Dear All,

We are piloting a classification use case with a customer that may be of interest you.

  1. Do you have internal labeled data?
    • This can be patent or non patent literature that you manually labeled as relevant/irrelevant, or with other proprietary technical categories.
  2. Do you reuse this data often, or perform labeling often?
    • Use cases include - labeling weekly patent alerts, analyzing internal or external portfolios, etc
  3. Do you wish to save time? 
    • If this is a recurring task - do you wish you could speed it up somehow?
  4. Do you wish to reuse this data for new projects and other use cases?
    • This is really your secret sauce - these labels capture your technical expertise.
    • What do you do after one project - delete or file all this work away?

We provide a cloud or desktop solution that chews up your data to train a smart AI CLASSIFIER.

You can feed it a new document to classify using your proprietary labels.

Our CLASSIFIER spits out the correct labels with ~95% accuracy for binary classes, and ~98% accuracy for the top 2 non-binary classes.

We also provide an 'estimate confidence' for each label, to help you curate the weaker estimates faster.

Put your knowledge to work!

  • No labels