Data Extraction

Data extraction software identifies and pulls specific datapoints out of documents such as contracts, leases, and pleadings, using natural language processing to locate and extract predefined categories of information, producing structured, searchable output instead of a folder of unstructured files. Many tools also cross-check extracted values for inconsistencies, such as mismatched names or missing fields, and link each extracted value back to its exact location in the source document to support verification and defensibility. Where a needed datapoint is not already predefined, most tools allow a user to train the system to recognize it, effectively building a custom extraction model for that datapoint. Generative AI has extended this category beyond fixed, predefined fields: rather than being limited to categories set up in advance, newer tools can respond to open-ended natural-language instructions about what to extract, and let users query extracted data conversationally, making the technology more adaptable to unusual documents, one-off requests, and larger-scale portfolio analysis without custom model-building.