I work in a firm that deals with patents in various ways. Often my friends/relatives come up with ideas and ask if their idea is patentable. Now how does one identify if their idea is patentable? And more importantly, should one patent their idea? Patenting is quite expensive—it may cost anywhere between $5,000 - $50,000. And a prior art search, i.e., a way to determine if your invention is patentable, also requires thousands of dollars if patent professionals conduct it.
Prior art search/patent search is expensive because it requires the searcher to create complex search strings, sift through hundreds if not thousands of documents, and come up with out-of-the-box ways to identify relevant prior art. Companies with a big pool of inventors and high R&D budgets can afford it all. But when it comes to individual inventors, it's pretty challenging.
I can conduct a decent search using free resources like Google Patents/Espacenet. However, I still had a quest for something more simple and intuitive, even for people from non-IP backgrounds. My quest led me to another free resource called
It was fun to run some inventive ideas through it – as it understood the ideas in simple English. I explored the search engine a bit more and found some more interesting features like query mapping, limited yet relevant results, the ability to save results, etc. And in empathy, as a tech enthusiast, I want to help individual inventors try this free, open-source patent search engine as well.
Reason #1 - Doesn’t Require Complex Keyword Search Query Creation
Reason #2 - Returns Only The Top 10 Most Relevant Results
Reason #3 - Conducts Intelligent Query Mapping, Including Synonyms
Reason #4 - Offers Zero Budget Prior Art Search
Reason #5 - Continuously Evolving Being Open Source
Reason #6 - Offers Results Saving and Report Generation
Reason #7 - Conducts Search in Humongous Pool of Data
Reason #8 - Helps Innovate Faster
As mentioned above, inventors need to state their ideas in plain language. PQAI will parse the text of the inventor’s query in natural language and query the patents in patent language.
Usually, patent search strategies involve keywords, classifications, inventors, and patent office databases amongst a whole host of sources. Your query and search results will look like this:
On the other hand, PQAI makes the job easier for you, with you writing your search query in natural language.
If you run the search query “(object*1 NEAR over*2) AND ((virtual OR augment*2) A 2 reality)” on Google Patents, the search engine will spit out about 1,12,000 results. Additionally, the relevance of results generally drops as you go down the list.
Ordinarily, going through hundreds of documents to find one specific and relevant piece of information takes most of your time. Essentially, you’re just spending time reading documents that you will eventually discard. On the other hand, PQAI makes life easier for inventors by only giving the top 10 most relevant results.
Usually, when you run a prior art search query, you will find it challenging to judge patents from their titles. For many results, you’ll have to consider the relevance of the patent by opening the documents in a separate tab and then going through the complete text, trying to narrow down on the relevant sections, if any. Adding to your problem is that a typical patent contains about 10-12 pages of text!
When PQAI identifies results, it goes one step beyond. It picks out relevant parts of documents matching your query. The snippets allow you to judge the relevance of query results directly from the search results page. Thus, you spend less time sifting through irrelevant results.
UpCounsel
PQAI, on the other hand, is an excellent option for carrying out a zero-budget prior art search.
Whether it be Linux or Mozilla Firefox, the combined community development efforts helped bring killer features to the product. Similarly, PQAI is an open-source, not-for-profit project which is continuously evolving with the contributions of the developer community.
End users can expect to have a matured AI algorithm in the coming times, making patent searches more effective. This makes adopting PQAI right now quite a useful course of action.
Once you’re aware of the existing prior art, you’ll be better able to avoid the typical rejections that patent examiners award. For example, the examiner might give you a 102-type rejection when they find an exact prior art invalidating claims of a patent application.
Or they might give you a 103-type rejection when they combine two or more references to prove an invention disclosed in a patent application as obvious.
PQAI helps inventors avoid this. It allows saving the relevant prior art searches report in a securely downloadable PDF. This is a great option because inventors can take this downloadable resource of patentable ideas to a consultation with their patent attorneys and land in a better position to make a go or no–go decision.
With PQAI, inventors are not just limited to patents. They can include articles, research papers, R&D, and more. PQAI’s database currently stands at 11 million US patents and applications and nearly 11.5 million research papers in engineering and computer science!
Inventors can simply get more work done using a tool like PQAI. With a massive data repository that is accessible, free, and simple to use, inventors don’t need to reinvent the wheel or be neck-deep in projects only to discover that their ideas aren’t novel.
Additionally, inventors can determine what parties have brought an existing patent to fruition and what have been its applications and commercial viability. This information can hasten the process of bringing novel and viable ideas to market.
Since PQAI is a community-driven project, which