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Visual Solutions for Presenting Complex Patent Data - An Interview with Taavi Raidma CEO of Deltasight

Visual Solutions for Presenting Complex Patent Data - An Interview with Taavi Raidma CEO of Deltasight

In another first for I am happy to present an interview with Taavi Raidma, CEO of Deltasight. Deltasight was previously known as CrowdIPR and  started making waves in the patent analytics world when they began focusing on network analysis as a means for visualizing connections between entities within patent information. This initial foray was called Holigraph and while graph databases are still a big part of what Deltasight delivers they have started presenting the results using infographics. Infographics provide a visual solution for presenting complex, integrated information on a topic in a concise, readable format.

Early readers of this blog will know that I started by posting several interesting infographics in the patent space, and eventually produced some of my own on using Public PAIR and key court cases involving patents, so I have a fondness for this approach to information dissemination.

Deltasight has already made several inforgraphic available to the public including analyses of Twitter, as compared to Facebook and LinkedIn, and a comparison of Nokia to TomTom and Garmin in the mapping and navigation space. The company was also featured in a recent article in Forbes on Why Banks will be Losers to Mobile and Ecommerce Leaders. The article featured the following quote that described the value of using infographics for sharing patent related information:

Banks need to compete in these areas with patent hungry challengers.  They also need ultra-high performance security. They need to be involved in identity management. The peer-to-peer space. New types of social messaging. Maybe even in end-to-end product financing and fulfillment.

These are all prerequisites if banks are to compete with start-ups and incumbents in the smartphone sector and e-commerce. If they are prepared, or preparing, well then their readiness should be reflected in their IP strategies.

The infographic below was prepared by, a business intelligence data company that specializes in tracking IP and innovation performance. It makes sorry reading for some banks, though American banks are way ahead of their European counterparts.

The research behind the infographic answers two simple questions – how many patents have been granted to these major bank; and what key areas of IP do they try to protect?

So, with that introduction here is my interview with Deltasight CEO Taavi Raidma:

What is Deltasight’s vision and mission? What do you want to achieve?

Our vision is to improve the efficiency and speed of global innovation. We achieve this by creating a bridge between patent and business data to provide practical and actionable intelligence about innovation. One of our goals is to make the abundant and valuable information in patent documents more readily available to the business community through visualizations and automated interpretations. Deltasight is not a patent search tool; our main focus is on the organizations and people behind the innovations.

Deltasight seems to be using infographics as a means for communicating this information to users can you tell us a little more about why you have gone in this direction?

Our user tests showed that visual solutions were far better comprehended than any alternatives when presenting complex data. And I believe it’s particularly useful in the IP space where the format of information has traditionally been a fairly big barrier for use of the information, for example, by business executives. We use infographics as a way to give a glimpse of our approach and its value, but the full platform provides much more – from visualized innovation profiles of specific companies, to sector overviews and entity comparisons.

How did it all get started?

We actually started as a research crowdsourcing platform back in 2011 and shortly after raised venture funding in the United Kingdom. About a year into developing that business (by then we had a community of about 2300 researchers working for us) we recognized that there were much more efficient ways of achieving our goals. While human element is surely very valuable in many cases, we saw that in a field where the amount of data grows exponentially every year, we had to focus on automating the system as much as possible. Today, all of our processes are exclusively based on automated data analysis and we use machine-learning algorithms to cope with the changing amounts and structure of data.

Since the majority of the analysis is automated can you share with us some details on what type of data standardization, or reductions are conducted in the background?

Our data comes from very different sources and the first step is to fuse it all together. It might sound easy, but gets rather difficult as the scale increases. Especially when dealing with things like misspellings, multiple people having the same name, etc. But the effort is worth it as we end up with a well-structured graph database, which extends beyond the IP domain. This means that end users get to do queries, which wouldn’t otherwise be possible (for one, think Facebook Graph Search for patents).

What solutions are you providing and how is your approach unique?

We started with the core belief that for effective analysis of innovation, the focus needs to be on the innovators, not single documents. So on Deltasight, the primary analysis happens on the level of companies and individuals – we provide visual overviews on what specific companies and people are up to, how they compare to others, what litigations they are involved in, what is their risk of litigation by NPEs and much more.

On the technical side, we opted to use graph databases to be able to easily map all the connections between the different entities as well as effortlessly add additional data sources – creating what we call the Innovation Graph. By applying network analysis and self-learning clustering to the Innovation Graph, we open up new ways for identifying emerging players in specific fields, spotting early trends and discovering potential IP clashes.

The use of graph databases and network analysis in particular seems to be increasing in the world of patent analytics; can you share some additional thoughts and details on the power of this technique?

Graph databases are not a silver bullet, and there are still many applications where traditional databases excel. But they certainly provide substantial benefits in specific use cases. Firstly, graph provides a very natural and flexible way of storing information. IP information is becoming increasingly important in business context and organizations need to cross-reference this information with a constantly growing range of other data sources. Graph database lets us add new data sources, entities and connections between them very efficiently. Secondly, we can use the graph and the mapped connections to evaluate the importance or relevance of specific companies, people and patents. And thirdly, we can observe the changes in the network to find insights into otherwise hard to spot trends. For example, if we see a growing movement of people with a specific skillset from one industry to another, it can tell us something quite unique. This hopefully helps us predict future innovation way before the first patent documents are published.

So what can a new user expect with regards to an interaction with Deltasight when they engage with your organization? Is Deltasight a product or is it more of a service?

We are a product company but do offer our expertise on patent data, visualization and data analytics on a consultancy basis as well. And we’re always looking for new interesting contacts and partnerships.

Who is the primary customer for Deltasight? Will the system be used by analysts or decision makers?

As I mentioned earlier, one of our goal is to make patent data more useful and comprehensible for the business community. I think the main purpose of the whole patent system – making sure inventions are public and available to everybody after a certain time – is still extremely underutilized. Part of that is because people are unreasonably scared of using patent data, but moreover it’s an accessibility issue, which we hope to solve.

At the moment, our clients include professional investors and private equity companies who use Deltasight for quick and easy IP due diligence, and we also have on-going projects with IP and technology firms as well as technology transfer offices.

Who are the people behind Deltasight?

My own background is in economics and consulting. Before Deltasight, I was a business consultant, helping startups and universities with their R&D and export strategies as well as IP issues. I have founded a few other companies in the marketing and e-commerce sectors and my academic background is in economics, innovation systems and economic development.

My Cofounder and our CTO Taavet Kikas has years of experience with machine learning, data mining and development of data-intensive systems from both the commercial as well as academic sectors. His academic research was on artificial intelligence and computational linguistics.

Our Chairman Donal O’Connell is former Director of IP at Nokia, currently runs his own IP strategy consultancy Chawton Innovation Services and teaches IP strategy at Imperial College Business School.

We also get lots of help from our advisor Mark Cordy, formerly of CPA Global and currently the European Director at a big data company Recommind, and our angel investor Arvi Tavast who is an expert on language sciences and natural language processing.

Any final thoughts or comments on the value proposition associated with Deltasight?

We love data and aim to improve its value through intuitive products, insightful content and visually effective user interfaces.

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