#01

The chatbot uses natural language processing (NLP) and machine learning techniques to analyze and interpret documents. It can extract key information, answer questions about document content, and create summaries. This allows employees to quickly get the information they need without having to manually search through extensive resources.

#02

We use advanced machine learning algorithms, such as neural networks and decision trees, to create classification models tailored to your company's specific needs. The chatbot can be trained on data from systems such as Jira to automatically categorize tickets, assign priorities, and direct tasks to the appropriate teams. This significantly reduces the time and effort spent on manual classification.

#03

We use information search and text generation techniques so that the chatbot can provide precise answers based on the knowledge base collected. We also use advanced language models, such as transformers and seq2seq architectures, that can generate consistent and natural responses. The chatbot can find the most relevant information in the knowledge base and use it to create a comprehensive answer to the user's query.

#04

We have designed chatbots to efficiently handle typical queries addressed to the service desk, such as technical problems, password resets, or access requests. Thanks to integration with ITSM systems, the chatbot can automatically create tickets, escalate issues, and provide status updates. In addition, chatbots support business employees in everyday tasks, such as scheduling meetings, searching for information in databases, or generating reports.