Text IQ, a machine learning platform for parsing sensitive corporate data, raises $12.6M

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.