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What is NLP technology
Natural language processing is an artificial intelligence (AI) technology that enables a machine to recognize and decode the nuances of human language. It processes unstructured data, analyzing it in terms of accuracy, spelling differences or semantic meaning. It tries to understand grammatical syntaxes and relationships between words and phrases just like a human does.
NLP is the component of text analysis
Text analysis uses natural language processing (NLP)
to transform unstructured text in documents and databases to obtain insights and patterns. It enables organizations to use the enormous amount of information at their disposal to make key decisions.
Get detailed information with NLP technology.
From information extraction to sentiment analysis. We will help you discover new insights contained in the text, driving your NLP algorithms and machine learning models.
We provide natural language processing services enabling text analysis used for mood analysis, information extraction, intention recognition and content categorization.
We offer solutions based on artificial intelligence using the best NLP techniques and tools.
Deep understanding of data monetization models and techniques.
A team of experienced specialists in the field of widely understood AI and ML.
Close cooperation with the academic community. Contribution to the development of science and knowledge.
Use of proprietary software components.
Use of modern analytical tools and advanced logic.
If your goal is to analyze large amounts of text data, including consumer opinions, improve the quality of user experience or increase their level of engagement, this solution will be perfect for you. Choose from our various NLP products to suit your specific needs.
Abstracts generating
Automatic generation of a text fragment to a shorter version, while maintaining key information elements and meaning of the content.
Objects detections
Determining the content of digital images and its classification e.g. whether it shows a human, a car or something else, but also the detection of various classes of objects in one image.
Keyword extraction
Automatic extraction of the most important words and phrases from the text. It plays a vital role in locating and categorizing an article in terms of information retrieval systems.
OCR
Character recognition in pdf documents or images. It helps you manage large volumes of documents more efficiently without the need for human intervention.
Synonym search
Search for synonyms of a word by considering its meaning and context. Finding similarities between sentences, searching for similar documents.
Named entities
Detect and classify named entities in unstructured text into predefined categories such as people names, organizations, locations, etc.
Processing tables
Extract information that is distributed in tables that are part of forms, preserving context, order and content within single table cells.
Similar documents
Based on the retrieved keywords, named concepts and language taxonomy, the system finds documents with similar content and contextual content.
Debt collection companies
On a daily basis, they use vast archives of electronic, multi-page documents, available in various text formats.
The problem can be the extraction and proper analysis of huge amounts of unstructured information allowing to carry out an effective investigation of claims, in accordance with the law and internal procedures.
The use of text recognition and processing mechanisms will allow the rapid and error-free processing of large amounts of documentation in an automated manner, and searching through voluminous archives will become much easier and faster, which significantly affects the efficiency of the recovery process.
Ministry of Development
Problem: an ever-increasing number of information and text documents that are increasingly difficult to manage.
Solution: a system was implemented that allowed efficient cataloging of documents, creation of a mechanism for intelligent search of information by context and content, and sharing of accumulated knowledge within the entire organization. As a result, the process of preparing materials on the basis of up-to-date knowledge was streamlined.
Energy operators
Facing an increasing number of complaints on a daily basis. Faced with regulatory requirements, the timely handling of complaints is becoming crucial in terms of costs, generated by the heavy involvement of operational personnel, as well as the need to pay compensation to customers whose complaints have not been resolved in a timely manner.
The use of DoRIS, based on natural language analysis (NLP), will facilitate the processing of an unstructured stream of information in the form of documents, scans, e-mails, web form data, etc. It will handle a range of cases and queries in an automated manner, allowing it to speed up, the claims process.
Efficient, fast and automated complaint handling will allow not only to meet complaint deadlines, but most importantly to ensure that customers receive the attention they deserve and that their case is handled fairly and in accordance with expectations, which will significantly reduce compensation costs.
Development companies
Having an extensive, distributed repository of documentation in a wide variety of formats: word, pdf, xls summaries, scans and image files.
It becomes a major challenge to quickly and flawlessly check the completeness of the technical documentation of a project / investment. Manual verification is tedious and cumbersome, due to the volume and variety of documents (several hundred pages!) and their multiple use within different projects.
Using NLP methods, the DoRIS system can be trained on selected corpora of documents included in a technical project to extract key information (decision numbers, effective dates, document categories) and classify documents and verify the completeness of the entire documentation package.
Banks
Receiving an average of about 1,000 letters per month from regulatory institutions requesting
The manual verification process is costly due to the time-consuming nature of processing each document and finding the relevant information. In addition, it is fallible because the correct preparation of information depends on many people.
Implementing an NLP-based system capable of accurately recognizing the context of a request can speed up the workflow process and thus reduce the response time from three days to just a few minutes, raising the quality level of prepared information.
Natural language processing (NLP) is a technology that allows computers to "understand" human language and act as requested to act. Voice assistance (speech recognition) and chatbots these are the most popular uses of NLP, but that's not all. This technology offers companies many benefits in many ways - from call analysis and customer service to system review, orders and cost cutting.
The element "processing" means that the textual information can be understood in its context and the intention can be distinguished from unstructured data. It is a powerful cognitive ability that supports many business processes. Let us guide you to the most productive NLP implementation considering your area of operation.
