Spotlight Feature: Company Trends

When on the lookout for new investment opportunities, being able to identify trends is the first step on the road to uncover the next most promising industries and startups. With a growing number of early-stage companies keeping traditional markets saturated, we see competition intensifying and under-the-radar industry areas getting more attention than ever. Keeping tabs on numbers of investments, amounts invested, numbers of exits, and other relevant metrics from the startup world, is the foundation for a successful data-driven investment practice that knows when to deviate from the beaten path. The PreSeries Company Trends section is the perfect feature to future proof your investment strategy by understanding where to direct your attention to stay ahead of the pack.

Of course, not every trend matters to everyone. As a professional investor, you most likely follow an investment thesis, a strategy that helps you determine which companies to invest in. In PreSeries, the Company Trends feature aims to help you find trends that match your investment philosophy. As seen above, you can find trends for companies matching your desired criteria such as: status (Running, Acquired, Acqui-hired, IPO, Zombie, and Closed), location (Country and City), industry area (more than 700 to choose from), and date of foundation.

After applying the filters, you can choose to generate visualizations from 11 different trends charts. The Founded Companies chart represents the evolution of the number of companies founded over time. The Closed Companies chart does the same but for closed companies. The IPO and Acquired Companies charts depict the number of companies with successful exits over time.

You can also generate charts for relative values such as Time to IPO, Time to be AcquiredTime to Close and Time to be Funded. These charts are good indicators on how quickly companies reach any of these states. The sample chart above answers the question “How much time usually elapses between the founding of the companies and the IPO of the companies?”. Last but not least, for any given graph, you can download the visualization as a PNG file and the results in CSV format.

That’s it for Company Trends. Make sure to check our related post on the Spotlight Feature!

Spotlight Feature: Company Search and Rankings

Whether you are an investor on the lookout for the next promising startup, an incubator program searching for the best way to filter your never-ending stream of applications, or simply an entrepreneur gathering intel on your competitors, you need lots of data, a way to filter the noise, and uncover hidden signals. Today, most of the decision-making traditionally resulting from gut-feel and simple business rules are being slowly replaced by data-driven approaches that go beyond our limited analytical skills as humans. We are in the middle of such a revolution and today’s large trove of data coupled with cutting-edge machine learning techniques makes this possible.

But with large amounts of data, comes great anxiety. It’s one thing to have a large dataset, it’s even better when you can make sense of it and quickly derive meaningful insights. If that is what you are looking for, then PreSeries is the right fit for you. We use machine learning algorithms to analyze over 300k+ companies and generate predictive scores that represent their chances of success. The best way to search and filter these companies is through the Company Search & Rankings feature accessible from the Dashboard.

Above, is an example of the combination of filters you can apply to search for specific companies. You can specify company status, location (country and city), development stage (concept, seed, product development, market development or steady), and industry areas (e.g. “Mobile” and “Personal Health”).

Once the filters are applied, the result page ranks the companies matching the chosen criteria. By default, all companies are ranked by their overall score in the Top Companies tab (as seen above). The result page includes the following information: company name, current status, location (country and city), current stage, industry areas, overall score and recent changes in overall score. Clicking on the company name will automatically redirect you to the corresponding Company Profile page. You can find more about company profiles here. Clicking on a Country, a City or a specific Area will display all companies matching the selected criteria. The “star” and “pin” icons under the company names are quick and easy ways to add companies to your Starred Companies and Bookmarks respectively.


The Mover and Shakers tab is similar to the Top Companies tab, but instead of ranking the companies using their overall scores (i.e., absolute values), it ranks them by the recent increase in their overall scores (i.e, relative values). Companies listed in this tab are worth paying attention to, a sharp increase in score is often the reflection of improved performances and maybe even a hidden unicorn?

Go to PreSeries now and request your free trial!

That’s it for the Company Search and Rankings! As always, we’d love to hear about your thoughts and feedback.

PreSeries opens its doors!

We are thrilled to report that PreSeries is opening its doors! As we celebrate the official launch, we’d like to invite all of you to try it out.

Enter PreSeries

If you work in venture capital, corporate strategy, innovation, M&A or investment banking, chances are you are spending too much of your time scouting for the most reliable and up-to-date data sources only to spend even more time to clean, prepare the data, and perform analyses to derive meaningful insights. Given this complex data landscape, PreSeries is positioned to be the Swiss Army knife that gives you an unfair advantage over other investors. With our unique approach taking advantage of Machine Learning to assess a startups’ likelihood of success, we allow you to cut through the noise and focus on what matters. After all, data-driven approach to early-stage investment is the only way to remove our human biases once and for all.

PreSeries is also the perfect solution for cash-hungry entrepreneurs. Fundraising activities often feel like hunting for whales on makeshift raft for many startup founder’s in an ocean of investors with fickle interest. Using PreSeries to target the right VCs is the equivalent of upgrading to a naval grade vessel. Now, you’re finally able to gain first-hand knowledge of VCs most likely to invest in your company and discard the ones that will likely take your precious time by making you run around the block twice.

If you are an analyst or a data-scientist, there is a high probability you’re not a fan of data fairytales. You have to see it to believe it. Well, you’re in luck! With the PreSeries Analyst Platform (powered by BigML), we give you access to PreSeries’ Machine Learning engine room. You’ll be able to look under the hood to not only access but also customize our consolidated datasets, Machine Learning models, predictions and much more.

More blog posts detailing specific PreSeries’ features will be published on a regular basis, so stay tuned!

P.S.: If you’re interested in a demo, simply get in touch with us at and we’ll schedule one in no time.

Spotlight Feature: Company Profiles

The PreSeries interface is built with the power-user in mind, which is why we opted for a dashboard-type design that makes it easier than ever to quickly access vital insights about startups, investors and industry areas without sacrificing quality for convenience. In fact, all of PreSeries’ features follow this balanced principle.

In this post, the focus will be on one of our central features: Company Profiles. Company Profiles include all important information that PreSeries gathered on startups from around the globe as well as unique predictions based on our own estimation of their likelihood of success. In other words, on top of the traditional descriptive information such as funding data and online metrics, every company profile comes with its own predictive scores that represent our data-driven assessment of  its future performance.

Let’s take a section-by-section look at a sample company profile, and see what kind of information and predictions can be found. Today, our test subject will be the Google backed augmented reality startup, Magic Leap.


First things first, the top section is dedicated to general information about the company (picture above). Next to its name is the company current status: running, acquired, IPO, zombie or closed. Each company comes with a short description of its activity, date of foundation and main areas of activity with the top area being shown in blue. Additional information such as the last time company data was updated, links to company’s official website, its social media and Crunchbase profiles are also available.


On the top right corner we have the company’s predictive scores. They are computed by PreSeries Machine Learning algorithms. If you hover your cursor over them, a popup box appears with an explanation of the score’s meaning.


In the second section (picture above), we feature our own predictions regarding the most likely future status of the startup. We compute probabilities for the following possible outcomes: IPO, get acquired, get “acqui-hired”, keep running as a going concern, become a “zombie “, and go defunct. We also compute the estimated time frame in which an exit is most likely to occur. In the graph below, PreSeries distinguishes between five different stages in a startup’s life: Concept, Seed, Product Development, Market Development and Steady. Depending on the company’s currently available information, PreSeries also makes a prediction on its current stage.


Next, is the section about funding. It features a chart representing the history of the company’s fundraising activity including total and detailed amounts by round, most recent series of funding, financing types applicable and of course the corresponding dates.


The metrics section (seen above) allows you to visualize the historical trend of every metric gathered as well as the predictive scores computed by PreSeries. This way, you can easily assess the evolution of a company’s metrics independently to get a better understanding of its context over time.


The last section in every Company Profile page features how the selected startup compares against other companies in terms of its financing structure in the Similar Companies section (the 10 companies on the left), and in terms of product/service offerings in the Competitors section (the 10 companies on the right). The scores represent the degree of similarity between the companies and the selected startup.

Go to PreSeries and request access now!

That’s it for the Company Profile page! As always, we’d love to hear about your thoughts and feedback.

PreSeries’ Algorithm Chooses Pixoneye as the Startup Most Likely to Succeed

PreSeries, the joint venture between Telefónica Open Future_ and BigML, staged the fourth edition of the Artificial Intelligence Startup Battle yesterday (Tuesday, February 28). The event took place at the main stage of the 4 Years From Now (4YFN) event, the startup focused platform of the Mobile World Congress that enables investors and corporations to connect with successful entrepreneurs to launch new ventures together. More than 500 attendees witnessed this unique battle, where no humans were involved in assessing the contestants. Instead, the Machine Learning algorithm of PreSeries chose the winner.

This fourth edition followed the footsteps of the previous AI Startup Battles, the first one celebrated in Valencia last March 15, 2016, the second one in Boston on October 12, 2016, and the third one in Sao Paulo on December 9, 2016, where PreSeries’ algorithm asked a number of dynamically selected questions to each contender in order to provide a score between 0 and 100. The startup with the highest score won the contest as the system deemed it to be the one with most likelihood of future success. The predictions are based on historical data from more than 350.000 companies from around the world.


Pixoneye, the winner of the Artificial Intelligence Startup Battle at 4 Years From Now conference. Ana Segurado, the Global Manager of Telefónica Open Future_ gives away the award (left) to Pixoneye’s Erin Bronstein (right).

With a score of 96.63, the winner was announced as Pixoneye. Pixoneye is based in London and Tel Aviv, and offers the ability to analyze the untapped power of mobile users’ photo galleries on behalf of their clients. The second place finisher was with a score of 94.00, an English company that develops chatbots that revolutionises customer interactions for businesses and user experiences. The third position, with 67.82 points, was for of London. gives people ownership of their data to enable the next phase in the evolution of human connectivity. Finally, the fourth placed contestant (with a score of 61.23) was Descifra of Mexico, which helps businesses understand the characteristics of the markets around them through easy to understand charts, tables, and maps.

As in previous battles, the audience enthusiastically warmed up to the idea of an AI system judging the contestants after the pitch sessions and was excited to witness Pixoneye being crowned the latest AI Startup Battle winner.