Our overall platform runs on plenty of natural language processing automations, which can be defined by the user. Now, the use cases our users face have different challenges, and require different automations. This is why we have implemented bricks: a collection of open-source and modular automations that can be stacked together, enabling users to customize the platform to their use cases with ease.
Browse bricks to find gold nuggets for your projects; enrich your texts e.g. with sentence complexity estimations, sentiment analysis, and more.
Classifiers summarize information. Think of them as functions returning values, i.e. one input = one output.
Extractors retrieve information. Think of them as functions yielding values, i.e. one input = arbitrary number of output.
Generators produce new data. Think of them as functions returning values, i.e. one input = one output, but that output is sequential.