Text IQ, a business-to-business enterprise data specialist, announced that it has been acquired by Relativity, the global legal and compliance technology company.
Text IQ assists organisations with large amounts of unstructured data, including public corporations and government agencies, identify sensitive information such as personal and privileged information.
Mike Gamson, CEO at Relativity, said:
“Relativity has been very fortunate to establish a very significant customer base in Canada.”
“And especially over the last few years, as the largest law firms and service providers in Canada have adopted RelativityOne, this is going to be really exciting for them.”
Text IQ is among the pioneers in unsupervised machine learning, graphical modelling, social network analysis, natural language processing and deep learning. Its technology will speed up and increase the accuracy of data breach response, lower the cost and risk in legal-privilege reviews and identify and manage personally identifiable information with privacy laws.
Apoorv Agarwal, co-founder and CEO at Text IQ, said: “At Relativity, Text IQ will continue its AI for Good initiative. The volunteer project has two aspects: the AI to Protect Privacy Tool and the Unconscious Bias Detector.”
In order to develop Unconscious Bias Detector, Text IQ has conducted research with ethicists and business leaders. The tool works by inputting employee lists and a set of performance reviews from which the Detector learns the context and patterns and identifies potential bias.
Agarwal said: “What we’re finding is that machine learning and AI is actually the right tool to use for finding unconscious bias.”
“A team of human reviewers is not the right way, because it’s a chicken-and-egg problem… We have our own biases.”
Agarwal is a specialist in natural language processing and machine learning. He has a PhD in computer science from Columbia University and was among the original team that built IBM Watson.
The “key differentiator” in how Text IQ combs through data is their use of socio-linguistic hypergraph, which Agarwal and his colleagues began developing while in academia, he says.
