, service provider market segments, and other customers. Luxtera’s technology, design and manufacturing innovation significantly improves performance and scale while lowering costs,” he wrote in a blog post announcing the acquisition.

Photonics uses light to move large amounts of data at higher speeds over increased distances via fiber optic cable. Cisco sees this as a way to future-proof customer networking requirements, while keeping them on Cisco equipment. “The combination of Cisco’s and Luxtera’s capabilities in 100GbE/400GbE optics, silicon and process technology will enable customers to build future-proof networks optimized for performance, reliability and cost,” Salvagno wrote.

While Cisco has been acquiring its share of high-profile software properties in recent years including AppDyanmics for $3.7 billion in 2017 and Jasper Technologies for $1.4 billion in 2016, it also acquired Israeli chip designer Leaba Semiconductor for $320 million in 2016 for its advanced chip making capability.

Today’s announcement would seem to build on that earlier purchase as Cisco tries to modernize its hardware offerings to meet increasingly stringent demands inside large-scale data centers.

The acquisition is subject to the typical regulatory scrutiny, but Cisco expects it to close in its fiscal year 2019 Q3. It reported its Q1 2019 earnings in November.

Google will make it easier for people without accounts to collaborate on G Suite documents

Soon it will be easier for people without Google accounts to collaborate on G Suite documents. Currently in beta, a new feature will enable G Suite users to invite people without G Suite subscriptions or Google accounts to work on files by sending them a pin code.

Using the pin code to gain access allows invitees to view, comment on, suggest edits to, or directly edit Google Docs, Sheets, and Slides. The owners and admins of the G Suite files monitor usage through activity logs and can revoke access at any time. According to the feature’s support article, admins are able to set permissions by department or domain. They can also restrict sharing outside of white-listed G Suite domains or their own organization.

In order to sign up for the beta program, companies need to fill in this form and select a non-G Suite domain they plan to collaborate with frequently.

According to a Reuters article published in February, since intensifying their focus on enterprise customers, Google has doubled the number of organizations with a G Suite subscription to more than 4 million. But despite Google’s efforts to build its enterprise user base, G Suite hasn’t come close to supplanting Office 365 as the cloud-based productivity software of choice for companies.

Office 365 made $13.8 billion in sales in 2016, versus just $1.3 billion for G Suite, according to Gartner. Google has added features to G Suite, however, to make the two competing software suites more interoperable, including an update that enables Google Drive users to comment on Office files, PDFs, and images in the Drive preview panel without needing to convert them to Google Docs, Sheets or Slide files first, even if they don’t have Microsoft Office or Acrobat Reader. Before that, Google also released a Drive plugin for Outlook.

This may not convince Microsoft customers to switch, especially if they have been using its software for decades, but at least it will get more workers comfortable with Google’s alternatives, and may convince some companies to subscribe to G Suite for at least some employees or departments.

The limits of coworking

It feels like there’s a WeWork on every street nowadays. Take a walk through midtown Manhattan (please don’t actually) and it might even seem like there are more WeWorks than office buildings.

Consider this an ongoing discussion about Urban Tech, its intersection with regulation, issues of public service, and other complexities that people have full PHDs on. I’m just a bitter, born-and-bred New Yorker trying to figure out why I’ve been stuck in between subway stops for the last 15 minutes, so please reach out with your take on any of these thoughts: @[email protected].

Co-working has permeated cities around the world at an astronomical rate. The rise has been so remarkable that even the headline-dominating SoftBank seems willing to bet the success of its colossal Vision Fund on the shift continuing, having poured billions into WeWork – including a recent $4.4 billion top-up that saw the co-working king’s valuation spike to $45 billion.

And there are no signs of the trend slowing down. With growing frequency, new startups are popping up across cities looking to turn under-utilized brick-and-mortar or commercial space into low-cost co-working options.

It’s a strategy spreading through every type of business from retail – where companies like Workbar have helped retailers offer up portions of their stores – to more niche verticals like parking lots – where companies like Campsyte are transforming empty lots into spaces for outdoor co-working and corporate off-sites. Restaurants and bars might even prove most popular for co-working, with startups like Spacious and KettleSpace turning restaurants that are closed during the day into private co-working space during their off-hours.

Before you know it, a startup will be strapping an Aeron chair to the top of a telephone pole and calling it “WirelessWorking”.

But is there a limit to how far co-working can go? Are all of the storefronts, restaurants and open spaces that line city streets going to be filled with MacBooks, cappuccinos and Moleskine notebooks? That might be too tall a task, even for the movement taking over skyscrapers.

The co-working of everything

Photo: Vasyl Dolmatov / iStock via Getty Images

So why is everyone trying to turn your favorite neighborhood dinner spot into a part-time WeWork in the first place? Co-working offers a particularly compelling use case for under-utilized space.

First, co-working falls under the same general commercial zoning categories as most independent businesses and very little additional infrastructure – outside of a few extra power outlets and some decent WiFi – is required to turn a space into an effective replacement for the often crowded and distracting coffee shops used by price-sensitive, lean, remote, or nomadic workers that make up a growing portion of the workforce.

Thus, businesses can list their space at little-to-no cost, without having to deal with structural layout changes that are more likely to arise when dealing with pop-up solutions or event rentals.

On the supply side, these co-working networks don’t have to purchase leases or make capital improvements to convert each space, and so they’re able to offer more square footage per member at a much lower rate than traditional co-working spaces. Spacious, for example, charges a monthly membership fee of $99-$129 dollars for access to its network of vetted restaurants, which is cheap compared to a WeWork desk, which can cost anywhere from $300-$800 per month in New York City.

Customers realize more affordable co-working alternatives, while tight-margin businesses facing increasing rents for under-utilized property are able to pool resources into a network and access a completely new revenue stream at very little cost. The value proposition is proving to be seriously convincing in initial cities – Spacious told the New York Times, that so many restaurants were applying to join the network on their own volition that only five percent of total applicants were ultimately getting accepted.

Basically, the business model here checks a lot of the boxes for successful marketplaces: Acquisition and transaction friction is low for both customers and suppliers, with both seeing real value that didn’t exist previously. Unit economics seem strong, and vetting on both sides of the market creates trust and community. Finally, there’s an observable network effect whereby suppliers benefit from higher occupancy as more customers join the network, while customers benefit from added flexibility as more locations join the network.

… Or just the co-working of some things

Photo: Caiaimage / Robert Daly via Getty Images

So is this the way of the future? The strategy is really compelling, with a creative solution that offers tremendous value to businesses and workers in major cities. But concerns around the scalability of demand make it difficult to picture this phenomenon becoming ubiquitous across cities or something that reaches the scale of a WeWork or large conventional co-working player.

All these companies seem to be competing for a similar demographic, not only with one another, but also with coffee shops, free workspaces, and other flexible co-working options like Croissant, which provides members with access to unused desks and offices in traditional co-working spaces. Like Spacious and KettleSpace, the spaces on Croissant own the property leases and are already built for co-working, so Croissant can still offer comparatively attractive rates.

The offer seems most compelling for someone that is able to work without a stable location and without the amenities offered in traditional co-working or office spaces, and is also price sensitive enough where they would trade those benefits for a lower price. Yet at the same time, they can’t be too price sensitive, where they would prefer working out of free – or close to free – coffee shops instead of paying a monthly membership fee to avoid the frictions that can come with them.

And it seems unclear whether the problem or solution is as poignant outside of high-density cities – let alone outside of high-density areas of high-density cities.

Without density, is the competition for space or traffic in coffee shops and free workspaces still high enough where it’s worth paying a membership fee for? Would the desire for a private working environment, or for a working community, be enough to incentivize membership alone? And in less-dense and more-sprawl oriented cities, members could also face the risk of having to travel significant distances if space isn’t available in nearby locations.

While the emerging workforce is trending towards more remote, agile and nomadic workers that can do more with less, it’s less certain how many will actually fit the profile that opts out of both more costly but stable traditional workspaces, as well as potentially frustrating but free alternatives. And if the lack of density does prove to be an issue, how many of those workers will live in hyper-dense areas, especially if they are price-sensitive and can work and live anywhere?

To be clear, I’m not saying the companies won’t see significant growth – in fact, I think they will. But will the trend of monetizing unused space through co-working come to permeate cities everywhere and do so with meaningful occupancy? Maybe not. That said, there is still a sizable and growing demographic that need these solutions and the value proposition is significant in many major urban areas.

The companies are creating real value, creating more efficient use of wasted space, and fixing a supply-demand issue. And the cultural value of even modestly helping independent businesses keep the lights on seems to outweigh the cultural “damage” some may fear in turning them into part-time co-working spaces.

And lastly, some reading while in transit:

They scaled YouTube. Now they’ll shard everyone with PlanetScale

When the former CTOs of YouTube, Facebook, and Dropbox seed fund a database startup, you know there’s something special going on under the hood. Jiten Vaidya and Sugu Sougoumarane saved YouTube from a scalability nightmare by inventing and open sourcing Vitess, a brilliant relational data storage system. But in the decade since working there, the pair have been inundated with requests from tech companies desperate for help building the operational scaffolding needed to actually integrate Vitess.

So today the pair are revealing their new startup PlanetScale that makes it easy to build multi-cloud databases that handle enormous amounts of information without locking customers into Amazon, Google, or Microsoft’s infrastructure. Battletested at YouTube, the technology could allow startups to fret less about their backend and focus more on their unique value proposition. “Now they don’t have to reinvent the wheel” Vaidya tells me. “A lot of companies facing this scaling problem end up solving it badly in-house and now there’s a way to solve that problem by using us to help.”

PlanetScale has quietly raised a $3 million seed round in April led by SignalFire and joined by a who’s who of engineering luminaries. They include YouTube co-founder and CTO Steve Chen, Quora CEO and former Facebook CTO Adam D’Angelo, former Dropbox CTO Aditya Agarwal, PayPal and Affirm co-founder Max Levchin, MuleSoft co-founder and CTO Ross Mason, Google director of engineering Parisa Tabriz, and Facebook’s first female engineer and South Park Commons Founder Ruchi Sanghvi. If anyone could foresee the need for Vitess implementation services, it’s these leaders who’ve dealt with scaling headaches at tech’s top companies.

But how can a scrappy startup challenge the tech juggernauts for cloud supremacy? First, by actually working with them. The PlanetScale beta that’s now launching lets companies spin up Vitess clusters on its database-as-a-service, their own through a licensing deal, or on AWS with Google Cloud and Microsoft Azure coming shortly. Once these integrations with the tech giants are established, PlanetScale clients can use it as an interface for a multi-cloud setup where they could keep their data master copies on AWS US-West with replicas on Google Cloud in Ireland and elsewhere. That protects companies from becoming dependent on one provider and then getting stuck with price hikes or service problems.

PlanetScale also promises to uphold the principles that undergirded Vitess. “It’s our value that we will keep everything in the query pack completely open source so none of our customers ever have to worry about lock-in” Vaidya says.

PlanetScale co-founders (from left): Jiten Vaidya and Sugu Sougoumarane

Battletested, YouTube Approved

He and Sougoumarane met 25 years ago while at Indian Institute Of Technology Bombay. Back in 1993 they worked at pioneering database company Informix together before it flamed out. Sougoumarane was eventually hired by Elon Musk as an early engineer for X.com before it got acquired by PayPal, and then left for YouTube. Vaidya was working at Google and the pair were reunited when it bought YouTube and Sougoumarane pulled him on to the team.

“YouTube was growing really quickly and the relationship database they were using with MySQL was sort of falling apart at the seams” Vaidya recalls. Adding more CPU and memory to the database infra wasn’t cutting it, so the team created Vitess. The horizontal scaling sharding middleware for MySQL let users segment their database to reduce memory usage while still being able to rapidly run operations. YouTube has smoothly ridden that infrastructure to 1.8 billion users ever since.

“Sugu and Mike Solomon invented and made Vitess open source right from the beginning since 2010 because they knew the scaling problem wasn’t just for YouTube, and they’ll be at other companies 5 or 10 years later trying to solve the same problem” Vaidya explains. That proved true, and now top apps like Square and HubSpot run entirely on Vitess, with Slack now 30 percent onboard.

Vaidya left YouTube in 2012 and became the lead engineer at Endorse, which got acquired by Dropbox where he worked for four years. But in the meantime, the engineering community strayed towards MongoDB-style key-value store databases, which Vaidya considers inferior. He sees indexing issues and says that if the system hiccups during an operation, data can become inconsistent — a big problem for banking and commerce apps. “We think horizontally-scaled relationship databases are more elegant and are something enterprises really need.

Database Legends Reunite

Fed up with the engineering heresy, a year ago Vaidya committed to creating PlanetScale. It’s composed of four core offerings: professional training in Vitess, on-demand support for open source Vitess users, Vitess database-as-a-service on Planetscale’s servers, and software licensing for clients that want to run Vitess on premises or through other cloud providers. It lets companies re-shard their databases on the fly to relocate user data to comply with regulations like GDPR, safely migrate from other systems without major codebase changes, make on-demand changes, and run on Kubernetes.

The PlanetScale team

PlanetScale’s customers now include Indonesian ecommerce giant Bukalapak, and it’s helping Booking.com, GitHub, and New Relic migrate to open source Vitess. Growth is suddenly ramping up due to inbound inquiries. Last month around when Square Cash became the number one app, its engineering team published a blog post extolling the virtues of Vitess. Now everyone’s seeking help with Vitess sharding, and PlanetScale is waiting with open arms. “Jiten and Sugu are legends and know firsthand what companies require to be successful in this booming data landscape” says Ilya Kirnos, founding partner and CTO of SignalFire.

The big cloud providers are trying to adapt to the relational database trend, with Google’s Cloud Spanner and Cloud SQL, and Amazon’s AWS SQL and AWS Aurora. Their huge networks and marketing war chests could pose a threat. But Vaidya insists that while it might be easy to get data into these systems, it can be a pain to get it out. PlanetScale is designed to give them freedom of optionality through its multi-cloud functionality so their eggs aren’t all in one basket.

Finding product market fit is tough enough. Trying to suddenly scale a popular app while also dealing with all the other challenges of growing a company can drive founders crazy. But if it’s good enough for YouTube, startups can trust PlanetScale to make databases one less thing they have to worry about.

Chorus.ai rings up $33M for its platform that analyses sales calls to close more deals

Chorus.ai, a service that listens to sales calls in real time, and then transcribes and analyses them to give helpful tips to the salesperson, has raised $33 million to double down on the current demand for more AI-based tools in the enterprise.

The Series B is being led by Georgian Partners, with participation also from Redpoint Ventures and Emergence Capital, previous investors that backed Israeli-founded, SF-based Chorus.ai in its $16 million Series A two years ago.

In the gap between then and now, the startup has seen strong growth, listening in to some 5 million calls, and performing hundreds of thousands of hours of transcriptions for around 200 customers, including Adobe, Zoom, and Outreach (among others that it will not name).

Micha Breakstone, the co-founder (who has a pretty long history in conversational AI, heading up R&D at Ginger Software and then Intel after it acquired the startup; and before that building the tech that eventually became Summly and got acquired by Yahoo, among other roles), says that while the platform gives information and updates to salespeople in real time, much of the focus today is on providing information to users post-conversation, based on both audio and video calls.

One of its big areas is “smart themes” — patterns and rules Chorus has learned through all those calls. For example, it has identified what kind of language the most successful sales people are using and in turn prompts those who are less successful to use it more. Two general tips Breakstone told me about: using more collaborative terms like we and us; and giving more backstory to clients, although there will be more specific themes and approaches based on Chorus’s specific customers and products.

“I’d say we are super attuned to our customers and what they need and want,” Breakstone said. Which makes sense given the whole premise of Chorus.

It also creates smart “playlists” for managers who will almost certainly never have the time to review hundreds of hours of calls but might want to hear instructive highlights or ‘red alert’ moments where a more senior person might need to step in to save or close a deal.

There are currently what seems like dozens of startups and larger businesses that are currently tackling the opportunity to provide “conversational intelligence” to sales teams, using advances in natural language processing, voice recognition, machine learning and big data to help turn every sales person into a Jerry Maguire (yes, I know he’s an agent, but still, he needs to close deals, and he’s a salesman). They include TalkIQ (which has now been acquired by Dialpad), People.AI, Gong, Voicera, VoiceOps, and I’m pulling from a long list.

“We were among the very first to start this, no one knew what conversational intelligence was before us,” Breakstone says. He describes most of what was out in the market at the time as “Nineties technology” and adds that “our tech is superior because we built it in the correct way from the ground up, with nothing sent to a third party.”

He says that this is one reason why the company has negative churn — it essentially wins customers and hasn’t lost any. And having the tech all in-house not only means the platform is smarter and more accurate, but that helps with compliance around regulations like GDPR, which also has been a boost to its business. It’s also scored well on metrics around reps hitting targets better with its tools (the company claims its products lead to 50 percent greater quota attainment and ‘ramp time’ up by 30 percent for new sales people who use it).

Chorus.ai has helped us become a smarter sales organization as we’ve scaled. We have visibility into our sales conversations and what is working across all of our offices”, said Greg Holmes, Head of Sales for Zoom Video Communications, in a statement. “We’ve seen a drastic reduction in new hire ramp times and higher sales productivity with even more reps hitting quota. Chorus.ai is a game changer.”

Chorus has raised $55 million to date and Breakstone said he would not disclose its valuation — despite my best attempts to use some of those sales tips to winkle the information out of him. But I understand it to be “significantly higher” than in its last round, and definitely in the hundreds of millions.

As a point of reference, after its Series A two years ago, it was only valued at around $33 million post-money according to PitchBook.

“Maintaining high-quality sales conversations as you scale a sales organization is hard for many companies, but key to delivering predictable revenue growth. Chorus.ai’s Conversation Intelligence platform solves that challenge with a market-leading solution that is easy-to-use and delivers best-in-class results.” said Simon Chong, Managing Partner at Georgian Partners, in a statement. (Chong is joining the board with this round.) “Chorus.ai works with some of the best sales teams in the world and they love the product. We are very excited to partner with Chorus.ai on their next phase of growth as they help world class sales teams reach higher quota attainment and efficiency.”

Wandelbots raises $6.8M to make programming a robot as easy as putting on a jacket

Industrial robotics is on track to be worth around $20 billion by 2020, but while it may something in common with other categories of cutting-edge tech — innovative use of artificial intelligence, pushing the boundaries of autonomous machines that are disrupting pre-existing technology — there is one key area where it differs: each robotics firm uses its own proprietary software and operating systems to run its machines, making programming the robots complicated, time-consuming and expensive.

A startup out of Germany called Wandelbots (a portmanteau of “change” and “robots” in German) has come up with an innovative way to skirt around that challenge: it has built a bridge that connects the operating systems of the 12 most popular industrial robotics makers with what a business wants them to do, and now they can be trained by a person wearing a jacket kitted with dozens of sensors.

“We are providing a universal language to teach those robots in the same way, independent of the technology stack,” said CEO Christian Piechnick said in an interview. Essentially reverse engineering the process of how a lot of software is built, Wandelbots is creating what is a Linux-like underpinning to all of it.

With some very big deals under its belt with the likes of Volkwagen, Infineon and Midea, the startup out of Dresden has now raised €6 million ($6.8 million), a Series A to take it to its next level of growth and specifically to open an office in China. The funding comes from Paua VenturesEQT Ventures and other unnamed previous investors. (It had previously raised a seed round around the time it was a finalist in our Disrupt Battlefield last year, pre-launch.)

Notably, Paua has a bit of a history of backing transformational software companies (it also invests in Stripe), and EQT, being connected to a private equity firm, is treating this as a strategic investment that might be deployed across its own assets.

Piechnick — who co-founded Wandelbots with Georg Püschel, Maria Piechnick, Sebastian Werner, Jan Falkenberg and Giang Nguyen on the back of research they did at university — said that typical programming of industrial robots to perform a task could have in the past taken three months, the employment of specialist systems integrators, and of course an extra cost on top of the machines themselves.

Someone with no technical knowledge, wearing one of Wandelbots’ jackets, can bring that process down to 10 minutes, with costs reduced by a factor of ten.

“In order to offer competitive products in the face of the rapid changes within the automotive industry, we need more cost savings and greater speed in the areas of production and automation of manufacturing processes,” said Marco Weiß, Head of New Mobility & Innovations at Volkswagen Sachsen GmbH, in a statement. “Wandelbots’ technology opens up significant opportunities for automation. Using Wandelbots offering, the installation and setup of robotic solutions can be implemented incredibly quickly by teams with limited programming skills.”

Wandelbots’ focus at the moment is on programming robotic arms rather than the mobile machines that you may have seen Amazon and others using to move goods around warehouses. For now, this means that there is not a strong crossover in terms of competition between these two branches of enterprise robotics.

However, Amazon has been expanding and working on new areas beyond warehouse movements: it has, for example, been working ways of using computer vision and robotic arms to identify and pick out the most optimal fruits and vegetables out of boxes to put into grocery orders.

Innovations like that from Amazon and others could see more pressure for innovation among robotics makers, although Piechnick notes that up to now we’ve seen very little in the way of movement, and there may never be (creating more opportunity for companies like his that build more usability).

“Attempts to build robotics operating systems have been tried over and over again, and each time it’s failed,” he said. “But robotics has completely different requirements, such as real time computing, safety issues and many other different factors. A robot in operation is much more complicated than a phone.” He also added that Wandelbots itself has a number of innovations of its own currently going through the patent process, which will widen its own functionality too in terms of what and how its software can train a robot to do. (This may see more than jackets enter the mix.)

As with companies in the area of robotic process automation — which uses AI to take over more mundane back-office features — Piechnick maintains that what he has built, and the rise of robotics overall, is not going to replace workers, but put them on to other roles, while allowing businesses to expand the scope of what they can do that a human might never have been able to execute.

“No company we work with has ever replaced a human worker with a robot,” he said, explaining that generally the upgrade is from machine to better machine. “It makes you more efficient and cost reductive, and it allows you to put your good people on more complicated tasks.”

Currently, Wandelbots is working with large-scale enterprises, although ultimately, it’s smaller businesses that are its target customer, he said.

“Previously the ROI on robots was too difficult for SMEs,” he said. “With our tech this changes.”

“Wandelbots will be one of the key companies enabling the mass-adoption of industrial robotics by revolutionizing how robots are trained and used,” said Georg Stockinger, Partner at Paua Ventures, in a statement. “Over the last few years, we’ve seen a steep decline in robotic hardware costs. Now, Wandelbots’ resolves the remaining hurdle to disruptive growth in industrial automation – the ease and speed of implementation and teaching. Both factors together will create a perfect storm, driving the next wave of industrial revolution.”

 

 

InVision, valued at $1.9 billion, picks up $115 million Series F

“The screen is becoming the most important place in the world,” says InVision CEO and founder Clark Valberg . In fact, it’s hard to get through a conversation with him without hearing it. And, considering that his company has grown to $100 million in annual recurring revenue, he has reason to believe his own affirmation.

InVision, the startup looking to be the Salesforce of design, has officially achieved unicorn status with the close of a $115 million Series F round, bringing the company’s total funding to $350 million. This deal values InVision at $1.9 billion, which is nearly double its valuation as of mid-2017 on the heels of its $100 million Series E financing.

Spark Capital led the round with participation from Goldman Sachs, as well as existing investors Battery Ventures, ICONIQ Capital, Tiger Global Management, FirstMark and Geodesic Capital. Atlassian also participated in the round. Earlier this year, Atlassian and InVision built out much deeper integrations, allowing Jira, Confluence and Trello users to instantly collaborate via InVision.

As part of the deal, Spark Capital’s Megan Quinn will be joining the board alongside existing board members, Amish Jani, Vas Natarajan, Simon Nebel, Lee Fixel, and Mark Hastings.

InVision started out back in 2011 as a simple prototyping tool. It let designers build out their experience without asking the engineering/dev team to actually build it, to then send to the engineering and product and marketing and executive teams for collaboration and/or approval.

Over the years, the company has stretched its efforts both up and downstream in the process, building out a full collaboration suite called InVision Cloud (so that every member of the organization can be involved in the design process), Studio, a design platform meant to take on the likes of Adobe and Sketch, and InVision Design System Manager, where design teams can manage their assets and best practices from one place.

But perhaps more impressive than InVision’s ability to build design products for designers is its ability to attract users that aren’t designers.

“Originally, I don’t think we appreciated how much the freemium model acted as a fly wheel internally within an organization,” said Megan Quinn. “Those designers weren’t just inviting designers from their own team or other teams, but PMs and Marketing and Customer Service and executives to collaborate and approve the designs. From the outside, InVision looks like a design company. But really, they start with the designer as a core customer and spread virally within an organization to serve a multitude.”

InVision has simply dominated prototyping and collaboration, today announcing it has surpassed 5 million users. What’s more, InVision has a wide variety of customers. The startup has a long and impressive list of digital first customers — including Netflix, Uber, Airbnb and Twitter — but also serves 97 percent of the Fortune 100, with customers like Adidas, General Electric, NASA, IKEA, Starbucks, and Toyota.

Part of that can be attributed to the quality of the products, but the fundamental shift to digital (as predicted by Valberg) is most certainly under way. Whether brands like it or not, customers are interacting with them more and more from behind a screen, and digital customer experience is becoming more and more important to all companies.

In fact, a McKinsey study showed that companies that are in the top quartile scores of the McKinsey Design Index outperformed their counterparts in both revenues and total returns to shareholders by as much as a factor of two.

But as with any transition, some folks are adverse to change. Valberg identifies industry education and evangelism as two big challenges for InVision.

“Organizations are not quick to change on things like design, which is why we’ve built out a Design Transformation Team,” said Valberg. “The team goes in and gets hands on with brands to help them with new practices and to achieve design maturity within the organization.”

With a fresh $115 million and 5 million users, InVision has just about everything it needs to step into a new tier of competition. Even amongst behemoths like Adobe, which pulled in $2.29 billion in revenue in Q3 alone, InVision has provided products that can both compliment and compete.

But Quinn believes that the future of InVision rests on execution.

“As with most companies, the biggest challenge will be continued excellence in execution,” said Quinn. “InVision has all the right tail winds with the right team, a great product, and excellent customers. It’s all about building and executing ahead of where the pack is going.”

Trello acquires Butler to add power of automation

Trello, the organizational tool owned by Atlassian, announced an acquisition of its very own this morning when it bought Butler, an plug-in for an undisclosed amount.

What Butler brings to Trello is the power of automation, stringing together a bunch of commands to make something complex happen automatically. As Trello’s Michael Pryor pointed out in a blog post announcing the acquisition, we are used to tools like IFTTT, Zapier and Apple Shortcuts, and this will bring a similar type of functionality directly into Trello.

Screenshot: Trello

“Over the years, teams have discovered that by automating processes on Trello boards with the Butler Power-Up, they could spend more time on important tasks and be more productive. Butler helps teams codify business rules and processes, taking something that might take ten steps to accomplish and automating it into one click.” Pryor wrote.

This means that Trello can be more than a static organizational tool. Instead, it can move into the realm of light-weight business process automation. For example, this could allow you to move an item from your To Do board to your Doing board automatically based on dates, or to share tasks with appropriate teams as a project moves through its lifecycle, saving a bunch of manual steps that tend to add up.

The company indicated that it will be incorporating the Alfred’s capabilities directly into Trello in the coming months. It will make it available to all level of users including the free tier, but they promise more advanced functionality for Business and Enterprise customers when the integration is complete. Pryor also suggested that more automation could be coming to Trello. “Butler is Trello’s first step down this road, enabling every user to automate pieces of their Trello workflow to save time, stay organized and get more done.”

Atlassian bought Trello in 2017 for $425 million, but this acquisition indicates it is functioning quasi-independently as part of the Atlassian family.

Why you need a supercomputer to build a house

When the hell did building a house become so complicated?

Don’t let the folks on HGTV fool you. The process of building a home nowadays is incredibly painful. Just applying for the necessary permits can be a soul-crushing undertaking that’ll have you running around the city, filling out useless forms, and waiting in motionless lines under fluorescent lights at City Hall wondering whether you should have just moved back in with your parents.

Consider this an ongoing discussion about Urban Tech, its intersection with regulation, issues of public service, and other complexities that people have full PHDs on. I’m just a bitter, born-and-bred New Yorker trying to figure out why I’ve been stuck in between subway stops for the last 15 minutes, so please reach out with your take on any of these thoughts: @[email protected].

And to actually get approval for those permits, your future home will have to satisfy a set of conditions that is a factorial of complex and conflicting federal, state and city building codes, separate sets of fire and energy requirements, and quasi-legal construction standards set by various independent agencies.

It wasn’t always this hard – remember when you’d hear people say “my grandparents built this house with their bare hands?” These proliferating rules have been among the main causes of the rapidly rising cost of housing in America and other developed nations. The good news is that a new generation of startups is identifying and simplifying these thickets of rules, and the future of housing may be determined as much by machine learning as woodworking.

When directions become deterrents

Photo by Bill Oxford via Getty Images

Cities once solely created the building codes that dictate the requirements for almost every aspect of a building’s design, and they structured those guidelines based on local terrain, climates and risks. Over time, townships, states, federally-recognized organizations and independent groups that sprouted from the insurance industry further created their own “model” building codes.

The complexity starts here. The federal codes and independent agency standards are optional for states, who have their own codes which are optional for cities, who have their own codes that are often inconsistent with the state’s and are optional for individual townships. Thus, local building codes are these ever-changing and constantly-swelling mutant books made up of whichever aspects of these different codes local governments choose to mix together. For instance, New York City’s building code is made up of five sections, 76 chapters and 35 appendices, alongside a separate set of 67 updates (The 2014 edition is available as a book for $155, and it makes a great gift for someone you never want to talk to again).

In short: what a shit show.

Because of the hyper-localized and overlapping nature of building codes, a home in one location can be subject to a completely different set of requirements than one elsewhere. So it’s really freaking difficult to even understand what you’re allowed to build, the conditions you need to satisfy, and how to best meet those conditions.

There are certain levels of complexity in housing codes that are hard to avoid. The structural integrity of a home is dependent on everything from walls to erosion and wind-flow. There are countless types of material and technology used in buildings, all of which are constantly evolving.

Thus, each thousand-page codebook from the various federal, state, city, township and independent agencies – all dictating interconnecting, location and structure-dependent needs – lead to an incredibly expansive decision tree that requires an endless set of simulations to fully understand all the options you have to reach compliance, and their respective cost-effectiveness and efficiency.

So homebuilders are often forced to turn to costly consultants or settle on designs that satisfy code but aren’t cost-efficient. And if construction issues cause you to fall short of the outcomes you expected, you could face hefty fines, delays or gigantic cost overruns from redesigns and rebuilds. All these costs flow through the lifecycle of a building, ultimately impacting affordability and access for homeowners and renters.

Startups are helping people crack the code

Photo by Caiaimage/Rafal Rodzoch via Getty Images

Strap on your hard hat – there may be hope for your dream home after all.

The friction, inefficiencies, and pure agony caused by our increasingly convoluted building codes have given rise to a growing set of companies that are helping people make sense of the home-building process by incorporating regulations directly into their software.

Using machine learning, their platforms run advanced scenario-analysis around interweaving building codes and inter-dependent structural variables, allowing users to create compliant designs and regulatory-informed decisions without having to ever encounter the regulations themselves.

For example, the prefab housing startup Cover is helping people figure out what kind of backyard homes they can design and build on their properties based on local zoning and permitting regulations.

Some startups are trying to provide similar services to developers of larger scale buildings as well. Just this past week, I covered the seed round for a startup called Cove.Tool, which analyzes local building energy codes – based on location and project-level characteristics specified by the developer – and spits out the most cost-effective and energy-efficient resource mix that can be built to hit local energy requirements.

And startups aren’t just simplifying the regulatory pains of the housing process through building codes. Envelope is helping developers make sense of our equally tortuous zoning codes, while Cover and companies like Camino are helping steer home and business-owners through arduous and analog permitting processes.

Look, I’m not saying codes are bad. In fact, I think building codes are good and necessary – no one wants to live in a home that might cave in on itself the next time it snows. But I still can’t help but ask myself why the hell does it take AI to figure out how to build a house? Why do we have building codes that take a supercomputer to figure out?

Ultimately, it would probably help to have more standardized building codes that we actually clean-up from time-to-time. More regional standardization would greatly reduce the number of conditional branches that exist. And if there was one set of accepted overarching codes that could still set precise requirements for all components of a building, there would still only be one path of regulations to follow, greatly reducing the knowledge and analysis necessary to efficiently build a home.

But housing’s inherent ties to geography make standardization unlikely. Each region has different land conditions, climates, priorities and political motivations that cause governments to want their own set of rules.

Instead, governments seem to be fine with sidestepping the issues caused by hyper-regional building codes and leaving it up to startups to help people wade through the ridiculousness that paves the home-building process, in the same way Concur aids employee with infuriating corporate expensing policies.

For now, we can count on startups that are unlocking value and making housing more accessible, simpler and cheaper just by making the rules easier to understand. And maybe one day my grandkids can tell their friends how their grandpa built his house with his own supercomputer.

And lastly, some reading while in transit:

Pivotal announces new serverless framework

Pivotal has always been about making open-source tools for enterprise developers, but surprisingly, up until now, the arsenal has lacked a serverless component. That changed today with the alpha launch of Pivotal Function Service.

Pivotal Function Service is a Kubernetes-based, multi-cloud function service. It’s part of the broader Pivotal vision of offering you a single platform for all your workloads on any cloud,” the company wrote in a blog post announcing the new service.

What’s interesting about Pivotal’s flavor of serverless, besides the fact that it’s based on open source, is that it has been designed to work both on-prem and in the cloud in a cloud native fashion, hence the Kubernetes-based aspect of it. This is unusual to say the least.

The idea up until now has been that the large-scale cloud providers like Amazon, Google and Microsoft could dial up whatever infrastructure your functions require, then dial them down when you’re finished without you ever having to think about the underlying infrastructure. The cloud provider deals with whatever compute, storage and memory you need to run the function, and no more.

Pivotal wants to take that same idea and make it available in the cloud across any cloud service. It also wants to make it available on-prem, which may seem curious at first, but Pivotal’s Onsi Fakhouri says customers want that same abilities both on-prem and in the cloud. “One of the key values that you often hear about serverless is that it will run down to zero and there is less utilization, but at the same time there are customers who want to explore and embrace the serverless programming paradigm on-prem,” Fakhouri said. Of course, then it is up to IT to ensure that there are sufficient resources to meet the demands of the serverless programs.

The new package includes several key components for developers, including an environment for building, deploying and managing your functions, a native eventing ability that provides a way to build rich event triggers to call whatever functionality you require and the ability to do this within a Kubernetes-based environment. This is particularly important as companies embrace a hybrid use case to manage the events across on-prem and cloud in a seamless way.

One of the advantages of Pivotal’s approach is that Pivotal can work on any cloud as an open product. This is in contrast to the cloud providers like Amazon, Google and Microsoft, which provide similar services that run exclusively on their clouds. Pivotal is not the first to build an open-source Function as a Service, but they are attempting to package it in a way that makes it easier to use.

Serverless doesn’t actually mean there are no underlying servers. Instead, it means that developers don’t have to point to any servers because the cloud provider takes care of whatever infrastructure is required. In an on-prem scenario, IT has to make those resources available.