We have been accustomed to religiously collecting data but often do not have time the time to properly understand and process it. This leads to a host of risk factors associated with what’s in your organization’s data but not fully uncovered yet, especially with a movement towards customer data privacy initiatives like GDPR. Text IQ analyzes your unstructured data using AI to understand context and meaning. Why is this important? This powerful platform can determine things like organizational hierarchy and indicate privacy and compliance risks before they become a problem. Text IQ’s proof of concept has outperformed humans and the standard methods of uncovering sensitive information. Originating from the founder’s Ph.D. thesis focused on British literature, the company has built a burgeoning business with eight straight quarters of revenue growth and profitability, applying its novel technology to real problems in the business world.
AlleyWatch spoke with CEO and cofounder Apoorv Agarwal about Text IQ’s traction, future plans, and recent funding round, which brings its total funding to $15.6M across three rounds.
Who were your investors and how much did you raise?
Text IQ closed a $12.6M Series A led by FirstMark Capital with participation from Sierra Ventures.
Tell us about the product or service that Text IQ offers.
Text IQ develops advanced AI solutions for detecting sensitive information, helping large corporations mitigate their most dangerous privacy, compliance, and legal risks.
What inspired you to start Text IQ?
I was working on my Ph.D. thesis at Columbia University using machine learning to identify social context in unstructured data. I developed a program that could scan novels and map out the characters relationships and successfully applied it to nineteenth-century British literature such as Jane Austen’s Emma. I also applied the technology to read though Enron emails, and it was able to accurately predict the company’s organizational hierarchy.
While at Columbia, I met Omar Haroun (Text IQ co-founder and COO), who was working on his JD/MBA. We founded Text IQ in 2014, launching an AI platform for finding “sensitive needles” hiding in enterprise data “haystacks.” We quickly found a sweet spot in corporate legal departments, helping large corporations mitigate their most dangerous legal risks.
Today Text IQ has contracts with Fortune 500 companies and federal agencies. Moreover, based on the results we’ve delivered to date, customers have asked us to extend the Text IQ AI platform to help them address major privacy and compliance risks related to GDPR and CCPA-like regulations.
How is Text IQ different?
Unlike other enterprise AI solutions, the Text IQ platform applies machine learning techniques to combine the power of linguistic analysis with social network analysis. By analyzing documents in relation to the individuals connected to its content and transmission, we can identify and isolate meaningful, sensitive data with unprecedented speed, accuracy, and efficiency.
What market does Text IQ target and how big is it?
Text IQ’s market opportunity includes federal agencies and Fortune 500 companies spanning pharmaceutical, financial services, insurance, technology, healthcare and other highly regulated industries. Any companies with large enterprise data sets that need to mitigate the risks and costs associated with documents that could cause irreparable reputational damage and legal action can benefit from using the Text IQ AI platform. We view this as a multi-billion-dollar market opportunity.
Who are your biggest competitors?
In every proof of concept we’ve done, the output of our technology has been compared with that of the status quo, which remains to be search terms + human reviewers. In every POC we’ve shown that we catch all the sensitive information the status quo system catches + more. We are also seeing a move from public cloud providers such as Microsoft, Amazon, and Box to add APIs in their cloud solutions that can help their customers identify sensitive information.
What was the funding process like?
We’re very fortunate in that we didn’t need to raise any funds. We’ve recorded 8 straight quarters of revenue growth and profitability and grown the team 5x since the beginning of 2019. But, our customers are asking us to help them address a range of enterprise challenges – including privacy and compliance risks related to GDPR and other similar regulations. So, we raised this Series A to expand sales, marketing, and R&D efforts, as well as to enter new markets and geographies. We’re currently focused on hiring and expect to double our headcount by the end of the year.
We were very selective when it came to investors and looked for investor/partners that would provide the most value to the organization. Matt Turck, a partner at FirstMark Capital, has deep expertise in AI and big data, and he is helping us find the talent needed to take advantage of the market opportunity as well as providing strategic guidance. Likewise, Tim Guleri, managing director with Sierra Ventures, is a proven entrepreneur who has successfully guided many emerging enterprise companies to successful IPOs.
What are the biggest challenges that you faced while raising capital?
The biggest challenge we faced was turning down some big brands that wanted to invest.
What factors about your business led your investors to write the check?
Our investors wrote checks because we’ve proven our technology and business model, delivered a 100% customer conversion and satisfaction rate, achieved and maintained profitability, and we’re successfully positioned to dominate a multi-billion-dollar market.
Our investors wrote checks because we’ve proven our technology and business model, delivered a 100% customer conversion and satisfaction rate, achieved and maintained profitability, and we’re successfully positioned to dominate a multi-billion-dollar market.
What are the milestones you plan to achieve in the next six months?
Milestones include hiring the right team, demonstrating ongoing success across a variety of customer use cases, and expanding our markets.
What advice can you offer companies in New York that do not have a fresh injection of capital in the bank?
Every company is different, so it can be hard to offer blanket advice, but one thing that we’ve proven at Text IQ is that focus on customers is critical. You can’t assume anything about customer needs and pain points. You need to create a hypothesis, test it, and build something that is a hair on fire problem.
Where do you see the company going now over the near term?
We’re in hyper-growth mode thanks to the explosion of privacy regulations and growing distrust around how organizations protect personal data. Our customers are asking for more AI-powered applications to handle sensitive information, and we intend to deliver.
What’s your favorite restaurant in the city?
The Mala Project
