Patents are rights of ownership. They confer the right to exclude others from using your invention without permission which you may grant freely, under license, or not at all. The control of how the rights are used resides with the owner. Establishing true ownership is important when assessing a technology landscape or identifying potential competitors, partners or acquisition targets as part of making strategic business decisions.
But it can be unclear who actually owns the patent. The name on the document is just the starting point. It may be accurate and complete, but often it is not. It may contain typographical errors (e.g. Int Busness Mashines Corp), may be a variant of the common business name (e.g. International Business Machine Corp, IBM Res GmbH etc.) or may be a subsidiary company (Storewiz Inc, Netezza Corp etc.). Or it may be absent altogether as in many US patent applications.
Then factor in that the patent may have been re-assigned, maybe several times, and it becomes clear that establishing the true ownership of a patent can be a challenge. And how about identifying the complete patent portfolio for a given company? Or for a complete group of companies from the parent down through all its subsidiaries?
There are some manual techniques which can be applied to help with these challenges, but they require substantial time and effort to achieve useful results. The same can now be achieved in a fraction of the time by automating those processes and using AI machine learning to derive true ownership of patents. That’s what the newly introduced Optimized Assignee and Ultimate Parent fields within Derwent Innovation are designed to do.
Download the full white paper “Optimized Assignee and Ultimate Parent: Lifting the fog around patent ownership” here, or request a demo.
