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Newlab and The Boston Globe team up to launch AI tools startup Applied XLabs
Applied XLabs is a new startup building tools that can automate data-gathering for journalists — and eventually, for knowledge workers in other industries.
The company is emerging from Brooklyn-based Newlab, with The Boston Globe as its launch partner. It will be led by Francesco Marconi (pictured above), who was previously R&D chief at The Wall Street Journal and head of AI strategy at the Associated Press.
Marconi told me that there’s a tremendous amount of data out there that could be useful to journalists, whether that’s inside public company filings or academic climate change research. But data-driven journalism remains a sliver of the industry, because “only a handful of organizations have the internal resources to create these types of tools, these types of analyses.”
The plan is for Applied XLabs to develop products to help newsrooms, starting with The Globe, automatically pull data and generate insights.
Vinay Mehra, president of The Boston Globe, said the hope is to use AI to improve the information that Globe journalists provide to different communities.
For example, Mehra said that The Globe has been expanding its coverage in Rhode Island, partly in response to the disappearance of local newspapers and the resulting “news deserts.” When the team started talking to the community about what kind of coverage they wanted to see, they came up with a long list of ideas like restaurant openings and closings. (That’s something news startup Hoodline, co-founded by Extra Crunch Managing Editor Eric Eldon, has also tried to tackle with data and automation.)
But providing comprehensive coverage in these areas is tough with a small newsroom, Mehra said: “We can’t keep throwing journalists at this.” So the idea is to “mine that data” and make existing journalists more effective.
At the same time, he emphasized that he doesn’t see AI as a way to replace journalists or justify newsroom cuts, and he noted that The Globe continues to hire.
“We can’t sit back and ignore these technologies that are coming out every day,” Mehra said. “The opportunity here is to redefine what is possible with AI, to expand our own thinking and horizons around how we do journalism today and how we serve these communities.”
Marconi added that ultimately, these tools could also be sold to knowledge workers in a variety of industries.
“The same way that you have Salesforce for managing the sales process, we are building the platform for knowledge workers,” he said. “The reason why it’s so important to start with news and why we’re working with journalists [is] the threshold is really, really high. If you are able to build products and seeds of information that editors can use and sign off on, then you can quickly expand into other industries.”
Applied XLabs is also the first startup to emerge from Newlab’s venture studio program. When we first visited Newlab back in 2016, it described itself as a workspace for companies in robotics, AI and other fields. Now it has created a studio model where it aims to bring together “diverse stakeholders” to create new companies in frontier tech.
“There is a substantial investment from Newlab, and in addition to capital, Newlab is providing all of the back-office services,” Marconi said. “I get the stability of an established company with the freedom, flexibility and creativity of a new venture.”
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London-based Gyana raises $3.9M for a no-code approach to data science
Coding and other computer science expertise remain some of the more important skills that a person can have in the working world today, but in the last few years, we have also seen a big rise in a new generation of tools providing an alternative way of reaping the fruits of technology: “no-code” software, which lets anyone — technical or non-technical — build apps, games, AI-based chatbots, and other products that used to be the exclusive terrain of engineers and computer scientists.
Today, one of the newer startups in the category — London-based Gyana, which lets non-technical people run data science analytics on any structured dataset — is announcing a round of £3 million to fuel its next stage of growth.
Led by U.K. firm Fuel Ventures, other investors in this round include Biz Stone of Twitter, Green Shores Capital and U+I , and it brings the total raised by the startup to $6.8 million since being founded in 2015.
Gyana (Sanskrit for “knowledge”) was co-founded by Joyeeta Das and David Kell, who were both pursuing post-graduate degrees at Oxford: Das, a former engineer, was getting an MBA, and Kell was doing a Ph. D. in physics.
Das said the idea of building this tool came out of the fact that the pair could see a big disconnect emerging not just in their studies, but also in the world at large — not so much a digital divide, as a digital light year in terms of the distance between the groups of who and who doesn’t know how to work in the realm of data science.
“Everyone talks about using data to inform decision making, and the world becoming data-driven, but actually that proposition is available to less than one percent of the world,” she said.
Out of that, the pair decided to work on building a platform that Das describes as a way to empower “citizen data scientists,” by letting users upload any structured data set (for example, a .CSV file) and running a series of queries on it to be able to visualise trends and other insights more easily.
While the longer term goal may be for any person to be able to produce an analytical insight out of a long list of numbers, the more practical and immediate application has been in enterprise services and building tools for non-technical knowledge workers to make better, data-driven decisions.
To prove out its software, the startup first built an app based on the platform that it calls Neera (Sanskrit for “water”), which specifically parses footfall and other “human movement” metrics, useful for applications in retail, real estate and civic planning — for example to determine well certain retail locations are performing, footfall in popular locations, decisions on where to place or remove stores, or how to price a piece of property.
Starting out with the aim of mid-market and smaller companies — those most likely not to have in-house data scientists to meet their business needs — startup has already picked up a series of customers that are actually quite a lot bigger than that. They include Vodafone, Barclays, EY, Pret a Manger, Knight Frank and the UK Ministry of Defense. It says it has some £1 million in contracts with these firms currently.
That, in turn, has served as the trigger to raise this latest round of funding and to launch Vayu (Sanskrit for “air”) — a more general purpose app that covers a wider set of parameters that can be applied to a dataset. So far, it has been adopted by academic researchers, financial services employees, and others that use analysis in their work, Das said.
With both Vayu and Neera, the aim — refreshingly — is to make the whole experience as privacy-friendly as possible, Das noted. Currently, you download an app if you want to use Gyana, and you keep your data local as you work on it. Gyana has no “anonymization” and no retention of data in its processes, except things like analytics around where your cursor hovers, so that Gyana knows how it can improve its product.
“There are always ways to reverse engineer these things,” Das said of anonymization. “We just wanted to make sure that we are not accidentally creating a situation where, despite learning from anaonyised materials, you can’t reverse engineer what people are analysing. We are just not convinced.”
While there is something commendable about building and shipping a tool with a lot of potential to it, Gyana runs the risk of facing what I think of as the “water, water everywhere” problem. Sometimes if a person really has no experience or specific aim, it can be hard to think of how to get started when you can do anything. Das said they have also identified this, and so while currently Gyana already offers some tutorials and helper tools within the app to nudge the user along, the plan is to eventually bring in a large variety of datasets for people to get started with, and also to develop a more intuitive way to “read” the basics of the files in order to figure out what kinds of data inquiries a person is most likely to want to make.
The rise of “no-code” software has been a swift one in the world of tech spanning the proliferation of startups, big acquisitions, and large funding rounds. Companies like Airtable and DashDash are aimed at building analytics leaning on interfaces that follow the basic design of a spreadsheet; AppSheet, which is a no-code mobile app building platform, was recently acquired by Google; and Roblox (for building games without needing to code) and Uncorq (for app development) have both raised significant funding just this week. In the area of no-code data analytics and visualisation, there are biggies like Tableau, as well as Trifacta, RapidMiner and more.
Gartner predicts that by 2024, some 65% of all app development will be made on low- or no-code platforms, and Forrester estimates that the no- and low-code market will be worth some $10 billion this year, rising to $21.2 billion by 2024.
That represents a big business opportunity for the likes of Gyana, which has been unique in using the no-code approach specifically to tackle the area of data science.
However, in the spirit of citizen data scientists, the intention is to keep a consumer version of the apps free to use as it works on signing up enterprise users with more enhanced paid products, which will be priced on an annual license basis (currently clients are paying between $6,000 and $12,000 depending on usage, she said).
“We want to do free for as long as we can,” Das said, both in relation to the data tools and the datasets that it will offer to users. “The biggest value add is not about accessing premium data that is hard to get. We are not a data marketplace but we want to provide data that makes sense to access,” adding that even with business users, “we’d like you to do 90% of what you want to do without paying for anything.”
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A look at Made Renovation, which just raised $9 million in seed funding to zero in on bathroom remodels
Made Renovation, a new, San Francisco-based company, thinks it has found a profitable way to help homeowners get done something that busy general contractors in the Bay Area won’t otherwise make time for, which is bathroom remodels.
Why they typically pass on these: they have too many entire homes, or, at least, entire floors, to build for affluent regional homeowners who’ve kept the construction industry buzzing for years.
It’s a problem that founders Roger Dickey, who previously co-founded Gigster, and Sagar Shah, who previously founded Quad, think they can solve through technology, naturally. Their big idea: create bathroom templates that customers can customize but whose scope and costs are generally understood, line up these customers, then hire general contractors who are willing to focus only on these bathrooms.
It’s an idea that’s picking up traction with these GCs, says Dickey, who explains it this way: “General contractors generally see net margin of 3%” no matter the size of the job, owing to unforeseen hurdles, like pipes that suddenly need to be rebuilt, drains that need to be dug and materials that don’t ship on schedule.
In addition to timing issues, GCs are also often dealing with frustrated building owners who might underestimate a project’s costs, particularly in California, where construction bills often cause sticker shock.
Made Renovation sees an opportunity to make both the lives of GCs and homeowners easier. Through pre-negotiated pricing, volume and materials handling (it right now rents part of a warehouse where it receives goods), it’s promising GCs a “reasonable margin” so they can not only pay their crews but live a higher quality of life themselves.
Meanwhile, per the plan, customers need only choose from the company’s “modern” collection, its more traditional “heritage”design or its “artisan” collection — all of which can be customized — then sit back while their long-neglected bathrooms are remade.
Whether Made Renovation can pull off its grand vision is a giant question mark. The construction industry is nothing if not messy, and in addition to convincing GCs of its merits, Made Renovation — like any marketplace company — has to strike the right balance between customer demand and supply as it gets off the ground.
In the meantime, investors clearly think it has promise. Led by Base10 Partners and with participation from Felicis Ventures, Founders Fund and some individual investors, the company has already raised $9 million in seed funding across two tranches.
Part of that capital is on display right now in San Francisco, where Made Renovation today opened its doors to customers who want to check out its design ideas and, if all goes as planned, will begin lining up their own home improvement projects. Customers simply pick a collection, Made Renovation then puts together a “mood board” of materials from that collection, sends out a 3D rendering of what to expect, then goes into build mode with its GC partners.
As for what happens when that build goes awry, Dickey says Made Renovation has it covered. Most notably, while it guarantees the work to its own customers, the GCs with whom it works guarantee their work to Made Renovation.
Dickey also notes that while the startup “may lose money on some projects,” he stresses there are caveats that customers agree to at the outset. Among these, he says, “We can’t X-ray their walls and see if they don’t have wiring up to code. We don’t cover dry rot in walls.” Technology, suggests Dickey, can only do so much.
If you’re in the Bay Area and want to check out its new storefront, it’s on Chestnut Street in SF, in the city’s Marina district. The company hopes to perfect its model in the Bay Area, says Dickey, then expand into other regions. As for why Made Renovation decided to tackle one of the most challenging U.S. markets first, he suggests it’s the best way to test its mettle. “I like the idea of starting a company here, because if we can make it work here, I think we can succeed anywhere.”
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Grab your ticket: Only one week to TC Sessions: Robotics + AI 2020
It’s T-minus one week to the big day, March 3, when more than 1,000 startuppers will convene in Berkeley, Calif. for TC Sessions: Robotics + AI 2020. We’re talking a hefty cross-section representing big companies and exciting new startups. We’re talking some of the most innovative thinkers, makers, researchers, investors and influencers — all focused on creating the future of these two world-changing technologies.
Don’t miss out on this one-day conference of interviews, panel discussions, Q&As, workshops and demos dedicated to every aspect of robotics and AI. General admission tickets cost $345. Snag your ticket now and save, because prices go up at the door. Want to save even more? Save 15% when you buy four or more tickets. Are you a student? Grab a ticket for just $50.
What do we have planned for this TC Session? Here’s a small sample of the fab programming that awaits you, and be sure to check out the full TC Session agenda here.
- Q&A with Founders: This is your chance to ask questions of Sébastien Boyer, co-founder and CEO of FarmWise and Noah Ready-Campbell, founder and CEO of Built Robotics — some of the most successful robotics founders on our stage.
- Disney Robotics: Imagineers from Disney will present state-of-the-art robotics built to populate its theme parks.
- Investing in Robotics and AI: Lessons from the Industry’s VCs: Dror Berman, founding partner at Innovation Endeavors, Jocelyn Goldfein, managing director at Zetta Venture Partners and Eric Migicovsky, general partner at Y Combinator will discuss the rising tide of venture capital funding in robotics and AI. The investors bring a combination of early-stage investing and corporate venture capital expertise, sharing a fondness for the wild world of robotics and AI investing.
And — new this year — don’t miss watching the finalists from our Pitch Night competition. Founders of these early-stage companies, hand-picked by TechCrunch editors, will take the stage and have just five minutes to present their wares.
With just one more week until TC Sessions: Robotics + AI 2020 kicks off, you don’t have much time left to save on tickets. Why pay more at the door? Buy your ticket now and join the best and brightest for a full day dedicated to all things robotics.
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ShapeMeasure’s smart tool and robotic cutter let contractors measure once and cut never
As much as we’d all like to believe that our houses are built with perfectly square angles and other highly regular measurements, that’s rarely the case — which makes remodeling complex and tedious. ShapeMeasure hopes to alleviate that pain with a device that automatically measures a space and a robotic mill that cuts the required lumber precisely to size, shortening and easing the process by huge amounts.
Founder Ben Blumer, who was exposed to the art of building and repair early by his father, a general contractor, had a brainwave that became the company during some renovations of his own.
“I was shocked to see our flooring installer, who had 10 years of experience, and was excellent at what he did, take over an hour to install a single stair,” Blumer said. “I started thinking, ‘a little bit of technology could go a long way here.’ ”
Finding himself at the time free to work on such a project, he recruited a former general contractor friend and applied to HAX, which soon shipped them off to Shenzhen to pursue their idea.
The main issue is stairs: they’re tricky, and especially in older homes can be pretty off-kilter. So although you know each stair is about 35 inches wide, it might be 35 and 3/64 inches, while the next one could be 34 and 61/64. Likewise, the angles might be ever so slightly off the 90 degrees or whatever they theoretically should be. Painstakingly measuring every single stair and manually cutting wood to those many slightly different dimensions is extremely time-consuming. The tool ShapeMeasure built makes it literally a push-button affair.
The device they settled on is essentially a super-precise lidar that measures around itself in wide arc, and the exact details of which comprise part of the company’s secret sauce. This gives the precise dimensions and attachment angles of the area around it, in the first intended use case a stair. The design, helped along by HAX’s Noel Joyce, looks a bit like a giant Dust Buster by way of the original “Alien.”
Obviously his shirt contradicts my headline, but if you think about the cutting as an automated process rather than something a person has to do, mine makes sense.
“We were working with Noel Joyce, HAX’s lead industrial designer. We wanted a product that looked and felt like a tool. We figured, if you’re trying to convince contractors to try something new, it should feel familiar,” Blumer said. “We spent hundreds of hours sourcing parts and re-engineering our scanning mechanism so that it could fit into Noel’s beautiful form factor. Turns out, contractors don’t care what it looks like. They liked the design, but were way more excited for the functionality.”
Once the shapes are scanned in and checked, that information can be beamed off to ShapeMeasure’s other device, a robotic lumber sizing system that cuts wood into the exact size and shape necessary to fit together as stairs. Of course, the contractor still has to bring them to the location and attach them by whatever means they see fit, but what was once a process with perhaps hundreds of steps has been simplified by an order of magnitude.
The machine is similar to other lumber-cutting devices, but simpler and easier to operate.
“There are lots of automatic cutting systems — often big, heavy, expensive and operated by professional CNC technicians. To cut flooring on a machine like that involves setting up jigs, clamping and reclamping each board, and generating custom gcode for each stair we cut,” Blumer said. They can be several times more costly and difficult to employ. “The cutting solution we’re building is compact, requires no clamping, and can be operated with just a few hours of training.”
It’s not just about length and width, either — molding and other flourishes on the stairs can make complex cuts necessary that would be impractical or at the very least extremely time-consuming to attempt manually.
Examples of complex cuts made by the ShapeMeasure machine.
The result is that the installation process from start to finish is about four times faster, they determined. If this seems a bit optimistic, know that it isn’t just armchair theorizing — they were careful to back up these numbers from the start.
“We take our speedup data really seriously,” said Blumer. “This is our top metric! One of the first purchases I made for the company was a dozen stopwatches. We’ve done installations in the ShapeMeasure lab and on real, messy construction sites — filming, timing and logging every moment.”
Interestingly, the precut lumber made other improvements possible — the team designed a bucket to accommodate the increased rate at which the installer uses glue and other parts. It’s a bit like if you improved painting speed so much that your new bottleneck was mixing and pouring the paint into roller trays fast enough.
Currently the company is working on establishing standard practices and packaging so that a ShapeMeasure “microfactory” can be set up easily anywhere in the country on short notice. And they’re “considering” raising money before then to accelerate the process. Blumer built the prototype with his own money and they pulled in a bit from HAX and then a small pre-seed round to get things started.
With luck and a bit of elbow grease, ShapeMeasure could turn out to be a real differentiator in the contractor space — every hour counts, as does every dollar in an estimate.
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Lerer Hippeau leads $6M investment in Pinterest-like digital asset manager Air
When it comes to the so-called “consumerization of the enterprise,” a workplace tool that looks an awful lot like Pinterest seems like it would be the trend’s final form. Brooklyn-based Air is building a digital asset manager for communications teams that aren’t satisfied with more general cloud storage options and want something that can show off visual files with a bit more pizzazz.
The startup tells TechCrunch that they have closed $6 million in funding led by Lerer Hippeau . RedSea Ventures, Advancit Capital and WndrCo also participated.
General-purpose cloud storage options from Google or Dropbox don’t always handle digital assets well — especially when it comes to previewing items, and Air’s more focused digital asset management competitors often require dedicated managers inside the org, the company says. Air has a pretty straightforward interface that looks more like a desktop site from Facebook or Pinterest, with a focus on thumbnails and video previews that’s simple and sleek.
Air is trying to capitalize on the trend toward greater à la carte software spend for teams looking to phase in products with very specific toolsets. The team is generally charging $10 per user per month, with 100GB of storage included.
“Adobe is an amazing suite of products, but with the idea that companies are mandating the tools that their employees use versus letting their employees choose — it makes a lot of sense that teams are going to ultimately end up having more autonomy and creating better work when they’re using tools that they care about,” Lerer Hippeau managing partner Ben Lerer tells TechCrunch.
Air lets customers migrate files from Dropbox or Google Drive to its AWS-hosted storage platform, which displays files like photos, videos, PDFs, fonts and other visual assets as Pinterest-esque boards. The app is a way to view and store files, but Air’s platform play focuses pretty heavily on giving co-workers the ability to comment and tag assets. Collaborating around files is a pretty easy sell; a couple of users discussing which photo they like best for a particular marketing campaign doesn’t require too much imagination.
The team has been focusing largely on attracting users in roles like brand marketing managers, content coordinators and social media managers as a way of infiltrating and scaling vertically inside marketing departments.
“What Airtable did to spreadsheets and what Notion did to docs, we’re doing for visual work,” CEO Shane Hegde told TechCrunch in an interview. “As we think about how we differentiate, it’s really that we’re a workspace collaboration tool, we’re not just cloud storage or digital asset management…”
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Chicago’s M1 Finance, a consumer-focused fintech platform, reaches $1B under management
Eagle-eyed readers will recall that we mentioned M1 Finance earlier today in our look at a few trends in the fintech industry. We’re back with the firm this afternoon as it has a bit of news that’s worth discussing.
Chicago-based M1 Finance announced today that it has reached the $1 billion assets under management mark, or AUM. Reaching AUM thresholds provides useful milestones that we can use to track the progress of various players in the fintech and finservices worlds.
M1 is an interesting company, bringing together a number of products to form a single platform. Its hybrid nature makes comparing its AUM to other companies’ histories a bit dicey. Still, for reference, Wealthfront, a roboadvisor, announced that it started 2013 with AUM of $100 million, and closed that year with $538 million. By mid-2014, Wealthfront had $1 billion AUM. Today it has over $20 billion.
So, the numbers matter, and reaching thresholds can help us understand where a company is in its maturity cycle.
Let’s talk about M1 Finance’s AUM growth, its revenue growth and its product model. It’s a neat company with a history of efficient growth.
Growth, product
We’ll start with product, as how the company approaches its feature-set helps explain how the service is priced, which in turn helps us grok the company’s growth.
M1 is not a roboadvisor, or a simple neobank, or a lending product; it’s all three at once, providing effectively the digital equivalent of a full-service bank, admittedly in the form of an online experience instead of a brick-and-mortar outlet. M1 users can open investment accounts, checking accounts, get a debit card and borrow money against their investment portfolios; it’s a cohesive feature set.
And one that lets M1 price its products lower as a group than it could individually. During a call with M1’s CEO Brian Barnes about the company’s AUM milestone, the executive connected the company’s long-term vision to its ability to price aggressively. (All fintechs are expanding their platforms, it’s worth noting, meaning that, in time, nearly every fintech player will offer an array of services; Wealthfront, famous for its work in roboadvising, now also offers savings and borrowing capabilities.)
Barnes said that M1 has long wanted to “manage the bulk of [its users’] financial assets, not create a sort of low-friction acquisition hook” to bring in smaller-dollar accounts. This, in turn, means that M1 can have higher per-user sums on its books, which, it appears, helped the company reduce prices on a per-product basis.
Here’s Barnes connecting per-account totals to pricing:
Managing more of someone’s financial assets, and financial life, is going to be more economical. What it allows us to do is maintain lower margins per product, but have enough margin on the entire financial relationship that we can build a very sustainable durable, long-lasting business.
That’s neat! And folks with lots of money expect low fees, especially in the Robinhood-era, so the setup probably helps with attracting users.
Revenue
Summing so far, M1 runs a broad set of financial products, attracting more dollars-per-user than other companies, perhaps, which lets it charge, in its view, lower prices.
How low? Barnes told TechCrunch that his company is “building [its] business model to make 1% of assets we manage [into] top line. So every billion bucks on the platform will be 10 million dollars in recurring revenue. And it is a relatively linear relationship.” The CEO later extended the point, saying that when his firm has $10 billion in AUM, it will generate $100 million.
This means that as M1 scales, we’ll be able to know with reasonable confidence how much revenue it’s driving.
The company charges in the manner you’d expect, with incomes from loaning money, interchange and a SaaS-product called M1 Plus that lowers some fees and provides interest on checking accounts, costing $125 yearly.
Now that M1 is big enough to matter, it has to double, and then double again. We’ll know how well that’s going based on how quickly the company reaches the $2 billion mark.
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Cartesiam helps developers bring AI to microcontrollers
Cartesiam, a startup that aims to bring machine learning to edge devices powered by microcontrollers, has launched a new tool for developers who want an easier way to build services for these devices. The new NanoEdge AI Studio is the first IDE specifically designed for enabling machine learning and inferencing on Arm Cortex-M microcontrollers, which power billions of devices already.
As Cartesiam GM Marc Dupaquier, who co-founded the company in 2016, told me, the company works very closely with Arm, given that both have a vested interest in having developers create new features for these devices. He noted that while the first wave of IoT was all about sending data to the cloud, that has now shifted and most companies now want to limit the amount of data they send out and do a lot more on the device itself. And that’s pretty much one of the founding theses of Cartesiam. “It’s just absurd to send all this data — which, by the way, also exposes the device from a security standpoint,” he said. “What if we could do it much closer to the device itself?”
The company first bet on Intel’s short-lived Curie SoC platform. That obviously didn’t work out all that well, given that Intel axed support for Curie in 2017. Since then, Cartesiam has focused on the Cortex-M platform, which worked out for the better, given how ubiquitous it has become. Since we’re talking about low-powered microcontrollers, though, it’s worth noting that we’re not talking about face recognition or natural language understanding here. Instead, using machine learning on these devices is more about making objects a little bit smarter and, especially in an industrial use case, detecting abnormalities or figuring out when it’s time to do preventive maintenance.
Today, Cartesiam already works with many large corporations that build Cortex-M-based devices. The NanoEdge Studio makes this development work far easier, though. “Developing a smart object must be simple, rapid and affordable — and today, it is not, so we are trying to change it,” said Dupaquier. But the company isn’t trying to pitch its product to data scientists, he stressed. “Our target is not the data scientists. We are actually not smart enough for that. But we are unbelievably smart for the embedded designer. We will resolve 99% of their problems.” He argues that Cartesiam reduced time to market by a factor of 20 to 50, “because you can get your solution running in days, not in multiple years.”
One nifty feature of the NanoEdge Studio is that it automatically tries to find the best algorithm for a given combination of sensors and use cases and the libraries it generates are extremely small and use somewhere between 4K to 16K of RAM.
NanoEdge Studio for both Windows and Linux is now generally available. Pricing starts at €690/month for a single user or €2,490/month for teams.
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Facebook’s Libra Association adds crypto prime broker Tagomi
TechCrunch has learned that $28 million-funded crypto startup Tagomi will be the newest member of the Libra Association that governs the Facebook-backed Libra stablecoin. A formal announcement is slated for Friday or next week.
Tagomi offers a platform that helps large traders and funds easily access cryptocurrency markets. The news comes days after Libra added Shopify, a reversal of dwindling membership after major partners like Visa, PayPal and Stripe dropped out late last year.
We’ve reached out to the Libra Association and have been promised a response by Facebook’s communications team.
Joining Libra means Tagomi will be expected to contribute at least $10 million toward developing the cryptocurrency, with that investment eligible to reap dividends from interest earned on money kept in the Libra Reserve. Tagomi will also operate a node that validates transactions coming through the Libra blockchain.
Tagomi was founded by Jennifer Campbell, a former investor at Union Square Ventures, which is also a Libra Association Member. The company has 25 employees across five offices. Tagomi will be the 22nd member of the Libra Association, according to information from the startup’s press representative, who was apparently supposed to hold this news until later. “Tagomi is joining the Libra Foundation and Jennifer will be the newest member,” they emailed TechCrunch. We’ll update this story following our interview with Campbell tomorrow.
Campbell and Tagomi will offer technical and policy support to Libra in an effort to make the cryptocurrency more safe and compliant with international law. That will be critical for the Libra Association to get the green light from regulators for a launch in 2020 like it originally planned. Lawmakers in the U.S. and EU have slammed Libra in hearings and the press over its potential to facilitate money laundering, harm privacy and destabilize the global financial system.
The full membership of the Libra Association is now:
Current Members:
Facebook’s Calibra, Tagomi, Shopify, PayU, Farfetch, Lyft, Spotify, Uber, Illiad SA, Anchorage, Bison Trails, Coinbase, Xapo, Andreessen Horowitz, Union Square Ventures, Breakthrough Initiatives, Ribbit Capital, Thrive Capital, Creative Destruction Lab, Kiva, Mercy Corps, Women’s World Banking.
Former Members:
Vodafone, Visa, Mastercard, Stripe, PayPal, Mercado Pago, Bookings Holdings, eBay.
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Twilio 2010 board deck gives peek at now-public company’s early days
Twilio is best known for its communications API, which allows developers to add messaging, voice or video to their apps with just a small slice of code. The company’s tools are used by customers like Lyft, Airbnb, Salesforce, Box and Duke University.
The former startup went public in 2016 at $15 a share. Yesterday Twilio’s stock closed at $113.90, giving the company a market cap of about $15.6 billion (after a horrendous week on Wall Street). It’s easy to look at its value (among other measures) and declare Twilio a successful public company. But just like every former startup out there, its ascent wasn’t always so certain.
Founded in 2008, Twilio was once a tentative early-stage company feeling its way forward in the market with an unproven product and more future potential than actual results. Recently, the company’s CEO Jeff Lawson shared a Twilio board deck from March 2010.
Naturally, we read through it — how could we not? — but we also decided to analyze it for you, pulling out what we learned and using the snapshot of Twilio’s history to illustrate how far the company has come in the last decade.
The presentation’s original time stamp lands after Twilio’s Series A and just before its Series B, allowing us to see a company molting from a hatchling to something more sturdy that could stand on its own two feet. The company raised $12 million six months after the deck was presented.
To get everyone on the same page, we’ll start with a little history, and then get into the deck itself. Let’s go!
Where Twilio came from
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