Allows employees of intelligence and law enforcement agencies to quickly identify/verify a required individual in an array of video and/or graphic files for further processing or narrowing down the search for a specific person.

Enables quick processing of large volumes of digital images (photos, videos, multimedia data) and stores data about objects of various types (people, vehicles, animals, weapons, locations, etc.) for further analysis by other modules.

The solution is used by intelligence and law enforcement agencies for real-time processing of large volumes of audio data obtained from various sources (COMINT, OSINT, HUMINT, etc.) with the purpose of their primary filtering based on the specific language.
Subsequently, the obtained results can be directed for speaker identification and transcription of their speech.

The solution is used by intelligence and law enforcement agencies for real-time processing of large volumes of audio data obtained from various sources (COMINT, OSINT, HUMINT, etc.) with the purpose of filtering the data based on the gender of the speaker. Typically, this functionality is part of a voice-based person identification solution. However, if necessary, it can also be used as a standalone module.

The technology is based on machine analysis of unique human voice features and is capable of verifying (checking) or identifying (determining) a specific person among an array of audio files or in a data stream based on voice samples.
In practice, this functionality is used for automatic processing of large volumes of audio data obtained from various sources. This technology allows for quickly selecting from millions of audio files only those containing conversations of individuals of interest and, if necessary, linking the obtained results with additional informational resources to gather comprehensive data about a specific person.

Transcription is actively used by radio reconnaissance units and law enforcement agencies for machine processing of large volumes of audio data obtained from various sources (OSINT, COMINT, HUMINT, etc.). The generated text files are stored in a database or on the local disk for further interactive editing and report preparation.

Fast processing of large volumes of text files. Search and selection based on specified criteria (categories, topics) for target text or audio files. The search based on criteria and templates is performed in files with the .txt extension (UTF8 encoding). All input files (archives, email protocols, text files of other formats) are automatically checked and, if necessary, converted. The functionality offers a cascading method of organizing search criteria - words/templates can be grouped into categories, and these, in turn, form topics. Therefore, if any of the specified criteria are found in a text file, that file will be associated with the corresponding category and topic. The selected target files can then be further filtered by the operator, and the search results (found criteria, number of matches, positions of key words, etc.) are stored as metadata.

Allows for the quick translation of large volumes of text files obtained from various sources (OSINT, COMINT, HUMINT) into the target language. The translation accuracy depends on the training level of the neural network for the chosen language package. The machine translation module also enables searching for required data based on different criteria and provides additional analytical information in the summary file.

The machine translation module incorporates state-of-the-art advancements in neural network training, ensuring high translation accuracy through semantic and morphological analysis of the original text. The latest generation of machine translation technologies comprehensively processes textual content and achieves more precise translations compared to previous generations relying on statistical algorithms.

The machine translation module is also used in conjunction with language identification, speech transcription, and image-to-text conversion functionalities.

Automatic processing of large volumes of text files and selection of messages of interest. Comprehensive analytical processing of the obtained data is carried out based on a set of specific criteria, including language identification, content summarization, semantic comparison, metadata classification, text sentiment analysis, thematic selection, optical character recognition of scanned text, and conversion into an acceptable format for machine processing.