Text IQ, a machine studying platform for parsing delicate company knowledge, raises $12.6M

Text IQ, a machine studying system that parses and understands delicate company knowledge, has raised $12.6 million in Series A funding led by FirstMark Capital, with participation from Sierra Ventures.

Text IQ began as co-founder Apoorv Agarwal’s Columbia thesis challenge titled “Social Network Extraction From Text.” The algorithm he constructed was capable of learn a novel, like Jane Austen’s “Emma,” for instance, and perceive the social hierarchy and interactions between characters.

This people-centric method to parsing unstructured knowledge finally grew to become the kernel of Text IQ, which helps companies discover what they’re in search of in a sea of unstructured, and extremely delicate, knowledge.

The platform began as a software utilized by company authorized groups. Lawyers typically must manually look by means of troves of paperwork and conversations (textual content messages, emails, Slack, and so forth.) to search out particular proof or info. Even utilizing search, these groups spend a great deal of time and sources trying by means of the search outcomes, which often aren’t as correct as they need to be.

“The status quo for this is to use search terms and hire hundreds of humans, if not thousands, to look for things that match their search terms,” mentioned Agarwal. “It’s super expensive, and it can take months to go through millions of documents. And it’s still risky, because they could be missing sensitive information. Compared to the status quo, Text IQ is not only cheaper and faster but, most interestingly, it’s much more accurate.”

Following success with authorized groups, Text IQ expanded into HR/compliance, giving corporations the flexibility to retrieve delicate details about inside compliance points and not using a handbook search. Because Text IQ understands who an individual is relative to the remainder of the group, and learns that group’s “language,” it might probably extra completely extract what’s related to the inquiry from all that unstructured knowledge in Slack, e-mail, and so forth.

More lately, within the wake of GDPR, Text IQ has expanded its product suite to work within the privateness realm. When an organization is requested by a buyer to get entry to all their knowledge, or to be forgotten, the method can take an infinite quantity of sources. Even then, bits of information may fall by means of the cracks.

For instance, if a buyer emailed Customer Service years in the past, which may not come up within the firm’s handbook search efforts to search out all of that buyer’s knowledge. But as a result of Text IQ understands this unstructured knowledge with a person-centric method, that e-mail wouldn’t slip by its system, in line with Agarwal.

Given the sensitivity of the info, Text IQ capabilities behind a company’s firewall, that means that Text IQ merely offers the software program to parse the info fairly than taking over any legal responsibility for the info itself. In different phrases, the know-how involves the info, and never the opposite method round.

Text IQ operates on a tiered subscription mannequin, and affords the product for a fraction of the worth they supply in financial savings when purchasers swap over from a handbook search. The firm declined to share any additional particulars on pricing.

Former Apple and Oracle General Counsel Dan Cooperman, former Verizon General Counsel Randal Milch, former Baxter International Global General Counsel Marla Persky and former Nationwide Insurance Chief Legal and Governance Officer Patricia Hatler are on the advisory board for Text IQ.

The firm has plans to go on a hiring spree following the brand new funding, trying to fill positions in R&D, engineering, product growth, finance and gross sales. Co-founder and COO Omar Haroun added that the corporate achieved profitability in its first quarter getting into the market and has been worthwhile for eight consecutive quarters.

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