Patent Landscape: Extract Deep Insights Using AI/NLP Engine
Patent data is quite large, unstructured, and complex. You need cleaner, more structured data to derive deep insights. Analysis is tough and time-consuming when dealing with large datasets. A tool that can quickly analyze massive amounts of data in a...
Patent Landscape: Doing Big Data Trend Analysis
Patent Landscapes help corporations, universities, start-ups, and research organizations to understand the trends in a particular technology. It also helps to explore rewarding business product development opportunities. They use various data mining techniques to identify various patent trends. The trends...
Patent Landscape: Extracting Key Competitor Insights
Competitive intelligence is a critical factor in the decision-making process for businesses. Whether you want to be the first-to-market or if you want to gain key insights on your competitors, their IP strategies and collaborations, and any whitespace, you need...
Patent Landscape: Extracting the Whitespaces
Whitespaces in the patent landscape are gaps that are void of innovation, meaning that there is little to no patenting activity in those spaces. Whitespace extraction means identifying the lack of patent filing in a particular technology area to drive...
Patent Landscape: Making Sense out of Insights Data
Technology intelligence, i.e., generating business-relevant insights, occurs when hypotheses are generated by connecting multiple and disparate data sources. For e.g., websites, press releases, annual reports, patents, technical publications, product manuals etc. Further, they are then verified through triangulation. Today, the...
Patent Landscape: Analyse, Set & Repeat – Track Evolution
How to track evolution of patent landscape? Most patent landscapes take months to complete. The data, however, becomes outdated after the landscape analysis is completed. In their respective technology areas, 15–30 patents are published each month. The data must be...