Democratizing AI for businesses of all size
The way we search for information is broken.
AI solutions can be expensive. There are infrastructure costs, even if you are fully in the cloud. There are software costs and even open-source tools carry usage costs. Moreover, you need to have the right expertise in-house to manage and maintain the whole apparatus, or you need to line up the right contractors, which can be expensive.
If your business is leveraging AI to offset costs somewhere else in the business, such as by implementing a chat bot to lower customer service costs, then that may be ok because you are offsetting people costs by leveraging technology. But if you are a researcher, or a smaller business operating in a high-tech field, such as in MedTech, you might not want to spend money building an AI-based engine when that money can be used elsewhere, and you must keep up with changing technology. Smaller firms, which can be some of the most innovative, have an even bigger challenge in that even if they wanted to make an investment in AI infrastructure, they likely can’t make one big enough to compete with bigger firms.
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.
FluidityIQ offers a cost-effective AI platform that can be used to leverage an existing knowledge base to drive patent research. Our patent-pending Private Innovation Library (PIL) allows researchers to answer complicated questions without hiring outside search experts or needing to run many searches to gather enough information, only to realize there are not enough hours in the day to process the search results to determine what is relevant and what is not.
When a researcher is running a search, they generally know what they are looking for. Today, they will use that knowledge to build a series of Boolean searches to collect a group of patents that could be relevant to their search. Sometimes, they use a third-party tool that might have screening criteria to help narrow the search. Some firms simply outsource the whole function. Regardless of the method, searchers can spend hundreds of person hours seeking and sorting and not be fully sure that all the information in front of them is the right information. At FluidityIQ we believe this can all be done in-house using your existing knowledge.
The FluidityIQ solution takes your existing research to create a contextual search strategy programmatically. This search strategy is then leveraged by our AI-based solution to identify relevant patent claims from a global patent database. These claims are categorized and ranked by relevance based on your own contextual data, not the structure of a series of Boolean search strings and not by an offshore third-party expert. We maintain lineage so that the attorney or researcher can drill down through the logic all the way to the source. Along the way, researchers can curate the strategy to ensure that only the most relevant claims are associated with a search.
Importantly, all this information flows back into the researcher’s own Private Innovation Library (PIL) to update the research and organically update the library with new information from new patents filed in the future. In this way, a patentability search, freedom-to-operate report or other research reports are dynamically updated going forward and are not a static report based on the point in time the report was completed.
To learn more about how FluidityIQ can help your business, reach out to us at info@fluidityiq.com.