AI Business recently caught up with Emilio Matthaei, CEO of LEVERTON. As a passionate data strategist, entrepreneur, ex-banker and researcher, Emilio’s mission is to revolutionise how individuals work with data and documents.
Based in Berlin, LEVERTON develops and applies disruptive deep learning and machine learning technology to extract and manage data from corporate documents – in more than 20 languages.
Their solutions enable clients from the financial and real estate sectors to optimise their contract management significantly, manage operational teams more efficiently and process transactions faster. LEVERTON’s smart data technology manages asset documentation with an underlying face value of more than €40 billion.


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Emilio Matthaei of LEVERTON


We begin by discussing LEVERTON’s key proposition. Emilio tells us how his team look at a company’s documentation differently:

“We see complex documentation with hundreds of pages and multiple amendments as the unstructured repository of historical management decisions. Our software helps turn them into structured data”.


By extracting and managing document data in so many languages from around the globe, LEVERTON is able to build a smart data core at an international scale. But their software does much more than this, as Emilio explains:

“By applying intelligent technology, data becomes transparent, data quality is improved, and processes are accelerated. For our clients, implementing our deep learning technology results in a significantly more efficient information extraction and a faster due diligence processes which ultimately leads to shortened transaction times.

“Throughout the lifespan of an asset, our clients can gather, store, and access relevant data within all documentation that has accumulated. Clients can always keep their core data up to date and consume multi-language portfolio data in their preferred language”.

And the result?

“Having instant access to the core data, companies can leverage the information at hand for more educated, faster, and better decision-making”, Emilio points out.


Reflecting on the early stages of LEVERTON, Emilio explains that they we were aiming at four main stakeholder groups: servicers (such as lawyers, capital market advisors, etc.), managers (asset, property and facility managers), investors (institutional and opportunistic) and large corporates:

“We identified that some of these groups were truly interested in using our unique technology for efficiency improvements, i.e. to become faster at executing certain time-consuming tasks and to reduce resources required – both human and financial.

“Other customers wanted to improve their internal structures and processes to make them more efficient, i.e. to strategically use structured data during the lifecycle of assets and documents”.


Now, LEVERTON are working with some of US’s financial heavyweights, from Brookfield Asset Management, to Cerberus Capital Management through to giant multinational Goldman Sachs. Their approach to key partnerships reflects their company mantra:

“We have been able to build strong partnerships with various industry leaders, thereby spreading our relationships across the globe and gaining market share in a given market vertical. At LEVERTON, we aim to focus on doing specific things truly great, rather than everything just mediocre”.


But forging strong relationship has not been without its challenges. Emilio details a key obstacle that LEVERTON share with many startups:

“We experienced that large organisations tend to make meaningful technological decisions a lot slower than small organisations, in particular in Europe. Enterprise sales for a disruptive deep learning technology is often held back by legal departments, technology vendor reviews, and the inaccessibility of key decision makers”.


Emilio and his team addressed this problem shrewdly – by speaking to the AI pioneers:

“We navigated around such difficulties by specifically identifying key leaders and change agents who helped us to promote our technology internally at our clients. Additionally, we have built the technical and organisational measures to comply with international standards and to make sure that we can guarantee the highest possible security standards for our customers”.


Looking ahead to the future, Emilio points out that for a company of LEVERTON’s size, it is not yet possible to scale on a global basis in several different industry verticals at the same time. Instead they consolidate and build from their existing strengths:

“We focus on the real estate and finance verticals and build our product for global usage. At the moment, we sell our technology to the real estate and finance industry out of Berlin, London and New York”.


But their deep learning technology, as well as the LEVERTON platform, is built independently from any given industry vertical. As a result, the LEVERTON team have found themselves in several discussions with large, global software giants that want to integrate their solution for other verticals like insurance and credit:

“These discussions are truly exciting because our technology is now in a stage where it can be spread across other industry verticals – for example, with large distribution partners”.


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LEVERTON are sponsors of The AI Summit in San Francisco on 28-29 September, where the most exciting startups, together with the long-standing giants of the tech industry, will meet with 600+ CxOs from the world’s leading enterprises. To find out more, visit:


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