The IP Catalyst and AI-powered portfolio engineering
IP organizations have introduced IP Catalyst capabilities in response to conventional, reactive patent creation no longer matching the pace of the businesses it serves. IP Catalysts have proven successful in engineering patent portfolios with clear business intent, rather than waiting to capture whatever happens to be invented.
One recurring issue has been that the IP Catalyst model is difficult to scale: the reach and effectiveness of any one Catalyst is inherently limited. AI changes that, closing the scaling gap and letting the IP Catalyst capability operate at the pace and breadth the business demands.
However, not just any AI will do. Generic LLMs and disconnected point tools risk noise, false confidence, and outputs that miss the business reality. The IP Catalyst capability needs purpose-built AI that embeds in the company's workflows and connects business strategy, technology landscapes, and patent positions into a single, coherent picture.
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