Natural language processing (NLP)

Natural Language Processing or NLP is a branch of AI that focuses on enabling machines to understand and process written or spoken information. It allows us to build applications that can organize large volumes of data in a matter of seconds, optimize document management, analyze brand perception, and many more.

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Information extraction & document population

The technology speeds up document processing by using advanced customizable search and extraction algorithms to work with large volumes of structured and unstructured text data. When integrated into business workﬂow, it can automatically pre-populate various templates (documents, CRM-tickets, etc.) with relevant and up-to-date information from multiple sources.

Key technologies

Simple customization to support customer speciﬁc ﬁelds/entities. We can customize the solution to work with any document templates and CRM ticketing systems.

Fine-tuning on a small data set. We only need a few samples of an extraction/population template to integrate it into the solution.

Multilingual support. Our solutions fully support 30+ languages.

Document summarization

Document summarization.

The technology enables the generation of a coherent and ﬂuent summary of the main points of any text (meeting notes, analytical reports, research papers). It can help you understand the main points of the 20-page document in a matter of minutes. That is why document summarization applications are always in demand.

Key technologies

Out-of-the-box API. Our system is trained on millions of open-source documents, so it can perform summarization immediately without unnecessary tuning or customization.

Progressive learning capability. The system will improve itself with every use based on the corrections you make.

Multilingual support. Our solutions fully support 30+ languages.

Text classification

Text classification is an application of NLP

Text classification is an application of NLP that automatically categorizes text into predefined categories or labels. Text classification is commonly used in a variety of applications such as email filtering, sentiment analysis, topic modeling, and text categorization. With automated text classification, the business team gets quick access to any required information.

Key technologies

Progressive learning capability. The system will improve itself with every use based on every correction you make.

Simple customization to support customer-specific categories/classes. We can customize the solution to work with any document template.

Multilingual support Our solutions fully support 30+ languages.

Sentiment analysis

NLP method

Sentiment analysis, also known as opinion mining, is an NLP method for identifying the positivity, negativity, or neutrality of data. Businesses frequently conduct sentiment analysis on textual data to track the perception of their brands and products in customer reviews and to better understand their target market, customer feedback categorization, toxic speech detection, etc.

Key technologies

Out-of-the-box API. ur system has learned to recognize offensive speech, hate speech, positive sentiments, etc. No additional manipulations are required to launch and the system is ready for use, which saves you effort on integration and time for launching a new feature or product.

Customer feedback categorization. The system can analyze customer feedback based on the level of satisfaction, including positive, negative, and neutral responses, as well as numerical ratings. It allows you to make integrated reports and evaluate the overall impression, trends, etc.

Document matching

Document matching allows you to integrate, search and gain insights from large volumes of text data. Our solution ensures that you can quickly search through millions of documents without missing any important information.