Personal blog of Yzmir Ramirez

PowerPoint may still dominate the landscape for presentations in many people’s minds, but some might say that legacy status also makes Microsoft’s software ripe for disruption. Now, a startup out of Berlin called Pitch has just picked up a substantial Series B of $85 million to take it on with what it believes is a more dynamic approach.

The round is being led by Lakestar and Tiger Global, with previous backers Index Ventures and Thrive Capital also participating. We understand from sources close to the company that the valuation is now at $600 million for the Berlin-based startup.

In the words of CEO and co-founder Christian Reber, the ambition is to create the “YouTube for presentations,” with the ability for people to create, collaborate on and share presentations with each other through an online-based interface.

His interest, meanwhile, in taking on Microsoft has a deeper story to it. As we have covered before, Reber’s previous startup, the planning startup Wunderlist, was acquired by Microsoft and folded into its productivity suite, only to eventually be killed off, much to Reber’s disbelief and disappointment.

Not to dwell too much in the past, the funding Pitch has now raised will be used in several areas, including hiring more people and reach. The startup has already seen good progress on the latter front. Pitch is already being used by tens of thousands of teams, it says, who have created some 125,000 workspaces on the platform. Customers include (ironically) a number of other trailblazers in the world of business productivity: Intercom, Superhuman and Notion are among the list.

The plan will be to work on bringing on more users into its freemium universe, while converting more to its Pitch Pro $10/user/month paid tier, which includes more extensions like unlimited storage, video uploads, version history and advanced permissioning. Pro already has a “couple of thousand” subscribers, Reber said, enough to prove out that “we definitely see our business model working.” Pitch is also working on rolling out an enterprise version so that it can sell Pitch into the bigger businesses and deployments that dominate usage of PowerPoint.

And the other way that Pitch plans to bring more people into the fold will be with more functionality. Along with the funding, Pitch is rolling out some new features that will include the beginnings of an ecosystem, where presentation designers and creators will be able to upload presentation templates, as well as presentations themselves, to help other people get started in creating their own presentations.

The idea here is to celebrate creators, Reber said, but it’s (at least for now) stopping short of paying them, seeing this more as a way of sharing designs and ideas in a more collaborative exchange with each other. Both, however, seem to me to be ripe opportunities down the line for building a marketplace. Creating a great pitch deck for a startup is great to share as a resource, but if you are also, say, a leadership coach who makes a living out of giving people inspiring direction on how to handle something, a pitch deck with that IP in it perhaps might not be something you’d always be willing to part with for free. (Reber says his inspiration here was the world of design forums like Dribble, where an exchange of ideas has thrived.)

Initially, the user-generated content will be selected by Pitch itself, although the plan over time will be to make it something that will be open to everyone, Reber said.

Another new feature will be presentation analytics. This will not be unlike the kind of data that people currently can apply to, say, email or web traffic to measure what people are clicking on, how long they are spending looking at content and where they are dropping off. Pitch will apply the same to its presentations — which are HTML-coded — so that those who are making them and sending them around can get a better idea of how they are performing, and even begin the process of A-B testing to try out different approaches.

Reber points out that analytics will be opt-in only: If users choose not to share that tracking, it won’t be shared, he said.

“As a German business, we have a special relationship with data privacy in the greatest sense,” he said. “We care deeply about making sure we approach features in a privacy-first way.” The idea is to make it less like spyware, and more like the kind of analytics one might have on YouTube for videos there.

Finally, it’s adding in more video features to bring in narrative recording and playback. These first will be “recorded” around the presentations themselves, but longer term, it’s likely that the feature will also have a live element, which makes a lot of sense since a lot of presentations have had their most highly trafficked exposure by way of webinars or live presentations (say, around an earnings call), where you might not only have multiple presenters talking along a slide deck, but also people feeding back, asking questions in relation to the presentation and so on.

If this all sounds a little WordPress-like, that’s not a coincidence. Reber noted that website building is something else that Pitch wants to bring into the platform. “We are experimenting with that,” he said. “In my opinion, presentations are collections of information and we want to publish them in various ways. Slides just happens to be one format. But if it’s all already written in HTML, why not build it also into a site? That will be another feature coming, and something that we will be also using the funding for.”

Indeed, that may not work for deeper content efforts (such as publications like the one you are reading right now), but would be perfectly adequate for, say, basic sites along the kind that are built on sites like Squarespace to lay out some online real estate for a small business. The scope of what you can already do, and what Pitch wants you to do, is precisely what makes this all so interesting to investors, they say.

“The exciting vision that Christian and the team at Pitch have is beyond just being a superior alternative to legacy presentation software,” said Stephen Nundy, partner at Lakestar, in a statement. “A reimagining of the entire workflow surrounding presentations is very much overdue, and when coupled with the ability to harness new data and media integrations, Pitch will lead the way in changing how stories are told. I’m very proud to be joining the board of a European company with its sights set on a truly global opportunity.”

“We are incredibly impressed by the quality of Pitch’s offering today and Christian’s vision for the future. Pitch will be a true productivity platform, and we are excited to become investors in this special company,” John Curtius, partner at Tiger Global, added.

Reber’s take on the new tools are also here:

Spreadsheet software — led by products like Microsoft’s Excel, Google’s Sheets and Apple’s Numbers — continues to be one of the most-used categories of business apps, with Excel alone clocking up more than a billion users just on its Android version. Now, a startup called Rows that’s built on that ubiquity, with a low-code platform that lets people populate and analyze web apps using just spreadsheet interfaces, is announcing funding and launching a freemium open beta of its expanded service.

The Berlin-based startup — which rebranded from dashdash at the end of last year — closed a Series B round of $16 million, money that it is using to continue investing in its platform as well as in sales and marketing. The platform’s move into an open beta comes with some 50 new integrations with other platforms like LinkedIn, Instagram and more, as well as 200 new features (using known spreadsheet shortcuts) to use in them.

The round was led by Lakestar, with past investors Accel (which led its $8 million Series A in 2018) and Cherry Ventures also participating. Christian Reber has also invested in this round. Reber knows a thing or two about software disrupting legacy productivity software — he is the co-founder and CEO of presentation software startup Pitch and the former CEO and founder of Microsoft-acquired Wunderlist — and notably he is joining Rows’ Advisory Board along with the investment.

A little detail about this Series B: CEO Humberto Ayres Pereira, who is based out of Porto, Portugal, where some of the staff is also based, tells us that this round actually was quietly closed over a year ago, in January 2020 — just ahead of the world shutting down amid the COVID-19 pandemic.

The startup chose to announce that round today to coincide with adding more features to its product and moving it into an open beta, he said.

That open beta is free in its most basic form — the free tier is limited to 10 users or less and a minimal amount of integration usage. Paid tiers, which cover more team members and up to 100,000 integration tasks (which are measured by how many times a spreadsheet queries another service), start at $59 per month.

One strong sign of interest in this latest iteration of the software is the lasting popularity of spreadsheets. Another is Rows’ traction to date: in invite-only mode, it picked up 10,000 users off its waitlist, and hundreds of companies, as customers. Currently most of those are free, Ayres Pereira said.

“Our goal is to have 1,000 paying companies as customers in the 12 months,” he said. That process has only just started, he added, with paying numbers in the modest “dozens” for now. He emphasized though that the company is very cash efficient and has, even without raising more funding, two years of runway on the money it has in the bank now.

The growing appeal of low-code

No-code and low-code software, which let people create and work with apps and other digital content without delving deep into the lines of code that underpin them, have continued to pick up traction in the market in the last several years.

The reason for this is straightforward: non-technical employees may not code, but they are getting increasingly adept at understanding how services function and what can be achieved within an app.

No-code and low-code platforms let them get more hands-on when it comes to customizing and creating the services that they need to use everyday to get their work done, without the time and effort it might take to get an engineer involved.

“People want to create their own tools,” said Ayres Pereira. “They want to understand and test and iterate.” He said that the majority of Rows’ users so far are based out of North America, and typical use cases include marketing and sales teams, as well as companies using Rows spreadsheets as a dynamic interface to manage logistics and other operations.

Stephen Nundy, the partner at Lakestar who led its investment, describes the army of users taking up no-code tools as “citizen developers.”

Rows is precisely the kind of platform that plays into the low-code trend. For people who are already au fait with the kinds of tools that you find in spreadsheets — and something like Excel has hundreds of functions in it — it presents a way of leaning on those familiar functions to trigger integrations with other apps, and to subsequently use a spreadsheet created in Rows to both analyse data from other apps, as well as update them.

You might ask, why is it more useful, for example, to look at content from Twitter in Rows rather than Twitter itself? A Rows document might let a person search for a set of Tweets using a certain chain of keywords, and then organise those results based on parameters such as how many “likes” those Tweets received.

Or users responding to a call to action for a promotion on Instagram might then be cross-referenced with a company’s existing database of customers, to analyze how those respondents overlap or present new leads.

You might also wonder why existing spreadsheet products may not have already build functionality like this.

Interestingly, Microsoft did dabble in building a way of linking up Excel with some rudimentary computing functions, in the form of Visual Basic for Applications. This however reached the dubious distinction of topping developers’ “most dreaded” languages list for two years running, and so as you might imagine it has somewhat died a death.

However, it does point to an opportunity for incumbents to disrupt their disruptors.

Apart from those most obvious, entrenched competitors, there have been a number of other startups building tools that are providing similar no- and low-code approaches.

Gyana is focusing more on data science, Tray.io provides a graphical interface to integrate how apps work together, Zapier and Notion also provide simple interfaces to integrate apps and APIs together and Airtable has its own take on reinventing the spreadsheet interface. For now, Ayres Pereira sees these more as compatriots than competitors.

“Yes, we overlap with services like Zapier and Notion,” he said. “But I’d say we are friends. We’re all raising awareness about people being able to do more and not having to be stuck using old tools. It’s not a zero sum game for us.”

When we covered Rows’s Series A two years ago, the startup had built a platform to let people who are comfortable working with data in spreadsheets use that interface to create and populate content in web apps. It had a lot of extensibility, but mainly geared at people still willing to do the work to create those links.

Two years on, while the spreadsheet has remained the anchor, the platform has grown. Ayres Pereira, who co-founded the company with Torben Schulz (both pictured above), said that there are some 50 new integrations now, including ways to analyse and update content on social media platforms like Instagram, YouTube, CrunchBase, Salesforce, Slack, LinkedIn and Twitter, as well as some 200 new features in the platform itself.

While people can import into Rows data from Google Sheets, he noted that the big daddy of them all, Excel, is not supported right now. The reason, he said, is because the vast majority of users of the product use the desktop version, which does not have APIs.

Meanwhile, Rows also has a number of templates available for people to guide them through simple tasks, such as looking up LinkedIn profiles or emails for a list of people, tracking social media counts and so on.

One of the most common aspects of spreadsheets, however, has yet to be built. The interface is still banked around rows and columns, but with no graphical tools to visualize data in different ways such as pie charts or graphs as you might have in a typical spreadsheet program.

It’s for this reason that Rows has yet to exit beta. The feature is one that is requested a lot, Pereira admitted, describing it as “the final frontier.” When Rows is ready to ship with that functionality, likely by Q3 of this year, it will tick over to general “1.0” release, he added.

“Humberto and Torben have really impressed us with their ambition to disrupt the market with a new spreadsheet paradigm that tackles the significant shortcomings of today’s solutions,” said Nundy at Lakestar. “Data integrations are native, the collaboration experience is first class and the ability to share and publish your work as an application is unique and will create more ‘Citizen developers’ to emerge. This is essential to the growing needs of today’s technology literate workforce. The level of interest they’ve received in their private beta is proof of the desirability of platforms like Rows, and we’re excited to be supporting them through their public beta launch and beyond with this investment.” Nundy is also joining Rows’ board with this round.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

“To see what these guys can deliver, it’s to be applauded,” he said. “They’re not just picking out names and addresses. We’re talking deep, semantic understanding. Other vendors are trying to be everything to everybody, but Eigen has found market fit in financial services use cases, and it stands up against the competition. You can see when a winner is breaking away from the pack and it’s a great signal for the future.”