Shahram Pourazadi, Intellectual Property and Technology Manager

Twelvivo is a boutique innovation advisory firm specializing in comprehensive and sustainable consulting for high tech start-ups and scaling companies, from ideation to commercialization. Shahram Pourazadi, IP and Technology Manager at Twelvivo, leverages his PhD in mechatronics to engage with clients at a deeply technical level, ensuring their innovations are adequately protected and monetized. A crucial part of his counsel involves conducting thorough prior art searches to identify points of patentability and revealing IP intelligence on key competitors.

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One of Shahram’s clients, developing a business analytics platform, needed help protecting their IP. After months of R&D and product iterations, this early-stage company demonstrated early traction and sought patent protection to stake their claim in the space. They consulted Twelvivo on their IP strategy, starting with a patentability search, aiming to file their first patent application as soon as possible. 

Traditionally, this process is time-consuming, involving comprehensive keyword searches combined with patent classifications and assignee/inventor name filters. Each relevant patent must then be thoroughly read and analyzed to adequately interpret claims and evaluate similarities. To make matters worse, specific keywords can be missed, making this arduous process less than ideal. Following a discovery interview to scope out the product’s main features, Shahram turned to NLPatent’s AI-based search platform to cut through the noise and generate better results efficiently.

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Shahram described the product’s main features in natural language and instantly uncovered related patents within the target technology area. By utilizing NLPatent’s Relevance Analysis feature, which highlighted the similarities and differences between his client’s product and each relevant patent document, he identified two features in his client’s product as likely novel and reported the findings to his client immediately. Due to the clarity of the analysis, Shahram included NLPatent’s Relevance Analysis, verbatim, in his report to the client.

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Through his analysis, Shahram not only accurately assessed patentability but also illuminated key product features that could pose potential infringement risks. This led him to recommend a freedom to operate (FTO) analysis, which the client agreed to pursue. Once again, using NLPatent’s Relevance Analysis feature, Shahram mapped product features and risk areas, providing recommendations on how to navigate their IP strategy without exposing undue infringement risk on third-party IP. This proactive approach allowed his client to focus their R&D efforts on designing around risk areas, leading to further innovation and technological improvements.

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NLPatent’s contextual AI-based search and Relevance Analysis feature empowered Shahram to improve the quality of his patent research, effectively assess patentability, and safely navigate potential risks. The time savings further enabled Shahram to offer this otherwise costly service to his client at a fraction of the usual price, resulting in extremely effective and affordable counsel.

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