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4 key areas SaaS startups must address to scale infrastructure for the enterprise

By Ram Iyer
Prashant Pandey Contributor
Prashant Pandey is the head of engineering at Asana, a leading work management platform for teams. Prior to Asana, Prashant started and led the Bay Area team building Amazon DynamoDB, a fully managed NoSQL database service.

Startups and SMBs are usually the first to adopt many SaaS products. But as these customers grow in size and complexity — and as you rope in larger organizations — scaling your infrastructure for the enterprise becomes critical for success.

Below are four tips on how to advance your company’s infrastructure to support and grow with your largest customers.

Address your customers’ security and reliability needs

If you’re building SaaS, odds are you’re holding very important customer data. Regardless of what you build, that makes you a threat vector for attacks on your customers. While security is important for all customers, the stakes certainly get higher the larger they grow.

Given the stakes, it’s paramount to build infrastructure, products and processes that address your customers’ growing security and reliability needs. That includes the ethical and moral obligation you have to make sure your systems and practices meet and exceed any claim you make about security and reliability to your customers.

Here are security and reliability requirements large customers typically ask for:

Formal SLAs around uptime: If you’re building SaaS, customers expect it to be available all the time. Large customers using your software for mission-critical applications will expect to see formal SLAs in contracts committing to 99.9% uptime or higher. As you build infrastructure and product layers, you need to be confident in your uptime and be able to measure uptime on a per customer basis so you know if you’re meeting your contractual obligations.

While it’s hard to prioritize asks from your largest customers, you’ll find that their collective feedback will pull your product roadmap in a specific direction.

Real-time status of your platform: Most larger customers will expect to see your platform’s historical uptime and have real-time visibility into events and incidents as they happen. As you mature and specialize, creating this visibility for customers also drives more collaboration between your customer operations and infrastructure teams. This collaboration is valuable to invest in, as it provides insights into how customers are experiencing a particular degradation in your service and allows for you to communicate back what you found so far and what your ETA is.

Backups: As your customers grow, be prepared for expectations around backups — not just in terms of how long it takes to recover the whole application, but also around backup periodicity, location of your backups and data retention (e.g., are you holding on to the data too long?). If you’re building your backup strategy, thinking about future flexibility around backup management will help you stay ahead of these asks.

Spotify’s Clubhouse rival, Greenroom, tops 140K installs on iOS, 100K on Android

By Sarah Perez

Spotify’s recently launched live audio app and Clubhouse rival, Spotify Greenroom, has a long road ahead of it if it wants to take on top social audio platforms like Clubhouse, Airtime, Spoon and others, not to mention those from top social networks, like Twitter and Facebook. To date, the new Greenroom app has only been downloaded a total of 141,000 times on iOS, according to data from app intelligence firm Sensor Tower. This includes downloads from its earlier iteration, Locker Room — an app Spotify acquired to make its move into live audio.

On Android, Google Play data indicates the app has been installed over 100,000 times, but Sensor Tower cannot yet confirm this figure.

For comparison, Clubhouse today has 30.2 million total installs, 18.7 million of which are on iOS, Sensor Tower says.

Other top audio apps include Airtime, with 11.4 million iOS installs, out of a total of 14.3 million (including Android); and Spoon, with 7.6 million iOS installs, out of a total of  27.3 million.

International apps like UAE’s Yalla and China’s Lizhi are massive, as well, with the former sporting 48.1 total installs, 3.8 million of which are on iOS. The latter has 29.5+ million total installs, but only a handful on iOS.

There are other newcomers that have managed to stake smaller claims in the social audio space, too, including Fishbowl (759,000 total installs), Cappuccino (497,000 installs), Riff (339,000 installs) and Sonar (154,000 installs.)

Image Credits: Sensor Tower. The firm analyzed 34 social audio apps. The chart shows those with the most installs.  

Spotify Greenroom’s launch last month, meanwhile, seems to have attracted only a small fraction of Spotify’s larger user base, which has now grown to 365 million monthly active users.

The majority of Greenroom’s installs — around 106,000 — took place after Greenroom’s official launch on July 16, 2021 through July 25, 2021, Sensor Tower says. Counting only its Greenroom installs, the app is ranked at No. 12 among social audio apps. It follows Tin Can, which gained 127,000 installs since launching in early March.

Because Greenroom took over Locker Room’s install base, some portion of Greenroom’s total iOS installs (141K) included downloads that occurred when the app was still Locker Room. But that number is fairly small. Sensor Tower estimates Locker Room saw only around 35,000 total iOS installs to date. That includes the time frame of October 26, 2020 — the month when the sports chat app launched to the public — up until the day before Greenroom’s debut (July 15, 2021).

We should also point out that downloads are not the same thing as registered users, and are far short of active users. Many people download a new app to try it, but then abandon it shortly after downloading it, or never remember to open it at all.

That means the number of people actively using Greenroom at this time, is likely much smaller that these figures indicate.

Spotify declined to comment on third-party estimates.

While Sensor Tower looked at competition across social audio apps on the app stores, Spotify’s competition in the live audio market won’t be limited to standalone apps, of course.

Other large tech platforms have more recently integrated social audio into their apps, too, including Facebook (Live Audio Rooms), Twitter (Spaces), Discord (Stage Channels) and trading app Public. A comparison with Greenroom here is not possible, as these companies would have to disclose how many of their active users are engaging with live audio, and they have not yet done so.

Despite what may be a slower uptake, Greenroom shouldn’t be counted out yet. The app is brand-new, and has time to catch up if all goes well. (And if the market for live audio, in general, continues to grow — even though the height of Covid lockdowns, which prompted all this live audio socializing in the first place, seems to have passed.)

Spotify’s success or failure with live audio will be particularly interesting to watch given the potential for the company to cross-promote live audio shows, events, and artist-produced content through its flagship streaming music application. What sort of programming Greenroom may later include is still unknown, however.

Following Spotify’s acquisition of Locker Room maker Betty Labs, the company said it would roll out programmed content related to music, culture, and entertainment, in addition to sports. It also launched a Creator Fund to help fuel the app with new content. 

But so far, Spotify hasn’t given its users a huge incentive to visit Greenroom.

The company, during its Q2 2021 earnings, explained why. It said it first needed to get Greenroom stabilized for a “Spotify-sized audience,” which it why it only soft-launched the app in June. Going forward, Spotify says there will be “more tie-ins” with the main Spotify app, but didn’t offer any specifics.

“Obviously we’ll leverage our existing distribution on Spotify,” noted Spotify CEO Daniel Ek. “But this feels like a great way to learn, experiment and iterate, much faster than if we had to wait for a full on integration into the main app,” he added.

Facebook warns of ‘headwinds’ to its ad business from regulators and Apple

By Taylor Hatmaker

Facebook posted its second quarter earnings Wednesday, beating expectations with $29 billion in revenue.

The world’s biggest social media company was expected to report $27.8 billion in revenue for the quarter, a 50 percent increase from the same period in 2020. Facebook reported earnings per share of $3.61, which also bested expectations. The company’s revenue was $18.6 billion in the same quarter of last year.

In the first financial period to really reflect a return to quasi-economic normalcy after a very online pandemic year, Facebook met user growth expectations. At the end of March, Facebook boasted 2.85 billion monthly active users across its network of apps. At the end of its second quarter, Facebook reported 2.9 billion monthly active users, roughly what was expected.

The company’s shares opened at $375 on Wednesday morning and were down to $360 in a dip following the earnings report.

In spite of a strong quarter, Facebook is warning of change ahead — namely impacts to its massive ad business, which generated $28.5 billion out of the company’s $29 billion this quarter. The company specifically named privacy-focused updates to Apple’s mobile operating system as a threat to its business.

“We continue to expect increased ad targeting headwinds in 2021 from regulatory and platform changes, notably the recent iOS updates, which we expect to have a greater impact in the third quarter compared to the second quarter,” the company stated its investor report outlook.

On the company’s investor call, Facebook CEO Mark Zuckerberg pointed to Facebook’s plans to reduce its reliance on ad revenue, noting the company’s expanded efforts to attract and support content creators and its e-commerce plans in particular. “We want our platforms to be the best place for creators to make a living,” Zuckerberg said, adding that the company plans to monetize creator tools starting in 2023.

Zuckerberg also emphasized Facebook’s grand aspirations for social experiences in VR. “Virtual reality will be a social platform, which is why we’re so focused on building it,” Zuckerberg said.

No matter what Facebook planned to report Wednesday, the company is a financial beast. Bad press and user mistrust in the West haven’t done much to hurt its bottom line and the company’s ad business is looking as dominant as ever. Short of meaningful antitrust reform in the U.S. or a surging competitor, there’s little to stand in Facebook’s way. The former might still be a long shot given partisan gridlock in Congress, even with the White House involved, but Facebook is finally facing a threat from the latter.

For years, it’s been difficult to imagine a social media platform emerging as a proper rival to the company, given Facebook’s market dominance and nasty habit of acquiring competitors or brazenly copying their innovations, but it’s clear that TikTok is turning into just that. YouTube is huge, but the platforms matured in parallel and co-exist, offering complementary experiences.

TikTok hit 700 million monthly active users in July 2020 and surpassed three billions global downloads earlier this month, becoming the only non-Facebook owned app to do so, according to data from Sensor Tower. If the famously addictive short form video app can successfully siphon off some of the long hours that young users spend on Instagram and Facebook’s other platforms and make itself a cozy home for brands in the process, the big blue giant out of Menlo Park might finally have something to lose sleep over.

Snapchat adds My Places feature to Snap Map, recommending spots to visit

By Amanda Silberling

As more people are venturing out into the world this summer (safely, we hope!), Snapchat wants to make it easier for people to find restaurants, stores, parks and other interesting spots in their neighborhood. Today, Snapchat is starting to roll out the My Places feature on its Snap Map, which connects users with over 30 million businesses. Users can log their favorite spots, send them to friends, and find recommendations.

My Places has three main tabs: visited, favorites and popular. Visited lists places you’ve checked into on Snapchat, and favorites saves, well, your favorites. But the popular tab is particularly interesting because it marks the first time that Snapchat is using an algorithm to provide personalized recommendations to help people engage with the world around them. The algorithm considers where you are, what you’ve tagged or favorited already, and where your friends and other Snapchatters have visited.

This further differentiates the social-forward Snap Map from more established resources like Google Maps and Apple Maps, which you can’t really use to find out what restaurants your friends like. Sure, Snapchat can’t give you directions to that trendy sushi bar, but it’s not meant to, just like how Google Maps isn’t meant to show you what bar all your friends went to without you last night.

Image Credits: Snapchat

Snapchat shared survey results indicating that its users are more likely on average to engage in “post-pandemic” activities (is that a good thing?) and added that 44% of Snapchatters turn to the Snap Map to find places around them that they’re interested in.

With over 250 million monthly active users on Snap Map, the company announced an update in May called Layers, which lets partner companies add data directly to their own map. So far, Snapchat has collaborated with Ticketmaster and The Infatuation, a restaurant recommendation website — these partnerships help users see where they can find live entertainment, or what great restaurants are hidden in plain sight. Snapchat plans to further integrate Layers into Snap Map and My Places later this year.

Last week, Snap announced that during Q2 this year, it grew both revenue and daily active users at the highest rates it has achieved in the last four years. Year over year, the app grew 23%.

Shopify’s Q2 results beat estimates as e-commerce shines

By Alex Wilhelm

Canadian e-commerce juggernaut Shopify this morning reported its second-quarter financial performance. Like Microsoft and Apple in the wake of their after-hours earnings reports, its shares are having a muted reaction to the better-than-expected results.

In the second quarter of 2021, Shopify reported revenues of $1.12 billion, up 57% on a year-over-year basis. The company’s subscription products grew 70% to $334.2 million, while its volume-driven merchant services drove their own top line up 52% to $785.2 million.

Investors had expected Shopify to report revenue of $1.05 billion.

Shopify also posted an enormous second-quarter profit. Indeed, from its $1.12 billion in total revenues, Shopify managed to generate $879.1 million in GAAP net income. How? The outsized profit came in part thanks to $778 million in unrealized gains related to equity investments. But even with those gains filtered out, Shopify’s adjusted net income of $284.6 million more than doubled its year-ago Q2 result of $129.4 million. Shopify’s earnings per share sans unrealized gains came to $2.24, far ahead of an expected 97 cents.

After reporting those results, Shopify shares are up less than a point.

In light of somewhat muted reactions to Big Tech earnings surpassing expectations, it’s increasingly clear that investors were anticipating that leading tech companies would trounce expectations in the second quarter; their earnings beats were largely priced-in ahead of the individual reports.

The rest of Shopify’s quarter is a series of huge figures. In the second three-month period of 2021, the company posted gross merchandise volume (GMV) of $42.2 billion, up 40% compared to the year-ago period. That was more than a billion dollars ahead of expectations. And the company’s monthly recurring revenue (MRR) grew 67% to $95.1 million in the quarter. That’s quick.

Shopify is priced like the growth will continue. Using its Q2 revenue result to generate an annual run rate for the firm, Shopify is currently valued at around 43x its present top line. That’s aggressive for a company that generates the minority of its revenues from recurring software fees, an investor favorite. Instead, investors seem content to pay what is effectively top dollar for the company’s blend of GMV-based service revenues and more traditional software incomes.

Consider the public markets bullish on the continued pace of e-commerce growth.

It will be interesting to see how BigCommerce, a Shopify competitor and fellow public company, performs when it reports earnings in early August. Shares of BigCommerce are up more than 3% today in wake of Shopify’s results. Ironic given Shopify’s relaxed market reaction to its own results? Sure, but who said the public markets are fair?

Financial firms should leverage machine learning to make anomaly detection easier

By Ram Iyer
Bikram Singh Contributor
Bikram Singh is the CEO and co-founder of EZOPS. He has built and managed operational services and technology solutions for banks, hedge funds, asset managers, fund administrators and custodians.

Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions. Broadly speaking, a true anomaly is one that deviates from the norm of the expected or the familiar. Anomalies can be the result of incompetence, maliciousness, system errors, accidents or the product of shifts in the underlying structure of day-to-day processes.

For the financial services industry, detecting anomalies is critical, as they may be indicative of illegal activities such as fraud, identity theft, network intrusion, account takeover or money laundering, which may result in undesired outcomes for both the institution and the individual.

There are different ways to address the challenge of anomaly detection, including supervised and unsupervised learning.

Detecting outlier data, or anomalies according to historic data patterns and trends can enrich a financial institution’s operational team by increasing their understanding and preparedness.

The challenge of detecting anomalies

Anomaly detection presents a unique challenge for a variety of reasons. First and foremost, the financial services industry has seen an increase in the volume and complexity of data in recent years. In addition, a large emphasis has been placed on the quality of data, turning it into a way to measure the health of an institution.

To make matters more complicated, anomaly detection requires the prediction of something that has not been seen before or prepared for. The increase in data and the fact that it is constantly changing exacerbates the challenge further.

Leveraging machine learning

There are different ways to address the challenge of anomaly detection, including supervised and unsupervised learning.

Space Jam and the Fury of an Algorithm Scorned

By Brian Barrett
The reboot—along with Netflix’s The Mitchells vs. the Machines—portray vengeful AIs as jilted geniuses. That revolution shouldn’t be televised.

Facebook Messenger is stepping up its emoji game

By Amanda Silberling

If you can’t say it with words, say it with an emoji. Facebook is announcing a few minor updates today to its Messenger platform, which make it easier than ever to find the exact emoji you’re looking for when reacting to a friend’s message (let’s be real, there’s a big difference between the “crying laughing” and “crying” emoji). This includes a search bar for emoji reactions, and a recently used emojis section. And, if you weren’t let down by the long-awaited “Space Jam” sequel, you can sport your love for hoopster Bugs Bunny with a “Space Jam 2” chat theme, available both on Messenger and in Instagram DMs. Don’t get too excited though — even though this theme sets a basketball as the chat’s emoji, the long lost, beloved basketball mini game has not yet made its triumphant return to the Messenger app.

Image Credits: Facebook Messenger

It may not feel like there’s room for innovation in, um, the emoji space, but even Twitter has explored the option of allowing people to emoji-react to tweets. And as live audio has become ever present — from Clubhouse, to Twitter Spaces, to Spotify’s Greenroom — why not add audio to emojis?

Last week, Messenger debuted Soundmojis, which are what they sound like — emojis with sounds. On the Messenger app, you can use Soundmojis by clicking the smiley face icon in the chat box, which opens up the expressions menu. When you select the loudspeaker icon, you can select from just under 30 standard emojis, but when you click on them, they play sounds including “Brooklyn 99” quotes, Olivia Rodrigo clips, and lines from “Bridgerton.” The “X” emoji plays “Oh No” by Capone, a song that went viral on TikTok.

According to Facebook Messenger, people send more than 2.4 billion messages with emojis on the platform each day. That’s great and all, but if we can tap the car emoji to hear sounds from “Fast & Furious,” when will we be able to tap the soccer emoji to play “keepie uppie” again?

Okendo raises $5.3M to help DTC brands ween themselves off of Big Tech customer data

By Lucas Matney

While direct-to-consumer growth has exploded in the past year, some brands are finding there’s still plenty of room to forge ahead in building a more direct relationships with their customers.

Sydney-based Okendo has made a splash in this world by building out a popular customer reviews systems for Shopify sellers, but it’s aiming to expand its ambitions and tackle a much bigger problem with its first outside funding — helping brands scale the quality of their first-party data and loosen their reliance on tech advertising kingpins for customer acquisition and engagement.

“Most DTC brands are still very dependent on big tech,” CEO Matthew Goodman tells TechCrunch.

Gathering more customer reviews data directly from consumers has been the first part of the puzzle with its product that helps brands manage and showcase customer ratings, reviews, user-generated media and product questions. Moving forward Okendo is looking to help firms manage more of the web of cross-channel customer data they have, standardizing it and allowing them to give customers a more personalized experience when they shop with them.

via Okendo

“Merchants have goals and want to better understand their customers,” Goodman says. “As soon as a brand reaches a certain level of scale they’re dealing with unwieldy data.”

Goodman says that Apple’s App Tracking Transparency feature and Google’s pledge to end third-party cookie tracking has pushed some brands to get more serious about scaling their own data sets to insulate themselves from any sudden movements.

The company needs more coin in its coffers to take on the challenge, raising their first bout of funding since launching back in 2018. They’ve raised $5.3 million in seed funding led by Index Ventures. 2020 was a big growth year for the startup as e-commerce spending surged and sellers looked more thoughtfully at how they were scaling. The company tripled its ARR during the year and doubled its headcount. The bootstrapped company was profitable at the time of the raise, Goodman says.

Today, the company boasts more than 3,500 DTC brands in the Shopify network as customers, including heavyweights like Netflix, Lego, Skims, Fanjoy and Crunchyroll. The startup is tight-lipped on what their next product launches will look like, but plans to jump into two new areas in the next 12 months, Goodman says.

Zebra raises $1.1M in a pre-seed round for messaging that pairs photos with voice chat

By Taylor Hatmaker

A new voice-based social app that cites Clubhouse as its biggest inspiration offers a playful new way to stay in touch with close friends and family. Zebra leaves video out of the equation altogether, inviting users to snap on-the-fly photos and send them off paired with casual voice updates.

Zebra focuses on asynchronous sharing, but it also lets users call one another if they’re both already hanging out on the app. The result is a fun and casual way to stay in touch for anyone who doesn’t feel like accidentally getting sucked into Instagram’s endless, ad-strewn feed every time they want to give a friend a quick update.

For now Zebra is a two-person team consisting of CEO Dennis Gecaj, a product designer based in Berlin, and Amer Shahnawaz, Zebra’s head of engineering, who previously worked on Snap Maps at Snapchat. The pre-seed funding was led by Alexis Ohanian’s fresh early-stage venture firm Seven Seven Six, which the Reddit co-founder announced in June. The app will launch formally in August but is now open for preorders through the App Store and as a beta in TestFlight.

“It’s no secret that we are in the midst of an audio revolution, one that has ushered in a series of new audio-first social platforms and content vehicles,” Ohanian said, noting that Zebra’s unique blend of photos and voice is what caught his eye.

Gecaj sees voice-based social networking as a much richer alternative to text-dominant platforms. While products like Instagram allow voice messages and technically let users make voice calls by disabling the camera, voice usually plays second fiddle to video. But video calls are more taxing and require more commitment — it’s no coincidence more and more Zoom cameras blinked offline as the pandemic dragged on.

Unlike Clubhouse, which Gecaj calls a “huge inspiration, Zebra is social audio designed for your inner circle. “With everything opening back up we saw an incredible opportunity for an asynchronous format for that,” he told TechCrunch.

Gecaj hopes that Zebra’s “talking photos” can capture the collective imagination in a way that makes early growth natural. Anyone who downloads Zebra can invite friends individually without needing to share their full contact list (and they’ll need to — you can’t do anything on the app without friends). Because Zebra’s interface is so clean and streamlined, this process is painless and doesn’t necessitate any extra digging through menus.

The idea of a “zebra” — naturally, Zebra is trying to make “zebra” happen — is that people like to see what they are talking about. On a different messaging app, this would require sending a photo and then sending a voice message in quick succession. But on Zebra, sending a photo is the main thing you can do. The app opens right to the camera where you snap a picture. You then hold the photo to record a snippet of voice to go along with it and send it off to friends and family, who appear in a row beneath the camera.

Zebra isn’t worried about the prospect of talking people into downloading another app. Gecaj sees a natural split emerging as creators and audiences increasingly become the focus of social platforms that were initially designed to help friends stay in touch.

“I think the trend is a division between creator platforms where you go to be entertained and platforms you go to hang out with your friends,” Gecaj told TechCrunch.

On top of that, he hopes that Zebra’s dual focus on voice and photos, two aspects of social networking that platforms either don’t prioritize or are actively abandoning, can make it appealing for people who aren’t as interested in video.

“We really also think that text messaging doesn’t have the same emotion as voice… and voice has been really neglected,” Gecaj said. “There’s really a richness to voice, a power to voice that nothing else has.”

 

Pink Floyd drummer invests in Disciple Media, a platform aimed at the creator economy

By Mike Butcher

Much has been made of the rise of the “creator economy” in the last year. With the Pandemic biting, millions flooded online, looking for a way to make money or promote themselves. The podcasting world has exploded, and with it platforms like Patreon, Clubhouse, and many others. But the thorny problem remains: Do you really own your audience as a creator, or does the platform own you? Companies like Mighty Networks, Circle and Tribe have tried to address this, giving creators greater control than social networks do over their audiences. Now another joins the fray.

Disciple Media bills itself as a SaaS platform to enable online creators to build community-led businesses. It’s now raised $6 million in funding in what it calls a ‘large Angel round’. It already claims to have garnered 2 million members and 500 communities since launching in 2018. Investors include Nick Mason (drummer in Pink Floyd), Sir Peter Michael (CEO of Cray Computers, founder of classic FM, Quantel and Cosworth Engineering), Rob Pierre (founder and CEO of Jellyfish), and Keith Morris (ex. chairman Sabre Insurance). It’s also announced a new Chairman, Eirik Svendsen, a expert in online marketplaces, SaaS and the publishing and media industry.

On its communities so far it has American country star and American Idol judge Luke Bryan, Gor Tex, and Body by Ciara. The platform is also available on iOS and Android and comes with community management tools, a CRM, and monetization options. The company claims its creators are now “earning millions in revenue each year.”

Benji Vaughan, Founder and CEO said: “The scale and rapid growth of the creator economy is extraordinary, and today that growth is being driven by entrepreneurial creators looking to build independent businesses outside of Youtube and the social networks.”

Vaughan, a Techno DJ and artist-turned-entrepreneur, says he came up with the idea after building similar communities for clients. He says the data created on Disciple communities is owned entirely by the host who built the network, “removing third-party risk and allowing insights to be actioned immediately”.

He told me: “We are moving from a position of effectively having ‘gig economy workers for social networks’ to owners of businesses who use social networks for their needs, not the other way around. Therefore, these people are starting to leave social networks to build their businesses and using social networks as marketing channels, as the rest of the world does. Once that migration happens where they move away from social networks as their prime platform, they need a hub where their data is going to get pulled together, they have an audience, which we see as a community that connects with itself as much as they do with the host.”

He thinks the equivalent of Salesforce or HubSpot in the creative economy is going to be a community platform: “That’s where they’re going to aggregate all the information about their valuable audience or community engagement. So, we are looking to, over time, to build out something very akin to what HubSpot sites they have for tech companies or SaaS businesses: a complete package, a complete platform to manage your engagement with your users, grow your user base and then convert that into revenue.”

Rob Pierre, founder and CEO Jellyfish said: “Creating and engaging with your community digitally has never been more important. Disciple allows you to do both of those things with a fully functional, feature-rich platform which requires very little upfront capital expenditure. It also provides numerous options to monetize your community.”

How we built an AI unicorn in 6 years

By Ram Iyer
Alex Dalyac Contributor
Alex Dalyac is the CEO and co-founder of Tractable, which develops artificial intelligence for accident and disaster recovery.

Today, Tractable is worth $1 billion. Our AI is used by millions of people across the world to recover faster from road accidents, and it also helps recycle as many cars as Tesla puts on the road.

And yet six years ago, Tractable was just me and Raz (Razvan Ranca, CTO), two college grads coding in a basement. Here’s how we did it, and what we learned along the way.

Build upon a fresh technological breakthrough

In 2013, I was fortunate to get into artificial intelligence (more specifically, deep learning) six months before it blew up internationally. It started when I took a course on Coursera called “Machine learning with neural networks” by Geoffrey Hinton. It was like being love struck. Back then, to me AI was science fiction, like “The Terminator.”

Narrowly focusing on a branch of applied science that was undergoing a paradigm shift which hadn’t yet reached the business world changed everything.

But an article in the tech press said the academic field was amid a resurgence. As a result of 100x larger training data sets and 100x higher compute power becoming available by reprogramming GPUs (graphics cards), a huge leap in predictive performance had been attained in image classification a year earlier. This meant computers were starting to be able to understand what’s in an image — like humans do.

The next step was getting this technology into the real world. While at university — Imperial College London — teaming up with much more skilled people, we built a plant recognition app with deep learning. We walked our professor through Hyde Park, watching him take photos of flowers with the app and laughing from joy as the AI recognized the right plant species. This had previously been impossible.

I started spending every spare moment on image classification with deep learning. Still, no one was talking about it in the news — even Imperial’s computer vision lab wasn’t yet on it! I felt like I was in on a revolutionary secret.

Looking back, narrowly focusing on a branch of applied science undergoing a breakthrough paradigm shift that hadn’t yet reached the business world changed everything.

Search for complementary co-founders who will become your best friends

I’d previously been rejected from Entrepreneur First (EF), one of the world’s best incubators, for not knowing anything about tech. Having changed that, I applied again.

The last interview was a hackathon, where I met Raz. He was doing machine learning research at Cambridge, had topped EF’s technical test, and published papers on reconstructing shredded documents and on poker bots that could detect bluffs. His bare-bones webpage read: “I seek data-driven solutions to currently intractable problems.” Now that had a ring to it (and where we’d get the name for Tractable).

That hackathon, we coded all night. The morning after, he and I knew something special was happening between us. We moved in together and would spend years side by side, 24/7, from waking up to Pantera in the morning to coding marathons at night.

But we also wouldn’t have got where we are without Adrien (Cohen, president), who joined as our third co-founder right after our seed round. Adrien had previously co-founded Lazada, an online supermarket in South East Asia like Amazon and Alibaba, which sold to Alibaba for $1.5 billion. Adrien would teach us how to build a business, inspire trust and hire world-class talent.

Find potential customers early so you can work out market fit

Tractable started at EF with a head start — a paying customer. Our first use case was … plastic pipe welds.

It was as glamorous as it sounds. Pipes that carry water and natural gas to your home are made of plastic. They’re connected by welds (melt the two plastic ends, connect them, let them cool down and solidify again as one). Image classification AI could visually check people’s weld setups to ensure good quality. Most of all, it was real-world value for breakthrough AI.

And yet in the end, they — our only paying customer — stopped working with us, just as we were raising our first round of funding. That was rough. Luckily, the number of pipe weld inspections was too small a market to interest investors, so we explored other use cases — utilities, geology, dermatology and medical imaging.

Q3 IPO cycle starts strong with Couchbase pricing and Kaltura relisting

By Alex Wilhelm

Today we have new filings from Couchbase and Kaltura: Couchbase set an initial price range for its IPO, something we’ve been waiting for, and Kaltura’s offering is back from hiatus with a new price range and some fresh financial information to boot.

Both bits of news should help us get a handle on how the Q3 2021 IPO cycle is shaping up at the start.

TechCrunch has long expected the third quarter’s IPO haul to prove strong; investors said as 2020 closed that quarters one, three and four would prove very active in terms of public market exits this year. Then the second quarter surpassed expectations, with more companies going public than at least some market observers anticipated.

With that in mind, you can imagine why the newly launched Q3 could prove an active period.

So! Let’s start with a dig into the filing from NoSQL provider Couchbase, working to understand its first price range and what the numbers may say about market demand for technology debuts. Here’s our first look at the company’s value. Then we are taking the Kaltura saga back up, checking into the pricing and second-quarter results from the technology company that provides video streaming software and services.

Frankly, I’ve been waiting for these filings to drop. So, let’s cut the chat and get into the numbers:

Couchbase’s IPO price range

In its new S-1/A filing, Couchbase reports that it anticipates a $20 to $23 per share IPO price. With a maximum sale of just over 8 million shares, Couchbase could raise as much as $185.15 million in its public offering.

The company will have 40,072,801 shares outstanding after its IPO, not including 1,050,000 shares that are reserved for possible release. The math from here is simple. To calculate Couchbase’s possible simple IPO valuation we can just do a little multiplication:

  • Couchbase simple valuation at $20 per share: ~$802 million
  • Couchbase simple valuation at $23 per share: ~$922 million

If you want to include the company’s reserved shares, add $21 million to the first figure, and $24.2 million to the second. Notably, TechCrunch wrote before it priced that using a historical analog from the Red Hat-IBM sale — both Couchbase and Red Hat work in the OSS space — the company would be worth around $900 million. So, we were pretty close.

The most important API metric is time to first call

By Annie Siebert
Joyce Lin Contributor
Joyce Lin is head of developer relations at Postman.

API publishers among Postman’s community of more than 15 million are working toward more seamless and integrated developer experiences for their APIs. Distilled from hundreds of one-on-one discussions, I recently shared a study on increasing adoption of an API with a public workspace in Postman. One of the biggest reasons to use a public workspace is to enhance developer onboarding with a faster time to first call (TTFC), the most important metric you’ll need for a public API.

If you are not investing in TTFC as your most important API metric, you are limiting the size of your potential developer base throughout your remaining adoption funnel.

To understand a developer’s journey, let’s first take a look at factors influencing how much time and energy they are willing to invest in learning your technology and making it work.

  • Urgency: Is the developer actively searching for a solution to an existing problem? Or did they hear about your technology in passing and have a mild curiosity?
  • Constraints: Is the developer trying to meet a deadline? Or do they have unlimited time and budget to explore the possibilities?
  • Alternatives: Is the developer required by their organization to use this solution? Or are they choosing from many providers and considering other ways to solve their problem?

Developer journey to an API

With that context in mind, the following stages describe the developer journey of encountering a new API:

Step 1: Browse

A developer browses your website and documentation to figure out what your API offers. Some people gloss over this step, preferring to learn what your tech offers interactively in the next steps. But judgments are formed at this very early stage, likely while comparing your product among alternatives. For example, if your documentation and onboarding process appears comparatively unorganized and riddled with errors, perhaps it is a reflection of your technology.

Step 2: Signup

Signing up for an account is a developer’s first commitment. It signals their intent to do something with your API. Frequently going hand-in-hand with the next step, signing up is required to generate an API key.

Step 3: First API call

Making the first API call is the first payoff a developer receives and is oftentimes when developers begin more deeply understanding how the API fits into their world. Stripe and Algolia embed interactive guides within their developer documentation to enable first API calls. Stripe and Twitter also use Postman public workspaces for interactive onboarding. Since many developers already use Postman, experiencing an API in familiar territory gets them one step closer to implementation.

How Retail Zipline’s Series A pitch deck ticked every box for Emergence Capital

By Jordan Crook

Melissa Wong spent more than a decade working for major retail brands before founding Retail Zipline. That kind of outrageous advantage — a complete understanding of the industry — is something that investors struggle to resist in a vertical SaaS company. At least, according to Emergence Capital investor Lotti Siniscalco.

Wong and Siniscalco joined us on a recent episode of Extra Crunch Live and went into detail on why Emergence was eager to finance Retail Zipline’s Series A round, walking us through Zipline’s Series A pitch deck and sharing which slides and bits clinched the deal.

Extra Crunch Live is a weekly virtual event series meant to help founders build better venture-backed businesses. We sit down with investors and the founders they finance to hear what brought them together, what they saw in each other and how they work together moving forward. We also host the ECL pitch-off, where founders in the audience can pitch their startups to our outstanding speakers.

Extra Crunch Live is accessible to everyone on a live basis, but the on-demand content is reserved exclusively for Extra Crunch members. You can check out the July slate here and see the full ECL library here.

Stand up, stand out

During Wong’s fundraising process, Zipline was also attending a big industry conference. Emergence suggested that they do a virtual pitch meeting while Wong was at the trade show, but Wong pushed back, insisting on an in-person pitch meeting. Not only did she know that she would deliver a better pitch in person, but she didn’t want to squander the limited amount of time she had at the trade show with potential clients and partners.

“She pointed to the screen projected behind her to help us stay on the most relevant piece of information. The way she did it really made us stay with her. Like, we couldn’t break eye contact.”

Once the in-person meeting did take place, Wong surprised the Emergence team. For one, she stood up to pitch. Wong explained that her co-founder is a bigger guy, and she’s a smaller woman, and she feels more confident and comfortable presenting from a standing position.

“She was one of the few or maybe the only CEO who ever stood up to pitch the entire team,” said Siniscalco. “She pointed to the screen projected behind her to help us stay on the most relevant piece of information. The way she did it really made us stay with her. Like, we couldn’t break eye contact.”

In terms of delivery, Wong had already made an impact. But the content of the deck, and her experience in retail, clinched the deal.

“I look for an unfair reason for a founder to be the perfect person to build this product,” said Siniscalco. “Wong gave us her background in the first slide, and I knew quickly that she was a credible person in the retail industry. Then, what I look for in a pitch, is customer love.”

Siniscalco said the combination of that unfair advantage and intense customer love is highly correlated with a very positive outcome for a company.

“When we first started out, I was really insecure because I came from the industry versus coming from a lot of Silicon Valley knowledge,” said Wong. “In retrospect, I really underestimated the competitive advantage of coming from the industry. People said it to me, but I didn’t understand what that resulted in. But it resulted in the numbers in our deck, because I know what customers want, what they want to buy next, how to keep them happy and I was able to be way more capital-efficient.”

The Zipline deck

Zipline’s entire deck (with some minor redactions) is embedded below. You can swipe on through at your leisure, but the real value here (in my humble opinion) is Siniscalco’s breakdown of how she reacted to the information in the deck. I’ll relay that here in text, but I also strongly suggest you watch (at least) the first half of the episode below to hear the founder/investor duo walk us through this deck.

Achieving digital transformation through RPA and process mining

By Ram Iyer
Alp Uguray Contributor
Alp Uguray is an award-winning technologist, adviser and investor with 2x UiPath (MVP) Most Valuable Professional Award and is a globally recognized expert on intelligent automation, AI (artificial intelligence), RPA, process mining and enterprise digital transformation.

Understanding what you will change is most important to achieve a long-lasting and successful robotic process automation transformation. There are three pillars that will be most impacted by the change: people, process and digital workers (also referred to as robots). The interaction of these three pillars executes workflows and tasks, and if integrated cohesively, determines the success of an enterprisewide digital transformation.

Robots are not coming to replace us, they are coming to take over the repetitive, mundane and monotonous tasks that we’ve never been fond of. They are here to transform the work we do by allowing us to focus on innovation and impactful work. RPA ties decisions and actions together. It is the skeletal structure of a digital process that carries information from point A to point B. However, the decision-making capability to understand and decide what comes next will be fueled by RPA’s integration with AI.

From a strategic standpoint, success measures for automating, optimizing and redesigning work should not be solely centered around metrics like decreasing fully loaded costs or FTE reduction, but should put the people at the center.

We are seeing software vendors adopt vertical technology capabilities and offer a wide range of capabilities to address the three pillars mentioned above. These include powerhouses like UiPath, which recently went public, Microsoft’s Softomotive acquisition, and Celonis, which recently became a unicorn with a $1 billion Series D round. RPA firms call it “intelligent automation,” whereas Celonis targets the execution management system. Both are aiming to be a one-stop shop for all things related to process.

We have seen investments in various product categories for each stage in the intelligent automation journey. Process and task mining for process discovery, centralized business process repositories for CoEs, executives to manage the pipeline and measure cost versus benefit, and artificial intelligence solutions for intelligent document processing.

For your transformation journey to be successful, you need to develop a deep understanding of your goals, people and the process.

Define goals and measurements of success

From a strategic standpoint, success measures for automating, optimizing and redesigning work should not be solely centered around metrics like decreasing fully loaded costs or FTE reduction, but should put the people at the center. To measure improved customer and employee experiences, give special attention to metrics like decreases in throughput time or rework rate, identify vendors that deliver late, and find missed invoice payments or determine loan requests from individuals that are more likely to be paid back late. These provide more targeted success measures for specific business units.

The returns realized with an automation program are not limited to metrics like time or cost savings. The overall performance of an automation program can be more thoroughly measured with the sum of successes of the improved CX/EX metrics in different business units. For each business process you will be redesigning, optimizing or automating, set a definitive problem statement and try to find the right solution to solve it. Do not try to fit predetermined solutions into the problems. Start with the problem and goal first.

Understand the people first

To accomplish enterprise digital transformation via RPA, executives should put people at the heart of their program. Understanding the skill sets and talents of the workforce within the company can yield better knowledge of how well each employee can contribute to the automation economy within the organization. A workforce that is continuously retrained and upskilled learns how to automate and flexibly complete tasks together with robots and is better equipped to achieve transformation at scale.

The Pentagon Scrubs a Cloud Deal and Looks to Add More AI

By Tom Simonite
The JEDI program had become a legal and political morass. Microsoft won the $10 billion contract, but Amazon and Oracle sued to block the deal.
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