Intellectual Property research technology has not advanced much over the years. Todays model still involves a laborious search and filter approach that is based on IP professionals progressively and iteratively excluding results until you find what you need. This model leaves the IP professional with two challenges:
The exclusionary search model misses out on nuance and changes in terminology, leading to missed IP
The iterative approach requires continuous human intervention which is laborious
At Convergent, we saw first hand how ineffective and laborious current systems are as we applied for our own IP. So, we worked with IP professionals to improve it using our Distributed Artificial Intelligence technology. The result of this effort was an IP Discovery Solution that leverages our AI/ML to find related IP that traditional systems fail to deliver. Read below to understand the high-level approach to our solution.
As you use the tool, our system quickly learns as you indicate your interests; building an interest model of the topics that characterize your current project. Our topic model allows us to cast a wider net than search based models.
As it learns your interests, our recommendation engine works in parallel on your behalf – digging deep and going laterally across the landscape - to find and recommend IP that is relevant to your project.
But it doesn’t stop there; armed with your specific interest model, the recommendation engine continuously and autonomously explores the IP landscape looking for new and relevant patents - even when you are not using it - to find and deliver a curated short list of patents you may have overlooked, but should consider.