If you have invented anything, or you have supported those who have, you know the importance of getting a patent. You can contact expert lawyers from a reliable law firm like Thompson Patent Law to learn more about patent laws and take their assistance with complicated legal procedures in obtaining patents and trademarks. You also know the importance of the searching related technologies in order to obtain and protect those patent rights.
Unfortunately, every patent search company has relied on old and inadequate methods to conduct patent searches. Every company, every time. –David Hunt
This has resulted in a disservice to patent practitioners who have the critical role of delivering informed legal advice to innovative companies. This is a greater disservice to the innovators who spend immense capital to create and protect intellectual property worldwide.
The patent community has witnessed small innovations, but none that resulted in a complete patent search. They have included:
- The move from physical records to electronic search tools
- Development of Boolean-based tools that reduced the need for a physical presence at a library
- Availability of non-patent literature resources that expanded data coverage
- Semantic search engines created to replace the human patent analyst, but failed
- Crowdsourcing that attempted to compete on breadth and accuracy, but failed
- Offshore providers that attempt to compete on price, but sacrifice quality
How Would I Know This?
With my colleagues I founded and led Landon IP, the world’s premier professional patent search firm with hundreds of patent analysts in 6 countries, co-wrote the definitive book on patent searching, used all of the available resources to conduct professional searches, invented software that compared them, and led Patent Resources Group (PRG) that educated nearly 1,000 people on patent search best practices.
The Need for an Ensemble Method
We know the patent community demands real innovation!
In our effort to raise the bar, Ensemble IP was founded by these five leaders, who have over 100 years of combined expertise in creating the modern patent search firm. We believe real innovation results in reliably comprehensive, accurate patent search results.
Previous developments failed to achieve dramatic results as none of the them could accommodate the vast increase in the amount of data that needs to be searched.
The dictionary definition of ensemble is helpful to understand this new approach:
- a group of items viewed as a whole rather than individually.
- in machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms.
As our name suggests, Ensemble IP applies a collection of approaches to improve patent search performance. These include modern business management, personnel development, internal crowdsourcing and collaboration, the strategic use of specialized database tools, and the best of machine learning to complement the patent expertise of the analyst.
We rely on human experts to find, read, and determine the relevancy of each reference. However, we drive innovation by placing the best A.I. systems in the hands of analysts at various stages of the patent search process to dramatically improve results. Ensemble IP’s patent analysts validate their results using powerful machine learned algorithms which help them to cite as much as 20% more instances of highly relevant prior art.
Ensemble IP blends native language skills to improve search results beyond what humans or machines can achieve by themselves. We study and use the latest algorithms and software tools. We help improve many of them.
As we strive to reshape the patent search field, you have a right to expect more than you have received from any patent search entity in the past or present. Let us help you reach that milestone.
For more information
For more information, consult this important white paper that shows how artificial intelligence (AI), when combined with patent search expertise, dramatically improves prior art search results.