DiscoverText - 2026 Pricing, Features, Reviews & Alternatives

DiscoverText is a cloud-based text analysis and data science software used to evaluate large amounts of unstructured free text, survey responses, Twitter data, public comment to government agencies, and more. The semi-structured workflow allows users to create adaptive, custom text classifiers using machine-learning and crowd source coding to find relevant items, and sort them into categories such as topic or sentiment.

DiscoverText includes a number of multilingual, data science, text mining, human coding, and machine-learning features which help to evaluate large volumes of unstructured free text, and conduct precise analysis at scale. Users can create customized, reusable machine-learning text classifiers or 'sifters' using the uClassify web service in order to accurately collect, clean, and analyze relevant text data. Results can then be sorted into topic, language, gender, sentiment, mood, and various other categories. The solution's combination of data science methods and tools for eDiscovery text analytics help to shorten the process, along with features for crowdsourcing. A collaborative annotation system and adjudication methods help to improve machine-learning by ranking human annotators over time. DiscoverText also includes a patented CoderRank approach which focuses on algorithmic techniques comparable to 'PageRank' for Google search, but tailored for large-scale text analytics.

Users can take advantage of features such as Boolean defined search, interactive word clouds, n-grams, and custom mini topic dictionaries, as well as filter items by date, geography, influence, networks, place name, and a variety of other metadata values. Features for deduplication and automated clustering of similar text allow users to create groupings to further accelerate the training of machine classifiers. Custom, complex search queries and human coding schemes can be saved for reuse at a later date.