AI (language)
models

Creation of large sustainable corpora for AI models tailored to specific customers’ needs.

Generating synthetic data using AI models to create large data sets tailored to the needs of specific tasks. In many cases, their use can significantly improve the accuracy of training AI models.

Manual or automatic annotation of customer-provided data (labeling, tagging, classification, etc.).

Processing and enriching data with NLP techniques (tokenization, segmentation, lemmatization, etc.).

Designing AI models tailored to the specific needs of customers.

Training AI models on big data.

Adaptation of pre-trained AI models (fine-tuning) to specific customer tasks.

• Construction of specialized AI models supporting automatic communication with the customer.
• The possibility to personalize communication by adapting content to the ​specific needs and interests of each customer.

• The possibility to apply AI models to a variety of customer-facing business processes.
• Ensuring compliance with established standards of communication with the client.