May
16
2018
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Dashdash, a platform to create web apps using only spreadsheet skills, nabs $8M led by Accel

Sometimes I think of spreadsheets as the dirty secret of the IT world today. We’ve seen a huge explosion in the number of productivity tools on the market tailored to help workers with different aspects of doing their job and organising their information, in part to keep them from simply dumping lots of information into Excel or whatever program they happen to use. And yet, spreadsheets are still one of the very, very most common pieces of software in use today to organise and share information: Excel alone now has around 1 billion users, and for those who are devotees, spreadsheets are not going to go away soon.

So it’s interesting that there are now startups — and larger companies like Microsoft — emerging that are tapping into that, creating new services that still appear like spreadsheets in the front end, while doing something completely different in the back.

One of the latest is a startup called dashdash, a startup out of Berlin and Porto that is building a platform for people, who might to be programmers but know their way around a spreadsheet, to use those skills to build, modify and update web apps.

The dashdash platform looks and acts like a spreadsheet up front, but behind the scenes, each ‘macro’ links to a web app computing feature, or a design element, to build something that ultimately will look nothing like a spreadsheet, bypassing all the lines of code that traditionally go into building web apps.

The startup is still in stealth mode, with plans to launch formally later this year. Today, it’s announcing that it has received $8 million in Series A funding to get there, with the round being led by Accel, with participation from Cherry Ventures, Atlantic Labs, and angel investors including Felix Jahn, founder of Home24. (It’s raised $9 million to date including $1 million in seed funding.)

Co-founded by serial entrepreneurs Humberto Ayres Pereira and Torben Schulz — who had also been co-founders of food delivery startup EatFirst — Ayres Pereira said that the idea came out of their own observations in work life and the bottleneck of getting things fixed or modified in a company’s apps (both internal and customer-facing).

“People have a lot of frustration with the IT department, and their generally access to it,” he said in an interview. “If you are part of an internet business, it’s very hard to get features prioritised in an app, no matter how small they are. Tech is like a big train on iron tracks, and it can be hard to steer it in a different direction.”

On the other hand, even among the less technical staff, there will be proficiency with certain software, including spreadsheets. “Programming and spreadsheets already store and transform data,” Ayers Pereira said. “There are already a lot of people trying to do more with incumbent spreadsheets, and [combining that with] non-IT people frustrated at having no solution for working on apps, we saw an opportunity to use this to build an elegant platform the empower people. We can’t teach people to program but we can provide them with the tools to do the exact same job.”

While in stealth mode, he said that early users have ranged from smaller businesses such as pharmacies, to “a multi-billion-dollar internet company.” (No names, of course, but it’s interesting to me that this problem even exists at large tech businesses.)

Dashdash is not the only company that is tapping this opportunity. The other week, and IoT startup called Hanhaa launched a service that would let those using Hanhaa IoT sensors in their networks to monitor and interact with them by way of an Excel spreadsheet — another tip of the hat to the realisation that those who might need to keep tabs on devices in the network might not be the people who are the engineers and technicians who have set them up.

That, in turn, is part of a bigger effort from Microsoft to catapult Excel from its reputation as a piece of clunky legacy software into something much more dynamic, playing on the company’s push into cloud services and Office 365.

In September of 2017, Microsoft gave a developer preview of new “streaming functions” for Excel on Office 365, which lets developers, IT professionals and end users the ability to bring streams of data from a variety of sources such as websites, stock tickers and hardware directly into a cell or cells in an Excel spreadsheet, by way of a custom function. “Because Excel is so widely used and familiar to so many people, the ability to do all kinds of amazing things with that data and without complex integration is now possible,” said Ben Summers, a senior product manager for the Office 365 ecosystem team, in a statement to TechCrunch.

That ability to remove the bottleneck from web app building, combined with the track record of the founders, are two of the reasons that Accel decided to invest before the product even launched.

“We believe in dashdash’s mission to democratise app creation and are excited to back Humberto and Torben at such an early stage in their journey,” said Andrei Brasoveanu, the Accel principal who led the deal. “The team has the experience and vision to build a high-impact company that brings computing to the fingertips of a broad audience. Over the past decade we’ve seen a proliferation of web services and APIs, but regular business users still need to rely on central IT and colleagues with development skills to leverage these in their day-to-day processes. With dashdash anyone will be able to access these powerful web services directly with minimal effort, empowering them to automate their day to day tasks and work more effectively.”

With every tool that emerges that frees up accessibility to more people — be they employees or consumers — there are inevitably questions about how that power will be used. In the case of dashdash, my first thought is about those who I know who work in IT: they generally don’t want anyone able to modify or “fix” their code, lest it just creates more problems. And that’s before you start wondering about how all these democratised web apps will look, and if they might inadvertently will add to more overall UI and UX confusion.

Ayres Pereira said dashdash is mindful of the design question, and will introduce ways of helping to direct this, for example for companies to implement their own house styles. And similarly, a business can put in place other controls to help channel how web apps created through dashdash’s spreadsheet interface ultimately get applied.

May
15
2018
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Aircall raises another $29 million

French startup Aircall has raised a funding round of $29 million for its cloud based call center solution. Draper Esprit led the round with NextWorld Capital, Balderton Capital and Newfund also participating.

The company has raised $40.5 million in total. Aircall participated in the Startup Battlefield at TechCrunch Disrupt SF a few years ago. The company first started at eFounders.

Aircall is following the software-as-a-service playbook. First, you take a boring industry like phone systems for large support and sales teams. Second, you bet everything on software. And third, you keep adding new features and integrations, and chasing new customers.

The company now has two offices in New York and Paris and handles millions of calls every day. With today’s funding round, the company plans to hire more people in both offices.

When you sign up to Aircall, you get virtual phone numbers in one or multiple countries. You can then configure a greeting message, add business hours and handle your call queue.

But the magic happens when you have multiple people handling sales or support calls. When someone calls, it can ring multiple people at once or someone specific first, then a second person if the first person isn’t available, etc. You get an overview of all your calls so you can assign them, tag them and more.

Aircall doesn’t work in a vacuum. So you can integrate Aircall with CRMs and other solutions like Salesforce, Zendesk and Zoho. The startup also launched a deep integration with Intercom that lets you switch from a text conversation to a phone call from the popup window.

It’s hard to list all the features right here. But chances are that if you’re running a call center, you’ll have everything you need for your team. Aircall currently costs $30 to $50 per user and per month to access all of this.

Apr
25
2018
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Allegro.AI nabs $11M for ‘deep learning as a service’, for businesses to build computer vision products

Artificial intelligence and the application of it across nearly every aspect of our lives is shaping up to be one of the major step changes of our modern society. Today, a startup that wants to help other companies capitalise on AI’s advances is announcing funding and emerging from stealth mode.

Allegro.AI, which has built a deep learning platform that companies can use to build and train computer-vision-based technologies — from self-driving car systems through to security, medical and any other services that require a system to read and parse visual data — is today announcing that it has raised $11 million in funding, as it prepares for a full-scale launch of its commercial services later this year after running pilots and working with early users in a closed beta.

The round may not be huge by today’s startup standards, but the presence of strategic investors speaks to the interest that the startup has sparked and the gap in the market for what it is offering. It includes MizMaa Ventures — a Chinese fund that is focused on investing in Israeli startups, along with participation from Robert Bosch Venture Capital GmbH (RBVC), Samsung Catalyst Fund and Israeli fund Dynamic Loop Capital. Other investors (the $11 million actually covers more than one round) are not being disclosed.

Nir Bar-Lev, the CEO and cofounder (Moses Guttmann, another cofounder, is the company’s CTO; and the third cofounder, Gil Westrich, is the VP of R&D), started Allegro.AI first as Seematics in 2016 after he left Google, where he had worked in various senior roles for over 10 years. It was partly that experience that led him to the idea that with the rise of AI, there would be an opportunity for companies that could build a platform to help other less AI-savvy companies build AI-based products.

“We’re addressing a gap in the industry,” he said in an interview. Although there are a number of services, for example Rekognition from Amazon’s AWS, which allow a developer to ping a database by way of an API to provide analytics and some identification of a video or image, these are relatively basic and couldn’t be used to build and “teach” full-scale navigation systems, for example.

“An ecosystem doesn’t exist for anything deep-learning based.” Every company that wants to build something would have to invest 80-90 percent of their total R&D resources on infrastructure, before getting to the many other apsects of building a product, he said, which might also include the hardware and applications themselves. “We’re providing this so that the companies don’t need to build it.”

Instead, the research scientists that will buy in the Allegro.AI platform — it’s not intended for non-technical users (not now at least) — can concentrate on overseeing projects and considering strategic applications and other aspects of the projects. He says that currently, its direct target customers are tech companies and others that rely heavily on tech, “but are not the Googles and Amazons of the world.”

Indeed, companies like Google, AWS, Microsoft, Apple and Facebook have all made major inroads into AI, and in one way or another each has a strong interest in enterprise services and may already be hosting a lot of data in their clouds. But Bar-Lev believes that companies ultimately will be wary to work with them on large-scale AI projects:

“A lot of the data that’s already on their cloud is data from before the AI revolution, before companies realized that the asset today is data,” he said. “If it’s there, it’s there and a lot of it is transactional and relational data.

“But what’s not there is all the signal-based data, all of the data coming from computer vision. That is not on these clouds. We haven’t spoken to a single automotive who is sharing that with these cloud providers. They are not even sharing it with their OEMs. I’ve worked at Google, and I know how companies are afraid of them. These companies are terrified of tech companies like Amazon and so on eating them up, so if they can now stop and control their assets they will do that.”

Customers have the option of working with Allegro either as a cloud or on-premise product, or a combination of the two, and this brings up the third reason that Allegro believes it has a strong opportunity. The quantity of data that is collected for image-based neural networks is massive, and in some regards it’s not practical to rely on cloud systems to process that. Allegro’s emphasis is on building computing at the edge to work with the data more efficiently, which is one of the reasons investors were also interested.

“AI and machine learning will transform the way we interact with all the devices in our lives, by enabling them to process what they’re seeing in real time,” said David Goldschmidt, VP and MD at Samsung Catalyst Fund, in a statement. “By advancing deep learning at the edge, Allegro.AI will help companies in a diverse range of fields—from robotics to mobility—develop devices that are more intelligent, robust, and responsive to their environment. We’re particularly excited about this investment because, like Samsung, Allegro.AI is committed not just to developing this foundational technology, but also to building the open, collaborative ecosystem that is necessary to bring it to consumers in a meaningful way.”

Allegro.AI is not the first company with hopes of providing AI and deep learning as a service to the enterprise world: Element.AI out of Canada is another startup that is being built on the premise that most companies know they will need to consider how to use AI in their businesses, but lack the in-house expertise or budget (or both) to do that. Until the wider field matures and AI know-how becomes something anyone can buy off-the-shelf, it’s going to present an interesting opportunity for the likes of Allegro and others to step in.

 

 

 

Apr
12
2018
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Bubblz lets you collaborate on painful processes

Meet Bubblz, a French startup that wants to optimize all the boring processes that slow you down. If you’re trying to hire someone, if you need to collect information from many people, if you regularly put together marketing campaigns, you can use Bubblz to automate all the steps and collaborate with your coworkers.

Many people use Trello or another kanban-based tool to manage potential new hires and all sorts of processes that require multiple steps. Bubblz uses the same metaphor but with a few extra tricks.

Setting up a process is going to take some thinking and a bit of time. But the idea is that you’ll save a lot of time once you have created a process in Bubblz.

Each step is represented as a column. You can then configure some actions based on each step. For instance, if you’re trying to hire someone, your first step could be an online form to collect information and upload files.

After that, you can review each application and configure multiple buttons. If you click yes, it can move the application to the next column. If you click no, it can send a rejection email and archive the application.

If you decide to hire someone, you can track that the person has signed their contract or automatically send an email to the IT department to make them aware of the new hire. You can define a short todo list for each step.

This is just an example but you can use Bubblz for other painful processes. You can create a new process from scratch or import one from the process library. I don’t think it makes sense to use Bubblz for everything, but it’s the kind of services that can make sense for some very specific issues and departments.

Bubblz uses a software-as-a-service approach. You can create a basic account for free, and the company also offers paid monthly plans for advanced features.

Apr
11
2018
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TravelPerk grabs $21M to make booking business trips suck less

TravelPerk, a Barcelona-based SaaS startup that’s built an end-to-end business travel platform, has closed a $21 million Series B round, led by Berlin-based Target Global and London’s Felix Capital. Earlier investors Spark Capital and Sunstone also participated in the round, alongside new investor Amplo.

When we last spoke to the startup back in June 2016 — as it was announcing a $7M Series A — it had just 20 customers. It’s now boasting more than 1,000, name-checking “high growth” companies such as Typeform, TransferWise, Outfittery, GetYourGuide, GoCardless, Hotjar, and CityJet among its clients, and touting revenue growth of 1,200% year-on-year.

Co-founder and CEO Avi Meir tells us the startup is “on pace” to generate $100M in GMV this year.

Meir’s founding idea, back in 2015, was to create a rewards program based around dynamic budgeting for business trips. But after conversations with potential customers about their pain-points, the team quickly pivoted to target a broader bundle of business travel booking problems.

The mission now can be summarized as trying to make the entire business travel journey suck less — from booking flights and hotels; to admin tools for managing policies; analytics; customer support; all conducted within what’s billed as a “consumer-like experience” to keep end-users happy. Essentially it’s offering end-to-end travel management for its target business users.

“Travel and finance managers were frustrated by how they currently manage travel and looked for an all in one tool that JUST WORKS without having to compare rates with Skyscanner, be redirected to different websites, write 20 emails back and forth with a travel agent to coordinate a simple trip for someone, and suffer bad user experience,” says Meir.

“We understood that in order to fix business travel there is no way around but diving into it head on and create the world’s best OTA (online travel agency), combined with the best in class admin tools  needed in order to manage the travel program and a consumer grade, smart user experience that travelers will love. So we became a full blown platform competing head on with the big TMCs (travel management companies) and the legacy corporate tools (Amex GBT, Concur, Egencia…) .”

He claims TravelPerk’s one-stop business trip shop now has the world’s largest bookable inventory (“all the travel agent inventory but also booking.com, Expedia, Skyscanner, Airbnb… practically any flight/hotel on the internet — only we have that”).

Target users at this stage are SMEs (up to 1,500 employees), with tech and consulting currently its strongest verticals, though Meir says it “really runs the gamut”. While the current focus is Europe, with its leading markets being the UK, Germany and Spain.

TravelPerk’s business model is freemium — and its pitch is it can save customers more than a fifth in annual business travel costs vs legacy corporate tools/travel agents thanks to the lack of commissions, free customer support etc.

But it also offers a premium tier with additional flexibility and perks — such as corporate hotel rates and a travel agent service for group bookings — for those customers who do want to pay to upgrade the experience.

On the competition front the main rivals are “old corporate travel agencies and TMC”, according to Meir, along with larger players such as Egencia (by Expedia) and Concur (SAP company).

“There are a few startups doing what we are doing in the U.S. like TripActions, NexTravel, as well as some smaller ones that are popping up but are in an earlier stage,” he notes.

“Since our first round… TravelPerk has been experiencing some incredible growth compared to any tech benchmark I know,” he adds. “We’ve found a stronger product market fit than we imagined and grew much faster than planned. It seems like everyone is unhappy with the way they are currently booking and managing business travel. Which makes this a $1.25 trillion market, ready for disruption.”

The Series B will be put towards scaling “fast”, with Meir arguing that TravelPerk has landed upon a “rare opportunity” to drive the market.

“Organic growth has been extremely fast and we have an immediate opportunity to scale the business fast, doing what we are doing right now at a bigger scale,” he says.

Commenting in a statement, Antoine Nussenbaum, partner at Felix Capital, also spies a major opportunity. “The corporate travel industry is one of the largest global markets yet to be disrupted online. At Felix Capital we have a high conviction about a new era of consumerization of enterprise software,” he says.

While Target Global general partner Shmuel Chafets describes TravelPerk as “very well positioned to be a market leader in the business travel space with a product that makes business travel as seamless and easy as personal travel”.

“We’re excited to support such an experienced and dedicated team that has a strong track record in the travel space,” he adds in a supporting statement. “TravelPerk is our first investment in Barcelona. We believe in a pan-European startup ecosystem and we look forward to seeing more opportunities in this emerging startup hub.”

Flush with fresh funding, the team’s next task is even more recruitment. “We’ll grow our teams all around with emphasis on engineering, operations and customer support. We’re also planning to expand, opening local offices in 4-5 new countries within the upcoming year and a half,” says Meir.

He notes the company has grown from 20 to 100 employees over the past 12 months already but adds that it will continue “hiring aggressively”.

Apr
09
2018
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Juro grabs $2M to take the hassle out of contracts

UK startup Juro, which is applying a “design centric approach” and machine learning tech to help businesses speed up the authoring and management of sales contracts, has closed $2m in seed funding led by Point Nine Capital.

Prior investor Seedcamp also contributed to the round. Juro is announcing Taavet Hinrikus (TransferWise’s co-founder) as an investor now too, as well as Michael Pennington (Gumtree co-founder) and the family office of Paul Forster (co-founder of Indeed.com).

Back in January 2017 the London-based startup closed a $750,000 (£615k) seed round, though CEO and co-founder Richard Mabey tells us that was really better classed as an angel round — with Point Nine Capital only joining “late” in the day.

“We actually could have strung it out to Series A,” he says of the funding that’s being announced now. “But we had multiple offers come in and there is so much of an explosion in demand for the [machine learning] that it made sense to do a round now rather than wait for the A. The whole legal industry is undergoing radical change and we want to be leading it.”

Juro’s SaaS product is an integrated contracts workflow that combines contract creation, e-signing and commenting capabilities with AI-powered contract analytics.

Its general focus is on customers that have to manage a high volume of contacts — such as marketplaces.

The 2016-founded startup is not breaking out any customer numbers yet but says its client list includes the likes of Estee Lauder, Deliveroo and Nested. And Mabey adds that “most” of its demand is coming from enterprise at this point, noting it has “several tech unicorns and Fortune 500 companies in trial”.

While design is clearly a major focus — with the startup deploying clean-looking templates and visual cues to offer a user-friendly ‘upgrade’ on traditional legal processes — the machine learning component is its scalable, value-added differentiator to serve the target b2b users by helping them identify recurring sticking points in contract negotiations and keep on top of contract renewals.

Mabey tells TechCrunch the new funding will be used to double down on development of the machine learning component of the product.

“We’re not the first to market in contract management by about 25 years,” he says with a smilie. “So we have always needed to prove out our vision of why the incumbents are failing. One part of this is clunky UX and we’ve succeeded so far in replacing legacy providers through better design (e.g. we replace DocuSign at 80% of our customers).

“But the thing we and our investors are really excited about is not just helping businesses with contract workflow but helping them understand their contract data, auto-tag contracts, see pattens in negotiations and red flag unusual contract terms.”

While this machine learning element is where he sees Juro cutting out a competitive edge in an existing and established market, Mabey concedes it takes “quite a lot of capital to do well”. Hence taking more funding now.

“We need a level of predictive accuracy in our models that risk averse lawyers can get comfortable with and that’s a big ask!” he says.

Specifically, Juro will be using the funding to hire data scientists and machine learning engineers — building out the team at both its London and Riga offices. “We’re doing it like crazy,” adds Mabey. “For example, we just hired from the UK government Digital Service the data scientist who delivered the first ML model used by the UK government (on the gov.uk website).

“There is a huge opportunity here but great execution is key and we’re building a world class team to do it. It’s a big bet to grow revenue as quickly as we are and do this kind of R&D but that’s just what the market is demanding.”

Juro’s HQ remains in London for now, though Mabey notes its entire engineering team is based in the EU — between Riga, Amsterdam and Barcelona — “in part to avoid ‘Brexit risk’”.

“Only 27% of the team is British and we have customers operating in 12 countries — something I’m quite proud of — but it does leave us rather exposed. We’re very open minded about where we will be based in the future and are waiting to hear from the government on the final terms of Brexit,” he says when asked whether the startup has any plans to Brexit to Berlin.

“We always look beyond the UK for talent: if the government cannot provide certainty to our Romanian product designer (ex Kalo, Entrepreneur First) that she can stay in the UK post Brexit without risking a visa application, tbh it makes me less bullish on London!”

Mar
16
2018
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Google expands its Cloud Platform region in the Netherlands

Google today announced that it has expanded its recently launched Cloud Platform region in the Netherlands with an additional zone. The investment, which is worth a reported 500 million euros, expands the existing Netherlands region from two to three regions. With this, all four of the Central European Google Cloud Platform zones now feature three zones (which are akin to what AWS would call “availability zones”) that allow developers to build highly available services across multiple data centers.

Google typically aims to have a least three zones in every region, so today’s announcement to expand its region in the Dutch province of Groningen doesn’t come as a major surprise.

With this move, Google is also making Cloud SpannerCloud BigtableManaged Instance Groups, and Cloud SQL available in the region.

Over the course of the last two years, Google has worked hard to expand its global data center footprint. While it still can’t compete with the likes of AWS and Azure, which currently offers more regions than any of its competitors, the company now has enough of a presence to be competitive in most markets.

In the near future, Google also plans to open regions in Los Angeles, Finland, Osaka and Hong Kong. The major blank spots on its current map remain Africa, China (for rather obvious reasons) and Eastern Europe, including Russia.

Mar
13
2018
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WeWork expands its Flatiron School education business to London with £1M in scholarships

WeWork — the co-working startup valued at $20 billion with some 200,000 members across 200 locations globally — is continuing with its strategy of expanding into a wide array of adjacent operations to grow its business. Today the company announced that it will be expanding the coding-focused Flatiron School abroad, starting in London this June.

Alongside this, it’s also launching a scholarship program, offering £1 million in fees to people from underrepresented groups in tech to enrol in Flatiron classes, working with existing local groups like AllBright, Code Bar and Women Who Code to spread the word.

This is the Flatiron School’s first move outside of the U.S. for its physical classes — it had already offered online courses internationally before this — and notably it is also WeWork’s first significant educational effort since acquiring the New York startup last October for an undisclosed sum.

Since acquiring Flatiron, WeWork’s chief growth officer Dave Fano — who himself joined WeWork when the company acquired his own startup, building infomation modelling firm Case, heralding the start of the company’s acquisition spree — said that the idea has been to let Flatiron run business as usual, offering a variety of online and in-person coding and related courses. That is now changing as WeWork puts the acquisition to work, so to speak.

Expanding the kinds of services that it offers in European markets specifically is an interesting move for WeWork. When it first opened for business here in London, for example, people hiring out desks in other people’s offices, or working out of dedicated co-working spaces, was already a standard practice.

“There was lots of co-working already, so there was no need to educate the market on it,” Fano said in an interview. Hence, adding in more services and offerings is a way to help differentiate WeWork from the rest of the productivity pack. Education sits alongside a number of other services that WeWork has been developing, from offering all-in, optimised office spaces (complete with the ever-present glass decanter of fruit-infused water in the kitchen) both for individuals and running then on behalf of other companies, through to event planning (by way of its Meetup acquisition), and likely more down the line.

On the other side, this move is also an indication of how Flatiron, which had raised a modest $14 million in funding in its five years of life before getting acquired, is using the acquisition by the well-capitalised WeWork to upsize and compete against the likes of General Assembly and others who have doubled down on international expansion to build out their coding education businesses.

Flatiron School’s London operation will be based out of Finsbury Pavement, one of WeWork’s multiple London locations, and it will kick off with two courses, one a full-time software engineering immersive course that will last 15 weeks; and the other a part-time front-end web developer course that will run 10 weeks.

There have been a lot of efforts, both private and public, to help raise tech literacy among the workforces of the world, as industries and economies hope to train people for the next generation of employment as more legacy roles and processes tip into obsolescence, and all signs point to a more digital, connected and technological future.

Not all of these have been home runs, though, with many programmes failing to connect the dots between learning new skills and then applying them in actual jobs. And of course there remains a big digital divide between those who are already socially or economically challenged ever getting access to either the training or the subsequent work opportunities.

The company claims to have a strong success track record for its educational program.

“In the US, Flatiron School has set the benchmark for programming education with its community-first learning platform, market-aligned open-source curriculum, and outcomes-focused approach to education,” claims Adam Enbar, Flatiron School’s co-founder and CEO. “Since 2012, Flatiron has maintained a 99 percent graduation rate for its Software Engineering Programs in NYC and more than 2,000 students have graduated from Flatiron School to date, across both the on-campus and online programs. With our new Flatiron London location, we’ll be able to give more people access to attain the skills they need to create their life’s work.”

Meanwhile, a spokesperson for the school said that it also has a 99 percent placement rate for those looking for jobs in NYC in the area of the immersive program, and 97 percent placement overall in software engineering, iOS development and the fellowship program.

It’s a small start, but offering £1 million in scholarships alongside the launch can offer at least a small boost in trying to fix that problem. And for WeWork, which has now raised $7.3 billion in funding — including backing from the seemingly bottomless coffers of Softbank’s Vision Fund — a $1 million scholarship fund is small change, so hopefully it prove to be successful and it might consider how it can dole out more.

Updated with more stats.

Mar
13
2018
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WeWork expands its Flatiron School education business to London with £1M in scholarships

 WeWork — the co-working startup valued at $20 billion with some 200,000 members across 200 locations globally — is continuing with its strategy of expanding into a wide array of adjacent operations to grow its business. Today the company announced that it will be expanding the coding-focused Flatiron School abroad, starting in London this June.
Alongside this, it’s also… Read More

Mar
09
2018
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InfoSum’s first product touts decentralized big data insights

Nick Halstead’s new startup, InfoSum, is launching its first product today — moving one step closer to his founding vision of a data platform that can help businesses and organizations unlock insights from big data silos without compromising user privacy, data security or data protection law. So a pretty high bar then.

If the underlying tech lives up to the promises being made for it, the timing for this business looks very good indeed, with the European Union’s new General Data Protection Regulation (GDPR) mere months away from applying across the region — ushering in a new regime of eye-wateringly large penalties to incentivize data handling best practice.

InfoSum bills its approach to collaboration around personal data as fully GDPR compliant — because it says it doesn’t rely on sharing the actual raw data with any third parties.

Rather a mathematical model is used to make a statistical comparison, and the platform delivers aggregated — but still, says Halstead — useful insights. Though he says the regulatory angle is fortuitous, rather than the full inspiration for the product.

“Two years ago, I saw that the world definitely needed a different way to think about working on knowledge about people,” he tells TechCrunch. “Both for privacy [reasons] — there isn’t a week where we don’t see some kind of data breach… they happen all the time — but also privacy isn’t enough by itself. There has to be a commercial reason to change things.”

The commercial imperative he reckons he’s spied is around how “unmanageable” big data can become when it’s pooled for collaborative purposes.

Datasets invariably need a lot of cleaning up to make different databases align and overlap. And the process of cleaning and structuring data so it can be usefully compared can run to multiple weeks. Yet that effort has to be put in before you really know if it will be worth your while doing so.

That snag of time + effort is a major barrier preventing even large companies from doing more interesting things with their data holdings, argues Halstead.

So InfoSum’s first product — called Link — is intended to give businesses a glimpse of the “art of the possible”, as he puts it — in just a couple of hours, rather than the “nine, ten weeks” he says it might otherwise take them.

“I set myself a challenge… could I get through the barriers that companies have around privacy, security, and the commercial risks when they handle consumer data. And, more importantly, when they need to work with third parties or need to work across their corporation where they’ve got numbers of consumer data and they want to be able to look at that data and look at the combined knowledge across those.

“That’s really where I came up with this idea of non-movement of data. And that’s the core principle of what’s behind InfoSum… I can connect knowledge across two data sets, as if they’ve been pooled.”

Halstead says that the problem with the traditional data pooling route — so copying and sharing raw data with all sorts of partners (or even internally, thereby expanding the risk vector surface area) — is that it’s risky. The myriad data breaches that regularly make headlines nowadays are a testament to that.

But that’s not the only commercial consideration in play, as he points out that raw data which has been shared is immediately less valuable — because it can’t be sold again.

“If I give you a data set in its raw form, I can’t sell that to you again — you can take it away, you can slice it and dice it as many ways as you want. You won’t need to come back to me for another three or four years for that same data,” he argues. “From a commercial point of view [what we’re doing] makes the data more valuable. In that data is never actually having to be handed over to the other party.”

Not blockchain for privacy

Decentralization, as a technology approach, is also of course having a major moment right now — thanks to blockchain hype. But InfoSum is definitely not blockchain. Which is a good thing. No sensible person should be trying to put personal data on a blockchain.

“The reality is that all the companies that say they’re doing blockchain for privacy aren’t using blockchain for the privacy part, they’re just using it for a trust model, or recording the transactions that occur,” says Halstead, discussing why blockchain is terrible for privacy.

“Because you can’t use the blockchain and say it’s GDPR compliant or privacy safe. Because the whole transparency part of it and the fact that it’s immutable. You can’t have an immutable database where you can’t then delete users from it. It just doesn’t work.”

Instead he describes InfoSum’s technology as “blockchain-esque” — because “everyone stays holding their data”. “The trust is then that because everyone holds their data, no one needs to give their data to everyone else. But you can still crucially, through our technology, combine the knowledge across those different data sets.”

So what exactly is InfoSum doing to the raw personal data to make it “privacy safe”? Halstead claims it goes “beyond hashing” or encrypting it. “Our solution goes beyond that — there is no way to re-identify any of our data because it’s not ever represented in that way,” he says, further claiming: “It is absolutely 100 per cent data isolation, and we are the only company doing this in this way.

“There are solutions out there where traditional models are pooling it but with encryption on top of it. But again if the encryption gets broken the data is still ending up being in a single silo.”

InfoSum’s approach is based on mathematically modeling users, using a “one way model”, and using that to make statistical comparisons and serve up aggregated insights.

“You can’t read things out of it, you can only test things against it,” he says of how it’s transforming the data. “So it’s only useful if you actually knew who those users were beforehand — which obviously you’re not going to. And you wouldn’t be able to do that unless you had access to our underlying code-base. Everyone else either users encryption or hashing or a combination of both of those.”

This one-way modeling technique is in the process of being patented — so Halstead says he can’t discuss the “fine details” — but he does mention a long standing technique for optimizing database communications, called bloom filters, saying those sorts of “principles” underpin InfoSum’s approach.

Although he also says it’s using those kind of techniques differently. Here’s how InfoSum’s website describes this process (which it calls Quantum):

InfoSum Quantum irreversibly anonymises data and creates a mathematical model that enables isolated datasets to be statistically compared. Identities are matched at an individual level and results are collated at an aggregate level – without bringing the datasets together.

On the surface, the approach shares a similar structure to Facebook’s Custom Audiences Product, where advertisers’ customer lists are locally hashed and then uploaded to Facebook for matching against its own list of hashed customer IDs — with any matches used to create a custom audience for ad targeting purposes.

Though Halstead argues InfoSum’s platform offers more for even this kind of audience building marketing scenario, because its users can use “much more valuable knowledge” to model on — knowledge they would not comfortably share with Facebook “because of the commercial risks of handing over that first person valuable data”.

“For instance if you had an attribute that defined which were your most valuable customers, you would be very unlikely to share that valuable knowledge — yet if you could safely then it would be one of the most potent indicators to model upon,” he suggests.

He also argues that InfoSum users will be able to achieve greater marketing insights via collaborations with other users of the platform vs being a customer of Facebook Custom Audiences — because Facebook simply “does not open up its knowledge”.

“You send them your customer lists, but they don’t then let you have the data they have,” he adds. “InfoSum for many DMPs [data management platforms] will allow them to collaborate with customers so the whole purchasing of marketing can be much more transparent.”

He also emphasizes that marketing is just one of the use-cases InfoSum’s platform can address.

Decentralized bunkers of data

One important clarification: InfoSum customers’ data does get moved — but it’s moved into a “private isolated bunker” of their choosing, rather than being uploaded to a third party.

“The easiest one to use is where we basically create you a 100 per cent isolated instance in Amazon [Web Services],” says Halstead. “We’ve worked with Amazon on this so that we’ve used a whole number of techniques so that once we create this for you, you put your data into it — we don’t have access to it. And when you connect it to the other part we use this data modeling so that no data then moves between them.”

“The ‘bunker’ is… an isolated instance,” he adds, elaborating on how communications with these bunkers are secured. “It has its own firewall, a private VPN, and of course uses standard SSL security. And once you have finished normalising the data it is turned into a form in which all PII [personally identifiable information] is deleted.

“And of course like any other security related company we have had independent security companies penetration test our solution and look at our architecture design.”

Other key pieces of InfoSum’s technology are around data integration and identity mapping — aimed at tackling the (inevitable) problem of data in different databases/datasets being stored in different formats. Which again is one of the commercial reasons why big data silos often stay just that: Silos.

Halstead gave TechCrunch a demo showing how the platform ingests and connects data, with users able to use “simple steps” to teach the system what is meant by data types stored in different formats — such as that ‘f’ means the same as ‘female’ for gender category purposes — to smooth the data mapping and “try to get it as clean as possible”.

Once that step has been completed, the user (or collaborating users) are able to get a view on how well linked their data sets are — and thus to glimpse “the start of the art of the possible”.

In practice this means they can choose to run different reports atop their linked datasets — such as if they want to enrich their data holdings by linking their own users across different products to gain new insights, such as for internal research purposes.

Or, where there’s two InfoSum users linking different data sets, they could use it for propensity modeling or lookalike modeling of customers, says Halstead. So, for example, a company could link models of their users with models of the users of a third party that holds richer data on its users to identify potential new customer types to target marketing at.

“Because I’ve asked to look at the overlap I can literally say I only know the gender of these people but I would also like to know what their income is,” he says, fleshing out another possible usage scenario. “You can’t drill into this, you can’t do really deep analytics — that’s what we’ll be launching later. But Link allows you to get this idea of what would it look like if I combine our datasets.

“The key here is it’s opening up a whole load of industries where sensitivity around doing this — and where, even in industries that share a lot of data already but where GDPR is going to be a massive barrier to it in the future.”

Halstead says he expects big demand from the marketing industry which is of course having to scramble to rework its processes to ensure they don’t fall foul of GDPR.

“Within marketing there is going to be a whole load of new challenges for companies where they were currently enhancing their databases, buying up large raw datasets and bringing their data into their own CRM. That world’s gone once we’ve got GDPR.

“Our model is safer, faster, and actually still really lets people do all the things they did before but while protecting the customers.”

But it’s not just marketing exciting him. Halstead believes InfoSum’s approach to lifting insights from personal data could be very widely applicable — arguing, for example, that it’s only a minority of use-cases, such as credit risk and fraud within banking, where companies actually need to look at data at an individual level.

One area he says he’s “very passionate” about InfoSum’s potential is in the healthcare space.

“We believe that this model isn’t just about helping marketing and helping a whole load of others — healthcare especially for us I think is going to be huge. Because [this affords] the ability to do research against health data where health data is never been actually shared,” he says.

“In the UK especially we’ve had a number of massive false starts where companies have, for very good reasons, wanted to be able to look at health records and combine data — which can turn into vital research to help people. But actually their way of doing it has been about giving out large datasets. And that’s just not acceptable.”

He even suggests the platform could be used for training AIs within the isolated bunkers — flagging a developer interface that will be launching after Link which will let users query the data as a traditional SQL query.

Though he says he sees most initial healthcare-related demand coming from analytics that need “one or two additional attributes” — such as, for example, comparing health records of people with diabetes with activity tracker data to look at outcomes for different activity levels.

“You don’t need to drill down into individuals to know that the research capabilities could give you incredible results to understand behavior,” he adds. “When you do medical research you need bodies of data to be able to prove things so the fact that we can only work at an aggregate level is not, I don’t think, any barrier to being able to do the kind of health research required.”

Another area he believes could really benefit is M&A — saying InfoSum’s platform could offer companies a way to understand how their user bases overlap before they sign on the line. (It is also of course handling and thus simplifying the legal side of multiple entities collaborating over data sets.)

“There hasn’t been the technology to allow them to look at whether there’s an overlap before,” he claims. “It puts the power in the hands of the buyer to be able to say we’d like to be able to look at what your user base looks like in comparison to ours.

“The problem right now is you could do that manually but if they then backed out there’s all kinds of legal problems because I’ve had to hand the raw data over… so no one does it. So we’re going to change the M&A market for allowing people to discover whether I should acquire someone before they go through to the data room process.”

While Link is something of a taster of what InfoSum’s platform aims to ultimately offer (with this first product priced low but not freemium), the SaaS business it’s intending to get into is data matchmaking — whereby, once it has a pipeline of users, it can start to suggest links that might be interesting for its customers to explore.

“There is no point in us reinventing the wheel of being the best visualization company because there’s plenty that have done that,” he says. “So we are working on data connectors for all of the most popular BI tools that plug in to then visualize the actual data.

“The long term vision for us moves more into being more of an introductory service — i.e. one we’ve got 100 companies in this how do we help those companies work out what other companies that they should be working with.”

“We’ve got some very good systems for — in a fully anonymized way — helping you understand what the intersection is from your data to all of the other datasets, obviously with their permission if they want us to calculate that for them,” he adds.

“The way our investors looked at this, this is the big opportunity going forward. There is not limit, in a decentralized world… imagine 1,000 bunkers around the world in these different corporates who all can start to collaborate. And that’s our ultimate goal — that all of them are still holding onto their own knowledge, 100% privacy safe, but then they have that opportunity to work with each other, which they don’t right now.”

Engineering around privacy risks?

But does he not see any risks to privacy of enabling the linking of so many separate datasets — even with limits in place to avoid individuals being directly outed as connected across different services?

“However many data sets there are the only thing it can reveal extra is whether every extra data has an extra bit of knowledge,” he responds on that. “And every party has the ability to define  what bit of data they would then want to be open to others to then work on.

“There are obviously sensitivities around certain combinations of attributes, around religion, gender and things like that. Where we already have a very clever permission system where the owners can define what combinations are acceptable and what aren’t.”

“My experience of working with all the social networks has meant — I hope — that we are ahead of the game of thinking about those,” he adds, saying that the matchmaking stage is also six months out at this point.

“I don’t see any down sides to it, as long as the controls are there to be able to limit it. It’s not like it’s going to be a sudden free for all. It’s an introductory service, rather than an open platform so everyone can see everything else.”

The permission system is clearly going to be important. But InfoSum does essentially appear to be heading down the platform route of offloading responsibility for ethical considerations — in its case around dataset linkages — to its customers.

Which does open the door to problematic data linkages down the line, and all sorts of unintended dots being joined.

Say, for example, a health clinic decides to match people with particular medical conditions to users of different dating apps — and the relative proportions of HIV rates across straight and gay dating apps in the local area gets published. What unintended consequences might spring from that linkage being made?

Other equally problematic linkages aren’t hard to imagine. And we’ve seen the appetite businesses have for making creepy observations about their users public.

“Combining two sets of aggregate data meaningfully is not easy,” says Eerke Boiten, professor of cyber security at De Montfort University, discussing InfoSum’s approach. “If they can make this all work out in a way that makes sense, preserves privacy, and is GDPR compliant, then they deserve a patent I suppose.”

On data linkages, Boiten points to the problems Facebook has had with racial profiling as illustrative of the potential pitfalls.

He also says there may also be GDPR-specific risks around customer profiling enabled by the platform. In an edge case scenario, for example, where two overlapped datasets are linked and found to have a 100% user match, that would mean people’s personal data had been processed by default — so that processing would have required a legal basis to be in place beforehand.

And there may be wider legal risks around profiling too. If, for example, linkages are used to deny services or vary pricing to certain types or blocks of customers, is that legal or ethical?

“From a company’s perspective, if it already has either consent or a legitimate purpose (under GDPR) to use customer data for analytical/statistical purposes then it can use our products,” says InfoSum’s COO Danvers Baillieu, on data processing consent. “Where a company has an issue using InfoSum as a sub-processor, then… we can set up the system differently so that we simply supply the software and they run it on their own machines (so we are not a data processor) –- but this is not yet available in Link.”

Baillieu also notes that the bin sizes InfoSum’s platform aggregates individuals into are configurable in its first product. “The default bin size is 10, and the absolute minimum is three,” he adds.

“The other key point around disclosure control is that our system never needs to publish the raw data table. All the famous breaches from Netflix onwards are because datasets have been pseudonymised badly and researchers have been able to run analysis across the visible fields and then figure out who the individuals are — this is simply not possible with our system as this data is never revealed.”

‘Fully GDPR compliant’ is certainly a big claim — and one that it going to have a lot of slings and arrows thrown at it as data gets ingested by InfoSum’s platform.

It’s also fair to say that a whole library of books could be written about technology’s unintended consequences.

Indeed, InfoSum’s own website credits Halstead as the inventor of the embedded retweet button, noting the technology is “something that is now ubiquitous on almost every website in the world”.

Those ubiquitous social plugins are also of course a core part of the infrastructure used to track Internet users wherever and almost everywhere they browse. So does he have any regrets about the invention, given how that bit of innovation has ended up being so devastating for digital privacy?

“When I invented it, the driving force for the retweet button was only really as a single number to count engagement. It was never to do with tracking. Our version of the retweet button never had any trackers in it,” he responds on that. “It was the number that drove our algorithms for delivering news in a very transparent way.

“I don’t need to add my voice to all the US pundits of the regrets of the beast that’s been unleashed. All of us feel that desire to unhook from some of these networks now because they aren’t being healthy for us in certain ways. And I certainly feel that what we’re not doing for improving the world of data is going to be good for everyone.”

When we first covered the UK-based startup it was going under the name CognitiveLogic — a placeholder name, as three weeks in Halstead says he was still figuring out exactly how to take his idea to market.

The founder of DataSift has not had difficulties raising funding for his new venture. There was an initial $3M from Upfront Ventures and IA Ventures, with the seed topped up by a further $5M last year, with new investors including Saul Klein (formerly Index Ventures) and Mike Chalfen of Mosaic Ventures. Halstead says he’ll be looking to raise “a very large Series A” over the summer.

In the meanwhile he says he has a “very long list” of hundreds customers wanting to get their hands on the platform to kick its tires. “The last three months has been a whirlwind of me going back to all of the major brands, all of the big data companies, there no large corporate that doesn’t have these kinds of challenges,” he adds.

“I saw a very big client this morning… they’re a large multinational, they’ve got three major brands where the three customer sets had never been joined together. So they don’t even know what the overlap of those brands are at the moment. So even giving them that insight would be massively valuable to them.”

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