Seravia is a technology company and computer science lies at the heart of everything we do. We pride ourselves on our deep technical skills, passion for learning and eagerness to take on the seemingly impossible. We regularly confront problems that seem too large, too hard, or too complex: machine learning, large-scale data warehousing, searching unstructured data. This enthusiasm for hard data problems starts with our management team:

Thomas Escobar, CEO

There are only a few places in the world where Thomas could combine a passion for startups, big data, artificial intelligence and corporate transparency in a single place. Seravia is one of them. Prior to founding Seravia, Thomas was a Product Manager at Google, Inc., where he led the development of software to manage Google’s global sales and operations during its hypergrowth phase. His teams applied Google technologies to the problems of international billing, corporate compliance and large-scale data warehousing. Thomas holds an MBA from INSEAD and is a magna cum laude graduate of Tufts University.

Danny Yang, PhD, CTO

For almost a decade Danny worked on applying machine learning to the problem of computer vision, first as a PhD student and later as one of the first employees at the startup (later acquired by Google). At, Danny created algorithms for face detection, clothing similarity and reverse engineering search rankings. Today he applies some of the same methods to unlocking patterns in business and legal data. Danny’s prodigious academic career spans high school valedictorian, chemistry and physics magna cum laude graduate of Harvard and Stanford PhD in Computer Science.

Casper Johansen, VP Business Development

Prior to founding Seravia, Casper was a Goldman Sachs Executive Director, a valedictorian 1st Lieutenant in the Royal Danish Air Force and a magna cum laude dual-degree law student. During these pursuits Casper fueled his entrepreneurial engine by founding and investing in several companies across multiple sectors and continents. An avid traveller, Casper has travelled the world and worked all over Europe and Asia. He balances all this through the love of his wife and kids.


We investigate and acquire datasets from around the world using automated data retrieval and "deep web" crawling methods.


Our analysts use our existing library of proprietary ETL tools to return clean and structured data in any format your business requires.


Raw data is rarely good enough by itself. We use advanced natural language and machine learning methods to extract entities, from people to addresses, so you can find information, not just data.


At over 200 million records, 1 billion entities and relationships and 88 countries, our existing dataset of companies, people, intellectual property, legal and financial filings make for powerful supplements to your existing data.


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