is a field that deals with the processing and analysis of people's natural language using machine learning algorithms and models. NLP includes various tasks such as information extraction, text classification, text generation, machine translation, tonality analysis, semantic ambiguity resolution and much more. The main purpose of NLP is to allow computers to "understand" and "process" natural language in the same way that humans do
NLP (Natural Language Processing) in machine learning
Identification and classification of specific elements, such as names, locations, dates and other significant attributes, in structured or unstructured data
Definition and classification of the emotional coloring of textual information for the recognition of positive, negative or neutral shades, as well as for monitoring public opinion
Preparation of datasets for training NLP and NLU models, with built-in personalization functions, tonality analysis, recommendation systems and feedback
Evaluation of GPT responses
Checking the quality and accuracy of the generated responses to improve the performance of GPT models, taking into account the feedback of real users and the norms of public safety and ethics
Working with texts in 40+ languages, moderation of automatic translations, transcription and voicing of texts by native speakers and people with the necessary accents
Collection and processing of text information from sites and marketplaces of interest for market research, competitive analysis, forecasting and improvement of know your client systems
Stages of work
Leave a request on the website for a free consultation with an expert. The account manager will guide you on the services, timelines, and price.
We will conduct a test pilot project for you and provide a golden set, based on which we will determine the final technical requirements and approve project metrics.
We prepare a contract and all necessary documentation upon the request of your accountants and lawyers.
We form a pool of suitable tools and assign an experienced manager who will be in touch with you regarding all project details.
Data uploads for verification are done iteratively, allowing your team to review and approve collected/annotated data.
You pay for the work after receiving the data in agreed quality and quantity.
Conducting a pilot
You pay for the work after you have received the data in the established quality and quantity