Even though FluidityIQ is an AI-native platform, we believe that strong results matter more than any technological feature, function, or architecture. Instead of adding to the hype surrounding all things AI in the current IP landscape, we chose to commission an objective analysis comparing the performance of our platform to two of the leading platforms in the market.

With the proliferation of AI-based patent searching tools, it is getting harder to determine what kind of tool will work best for your business. If you or your clients are conducting patent research in areas with cutting edge technology, tool selection is even more important if you want to be sure you are protecting your innovations.

The race is on.  With over $500B being spent on foundational models and supporting infrastructure, the tech giants are jockeying for their place as the go-to provider of Generative AI capabilities.  Surely, it’s an exciting time for us in the tech industry as models continue to leapfrog each other with new capabilities and ever-expanding context windows. 

There is an artificial intelligence (AI) arms race in many industries right now and patent intelligence is no exception. As various providers work to ensure that they are not being left behind, the user community is left sorting through all the noise to determine what kind of solution makes sense for their specific business or legal practice. This can be a difficult task, even with a reasonable understanding of AI capabilities.

At FluidityIQ we believe that the work of experts is important and should not be diluted. A researcher, attorney or R&D professional should not have to spend resources or hundreds of person hours to figure out how to become an AI expert just to do their job. They should be able to focus on their core job without the fear of being left behind. That is why we aim to democratize AI for patent research market.

At FluidityIQ, we believe that any research project is a dynamic, living, breathing process that theoretically could have no end, although could support multiple outcomes over time. Search tools that rely solely on Boolean search strings or that render a result that represents a single point in time, are not adequate today nor will they be viable with the current data proliferation rates.

The FluidityIQ Private Innovation Library (PIL) is a persistently updated self-learning environment that is designed to connect existing research with innovation trends as represented by global patent filings.