Relativity is banking that Text IQ's technology will help to drive improvements to its own platforms—in particular the AI and machine learning functionality in tools like RelativityOne and Relativity Trace.

Text IQ, a machine learning system that parses and understands sensitive corporate data, has raised $12.6 million in Series A funding led by FirstMark Capital, with participation from Sierra Ventures. Text IQ started as co-founder Apoorv Agarwal's Columbia thesis project titled "Social Network Extraction From Text." The algorithm he built was able to read a novel, like Jane Austen's "Emma," for example, and understand the social hierarchy and interactions between characters. This people-centric approach to parsing unstructured data eventually became the kernel of Text IQ, which helps corporations find what they're looking for in a sea of unstructured, and highly sensitive, data. The platform started as a tool used by corporate legal teams.

Text IQ chief executive Apoorv Agarwal says his software's job is to spot a needle in a haystack – but a costly one. Make a mistake in discovery during litigation, and a company can face sanctions of tens or hundreds of millions of dollars, he says. Like other startups, Text IQ's raised funding to solve that problem. Unlike others, Text IQ is profitable. And for its first outside funding, it's taking only about $3 million from top investor Floodgate and a group of veteran legal counsels in a seed round its founders say could be the only money it ever needs.