Startup Launches Artificial Intelligence Tool to Diagram Corporate Structures


A new legal technology company called Deftr is today launching a tool powered by artificial intelligence that helps professionals diagram intricate corporate structures. The tool reads text in real time, as it is being typed, then turns that text into a shareable, interactive graphic illustrating a corporate structure or transaction.

In a press release being issued today, Deftr’s co-founder and CEO Matthew Osman explained:

Building charts to represent corporate structures or transactions essentially by hand is a laborious process all too familiar to anyone in corporate life. It’s the reason a lot of associates don’t have weekends. Our tool automates this outdated, manual process, allowing a user to build a chart in a fraction of the time and focus their efforts on high-level, analytical work.

The tool should be of value to law firms, in-house legal departments, accounting firms, financial services and management consultants, Deftr says.

These professionals frequently need to analyze a corporation’s structure, interpret implications and strategies therefrom, and explain it to clients in plain English. The most effective approach involves transforming dense, textual information into comprehensible graphics. Unfortunately, even with modern software, it still ends up requiring manual work.

A trial version of the software is slated to be available today at

Deftr says it plans to expand its offerings beyond visualization into compliance checking. It is developing a feature that will automatically compare corporate structures against guidance from regulators.

Headquartered in Cambridge, Mass., Deftr is named for the dynamic tax ledger used by the Ottoman Empire. It received a Y Combinator Fellowship in May 2016.

Co-founder Osman was a barrister in the UK who most recently worked for a $1 billion structured credit hedge fund in London. Fellow co-founder Jacob Rosen is a data analyst who previously used predictive computational models to help detect Medicare and tax fraud. He received his master’s degree in technology and policy from the Massachusetts Institute of Technology in 2015.

I hope to be getting a demo or trying it myself soon and will report back when I do.