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Lower the Cost of Innovation With IP Search Automation

By applying key IP analytics to determine the full technical and commercial potential of your burgeoning invention, you can act quickly to protect and market it. In the past, this workflow was much easier said than done. Evaluation stage research could take months, or even years, just decades ago. IP metrics such as risks to commercialization or patenting, potential ROI, budgetary requirements, and the type of IP protection to seek, were prohibitively time-consuming to predict. Fortunately, advancements in database searching using Boolean search made it possible to filter out irrelevant data and speed this process up significantly. The cost-effectiveness of improved search dramatically boosted ROI to help produce more, higher-quality ideas. But even for the IP stakeholders truly adept at Boolean searching, many of them outside the innovating organization, there was still a world of data that needed analyzing.

Use Database Search to Research Your Idea

If you’ve decided to pursue a given idea, written an invention disclosure, and performed initial patentability searches and landscape analyses, the next step is researching marketplace viability. This is called the Evaluation Stage and it is an innovation workflow conducted from a multidisciplinary perspective. Evaluation should include legal, commercial, and technical data. When evaluating an idea, you’ll examine and analyze the role your technology will play in the marketplace, including its monetization potential and potential competitors. These will help determine the likelihood of your technology’s success and what IP protections to seek. Questions you’ll answer with IP search workflows go to the heart of idea novelty and legal risks, and the type of IP protection your invention needs.

Understand How Search Technology Has Evolved

Available since the 1990s and early 2000s, semantic searches attempted to solve database search’s basic problem: not everyone can use Boolean search. Boolean logic was effective (and still is) but to use it effectively, you had to understand how it worked. Search engines like Google created database search systems that not only used keywords but analyzed their use within a phrase to determine semantic meaning and search intent. Search companies eventually collected enough data to start drawing correlations between words and phrases, allowing computers to make conceptual connections between disparate keywords. Keywords became the gold standard of search and search engines.’s natural language processing (NLP) tools power search results that are fast, comprehensive, and useful by using modern technology to connect searchers to all relevant data points.’s AI-enabled search product is so precise that it is used to identify conceptually connected technologies that Boolean searchers and users of less-developed NLP capabilities often miss.

As with many AI applications, NLP programs don’t automatically apply to every search use case.’s AI-enhanced search is trained and optimized in-house with the latest IP data sets to develop the latest iteration of our flagship InnovationQ+™, designed to solve problems specific to the IP industry.

Applications of AI Search

InnovationQ+ can be used by a variety of stakeholders in IP. Universities, enterprises, and consultancies can all benefit from a search platform that delivers quality simply and in minutes. IP consultant Steven Bittenson is just one example of a veteran consultant who has consolidated and streamlined his research workflow with’s innovation suite. In his use case of providing patent portfolio analysis, process modeling, and prototype development to clients, Bittenson benefits from saving time and effort.

With InnovationQ+, Bittenson applies’s Semantic GistⓇ to the unique set of problems clients rely on him to solve. Solving those problems, like pulling key references vital to evaluation-stage workflows, used to take days, even weeks. Now, it takes minutes. He’s used other supposed semantic search products before but the NLP capacity of alternatives was “in name only.”

AI Search Use Cases

Semantic Gist doesn’t just search millions of database entries quickly, although it does that with ease. It also combines the benefits of classic Boolean search with NLP so that Bittenson can deliver exceptional results for clients who need his expertise. Even with products like AI-powered semantic search already available to innovation companies, it’s still necessary to combine both search styles to get the full picture. The unique benefits of Semantic Gist stand out to a consultant like Bittenson, who’s used other search engines for evaluation-stage research before. “There was just no comparison.”

Experiences like Bittenson’s are meaningful when they are representative of larger datasets. The results are clear:’s InnovationQ+ puts powerfully integrated Boolean and NLP search together for unprecedented results. Searchers using these products can save one to two hours per search. When evaluation- research by specialists like Bittenson can involve hundreds of searches, the time savings are significant. Innovation workflows with streamlined taskflows can see a significant boost in ROI. Consolidated results and an intuitive interface accelerate inter-team communications and help consultants like Bittenson confidently bring results to clients. “The interface enables me to have a presentation format configured for the client,” creating the collaborative environment essential to innovation. “The client can immediately see the information. We can compare things, we can look back and forth. We can enlarge and easily thumb through images.”

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