Every week more than 100.000 new patent documents are published. Monitoring patent documents is crucial for staying ahead of competitors and maintaining a competitive edge in your industry. However, reviewing and categorizing new patents can be a time-consuming and laborious task especially with the number of patent documents that are published every week.
Both IamIP and Sartorius, a long-standing client of ours, developed a common understanding of all these challenges, and for this reason decided to collaborate to develop a feature that will enhance the user experience on the platform and that will make the patent monitoring easier and faster.
Now, we are excited to announce the release of our newest feature, the AI Patent Categorizer.
The AI Patent Categorizer
The AI Patent Categorizer is a new AI-based feature that allows users to navigate among millions of patents more easily. It sifts through the database and automatically identifies the most relevant documents. It also provides the user with an AI-generated confidence score of every result. A mathematical model categorizes the patent documents into “relevant” and “irrelevant” and ranks the search results with a binary score of (1 and 0) score relevance.
The AI Patent Categorizer also provides the user with an AI generated confidence score of every result. The feature considers various components of patent documents, including the title, abstract, claims, description, and applicant information. By considering these fields, it aims to comprehensively analyze patent documents and provide valuable insights and categorization. What’s important is that the AI can be further fine-tuned to capture potentially problematic areas with greater accuracy based on weekly monitoring feedback, which made the feature stronger and more effective in its work. The fine-tuning is tailored to each customer based on provided data.
The Process
The workflow for the IamIP AI Categorizer involves several stages to ensure effective categorization and analysis of patents. Here are the steps that are part of the process:
- Agree on Monitoring(s)
- Gather training data set
- Train and set up AI model
- Capturing of new patents
- Categorizing of new patents by AI model
- Intellectual review process
- Re-train AI model
Results
After conducting extensive tests on the AI Patent Categorizer, Sartorius and IamIP have reached the following conclusions:
- The AI Patent Categorizer has demonstrated the potential for up to 80% time savings in the patent categorization process.
- The success rate of the AI Patent Categorizer has shown an impressive improvement of over 90% in identifying the relevant documents, compared to traditional methods.
- The automation provided by the AI Patent Categorizer allows for round-the-clock operation, providing continuous support and efficiency.
After implementing the AI Patent Categorizer, Sartorius had notable improvements in the weekly patent monitoring process. Its impact was significant, providing several advantages over traditional methods.
Take a look at our case study with Sartorius if you would like to know more about the AI Patent Categorizer and its use cases and don’t hesitate to contact us if you would like to receive a demo of the new feature.
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