Cs Disco, Inc.

Alan Justin Lockett

Verlyn Michael Fischer

Ryan Connor Rollings

Robert Duane Harrington

Richard Alan Vestal

Brian Daniel Luskey

Jesse Abraham Ramos

Artificial intelligence based document analysis systems and methods are disclosed. Embodiments of document analysis systems may allow the reuse of coded datasets defined in association with a particular code by allowing these datasets to be bundled to define a dataset for another code, where that code may be associated with a target corpus of documents. A model can then be trained based on that dataset and used to provide predictive scores for the documents of the target corpora with respect to the code. Furthermore, this code can be applied not just to the target corpus of documents, but additionally can be applied against any other corpora.

System and method for artificial intelligence driven document analysis, including automated reuse of predictive coding rules based on management and curation of datasets or models

Artificial intelligence based document analysis systems and methods are disclosed. Embodiments of document analysis systems may allow the manipulation of datasets and associated codes by determining representations for these codes or datasets based on a machine learning model. The codes or datasets can then be manipulated using the associated representations.

System and method for artificial intelligence driven document analysis, including searching, indexing, comparing or associating datasets based on learned representations

Embodiments as disclosed may generate an organizational hierarchy based on embeddings of portions of documents. Embeddings resulting from the embedding of the portions of the documents can be clustered using a hierarchical clustering mechanism to segment the portion space into a set of hierarchical clusters. Documents can be assigned to these clusters based on the presence of a portion of a document within a cluster. In this manner, the documents may themselves be clustered based on the clusters created from portions across the documents of the corpus. The clusters to which a document is assigned may also be ranked with respect to that document. Similarly, documents assigned to cluster can be ranked within the cluster to which they are assigned. Additionally, in certain embodiments, names or snippets for the clusters of the hierarchy may be derived from the portions comprising that cluster.

System and method for hierarchically organizing documents based on document portions

A machine learning system continuously receives tag signals indicating membership relations between data objects from a data corpus and tag targets. The machine learning system is asynchronously and iteratively trained with the received tag signals to identify further data objects from the data corpus predicted to have a membership relation with the single tag target. The machine learning system constantly improves its predictive accuracy in short time by the continuous training of a backend machine learning model based on implicit and explicit tag signals gathered from a non-intrusive monitoring of user interactions during a review process of the data corpus.

Methods and apparatus for asynchronous and interactive machine learning using word embedding within text-based documents and multimodal documents

A non-transitory medium includes code representing processor-executable instructions; the code causes a processor to produce, via a machine learning model, a predicted value of a membership relationship between a data object and a target tag. The code causes the processor to display, via a user interface, the data object and the target tag and indicate a non-empty set of identified sections of one or more attributes of data object supporting the membership relationship between the data object and the target tag. The code also causes the processor to receive a tag signal, via the user interface, indicating one of an acceptance tag signal, a dismissal tag signal, or a corrective tag signal, and re-train the machine learning model based at least in part on the tag signal.

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Georgetown, TX, United States of America

Alan Justin Lockett