• last updated : 07 November, 2022

XLSCOUT releases ‘INVALIDATOR+’ – A Patent Invalidity Search Tool 

Category: Press Release
Press Release Invalidator

XLSCOUT proudly announces the launch of INVALIDATOR+, a tool that utilizes Artificial Intelligence (AI) and Machine Learning (ML) to conduct a first-pass patent invalidation search. 

Invalidator+ harnesses the power of our proprietary Patent ParaBERT technology and state-of-the-art Reinforcement Learning to conduct a first-pass Invalidation search.  

How does Invalidator+ works? 

3 Step Invalidity Search

Invalidity Analysis with Patent ParaBERT 

XLSCOUT utilized its “Patent ParaBERT” technology wherein they fine-tuned the already trained state-of-the-art BERT model on its various multi-domain technology datasets for prior art searching. This technology helps XLSCOUT understand the natural language text within the patent documents. The Invalidator+ uses this fine-tuned Patent ParaBERT Model to understand the context of each paragraph in a patent document to provide more accurate prior art results. As a result of this, we have seen significant improvements in document similarity check and, furthermore, the Invalidator+ app can now generate high-quality first-pass invalidation search reports. 

Accurate Analysis with Reinforcement Learning 

XLSCOUT put the use of reinforcement learning to its AI-based Invalidator+ tool to get quality invalidation search reports in just 10 minutes. The Invalidator+ uses reinforcement learning to filter the noise from the prior art by pulling up the relevant results on top of the list. To be precise, it assists in conducting an invalidity search to help you determine any patent or non-patent documents that challenge the novelty and inventiveness of a patent in question. By selecting a few relevant and non-relevant results, users can apply the reinforcement to the result set. The system takes the user’s feedback and then re-ranks the results by bringing the quality results to the top and sending the noise to the bottom. 

Without reinforcement learning, users go through hundreds of results manually. By applying this process, users can skip going through the non-relevant results. Reinforcement can also be applied multiple times to a result set according to users’ different requirements/criteria. Users can then view the Top-10 or Top-20 results for each criterion to perform a prior-art analysis for patent invalidation. 

Users can quickly generate an automated invalidation search report by selecting the Top-10 or 20 results in Invalidator+. The invalidation search reports include a list of results along with relevant text mapping with the key features of the invention for enabling quick decision-making. 

To learn more about the Invalidator+, Schedule your free demo now!