SalesTech Star

Brightflag Awarded U.S. Patent for AI Innovation in Legal Operations

The United States Patent and Trademark Office (USPTO) has granted Brightflag, the AI-powered legal operations management software company, a patent for its innovative application of artificial intelligence (AI) and machine learning in legal technology. U.S. Patent No. 11,107,137 validates the systems, techniques and processes for automated analysis of legal invoices which form the core of Brightflag’s software.

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Brightflag’s patented solution applies machine learning to an extremely valuable but traditionally untapped source of insight — outside counsel invoices. The software automatically classifies invoice text into the appropriate tasks and activities to create a structured, machine-readable data set on legal service delivery, helping in-house teams to better understand and control the more than $300 billion spent annually with outside counsel in the U.S. alone.

“This patent confirms the uniqueness of Brightflag’s core technology, but its practical value is something that in-house legal teams have been confirming daily since 2014,” said Brightflag CEO and co-founder Ian Nolan. “By effectively translating legal service descriptions into objective data insights, we’ve given customers a powerful new asset in their quest to develop more value-based partnerships.”

The operational impact of Brightflag’s AI is first seen during the invoice review process, as it rapidly interprets invoice narratives and flags legal services that represent a potential breach of billing guidelines. The resulting time and cost savings realized by customers at this initial step are often significant, but the value of the associated insights can be extended to every stage of the legal matter lifecycle.

The unique data set generated by Brightflag’s AI has already enabled its customers to predict budget overruns, benchmark vendor performance, and optimize resourcing models. As the company continues to build upon the more than 100,000 hours already invested in refining its machine learning model, the team looks forward to pioneering additional use cases alongside customers in the months and years ahead.

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