We will pack your raw Data Lake in "bottles" with useful information.

Harvester — an AI-powered platform for automatic and comprehensive processing and analysis of all types of digital information, including audio, image, video and text, for the purpose of intelligence and law enforcement investigations. Modular and scalable architecture.


    Multi-source data processing and analytics
    Modular and scalable architecture
    Modular and scalable architecture
    On-premises (data security and confidentiality)
    Big data processing with high collection intensity
    Adapted for use in different regions of the world
    Automatic Code Detection
    Сan be flexibly integrated into the customer's existing analytics systems
    Hybrid approach  
    New language models can be added
    Multiple integration possibilities 
    Highly customizable for customer needs

How it works


Harvester has a multi-service architecture that allows users to quickly, flexibly and efficiently build automated systems for deep processing of audio, text and visual data.

Harvester works with large volumes of data, which will be uploaded to the Harvester storage itself or to some external storage to which the Harvester will have access. The Harvester can also store the results of its work in an external storage that the user will define. So, if necessary, Harvester will not have access to the internal processes of already existing systems of the customer. That is, the Harvester can be quite easily and painlessly integrated into the already existing infrastructure of information collection and processing. At the same time, the operation and security of this system will not be disturbed.

The result of Harvester work can be of two types:

  • Files selected and structured according to specified criteria with which analysts and investigators will work in the future. That is, from the entire vast array of data, only the necessary files will be selected, in which the data required for analysis will be highlighted.

  • An indexed database n which tags will be assigned to each file depending on what information is there. In the future, the analyst can make requests to this database himself and receive the files he needs at the moment. This speeds up the work of analysts and gives them flexibility in working with data.

The peculiarity of Harvester is that the data can be processed both by separate services and by all services at once. What's more, the user can create a data processing workflow himself, which will be customized specifically for his tasks and needs. In other words, Harvester allows users to configure various scenarios for processing and analyzing data received from various sources in order to filter out "garbage". 

Of particular value is the ability to analyze different types of data and compare them with each other. Harvester speeds up work with data and increases the efficiency of work of analysts or investigators. The number of errors during data processing is reduced.

Harvester accelerates processing and analysis of large volumes of data for faster decision-making and better insights in intelligence.

Harvester has integrated turnkey solutions that are based on multiple advanced and proven technologies. These solutions have been developed in cooperation with world-leading research laboratories that specialize in Automatic Speech Recognition (ASR) and Natural Language Processing / Understanding (NLP/NLU). We using state-of-the-art technologies developed by leading experts, which help to enhance the accuracy and reliability of data processing.

In Harvester, multiple technologies are combined to process the same type of data. This significantly expands the possibilities of processing audio and text messages, which are formed using different languages. The accuracy of data processing increases, which is especially relevant for transcription, translation and text analytics.

The system is optimal for solving tasks of constant search and obtaining information in large arrays of data using a conveyor method. Harvester also enables the operator to determine the sequence and settings of data processing, evaluate the results and quickly make decisions.


    More efficient and faster processing of massive data sets
    Faster decision-making
    High data security and confidentiality
    Expanded possibilities of processing audio and text messages
    Possibility to work with multi-language and multisource data at once
    Possibility to gather information from data that is more valuable, relevant, and useful for decision-making purposes
    Optimization for solving tasks of constant search and obtaining information in large arrays of data using a conveyor method 
    Filter out irrelevant data and compare different types of data
    Quick search of needed data in the massive data sets

Data types

Video & Images

● recognition of a person on the face (identification/verification) and analysis of portrait characteristics● people search● objects search and detection


● recognition of a person by voice (identification/verification)● speech transcription (audio to text conversion)● retraining of language models for transcription● speaker language identification in audio● determining the gender of a person in audio


● language identification● translation of text documents● keyword spotting● sentiment analysis● text document summarization● named entity recognition● text documents● categorization by predefined topics

Interface examples (TBD)


Face Recognition (FR)


Objects Detection & Identification (ODI)


Speaker Recognition (SR)


Gender Identification (GI)


Language Identification (LI)


Speech-to-Text Transcription (S2T)


Language Identification (LID)


Keyword Spotting (KWS)


Machine Translation (MT)

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