We specialize in analysis and review of large patent portfolios. The need for such analysis frequently arises in a context of a portfolio acquisition or an M&A transaction.
The key to an efficient analysis of a large patent portfolio is human resource management. Unfortunately, the artificial intelligence alone, at the present state of technology, is not strong enough to identify valuable patents with a reasonable certainty, as good as experienced patent attorneys can.
The Artificial Intelligence and machine learning, however, has its place in our analysis. We use the algorithms in combination with our business, legal and technical judgement to subdivide large portfolios into 3 categories:
- Category 1: patents that will be analyzed by our attorneys in detail
- Category 2: patents that will be analyzed after we complete the analysis of Category 1
- Category 3: patents that will not be reviewed manually
Category 1 is usually a reasonably small group consisting of, on average, 3%-5% of all patents in any given portfolio. These are the patents that appear to be (1) in most relevant technology classes, (2) with reasonably broad claims, (3) with early priority dates, (4) with a significant number of forward citations, (5) developed by reputable inventors and businesses.
Category 2 is larger group that usually ranges between 10% and 70% of the portfolio. The exact percentage depends on the portfolio and the desired depth of the review. These are the patents that appear to be valuable but require deeper research. Going through all or some of these patents is mostly a decision determined by client’s budget.
Category 3 these are the patents that, according to our algorithms, are least likely to be valuable and they should only be looked if the review of the first two groups produced inconclusive results.