In business, the extraction of information has always been an essential activity, and it has a very high impact on the effectiveness and efficiency of activities and processes. Today's technology allows this to be done quickly, even from huge, heterogeneous, unstructured and/or disorganised information sources.
Pdfs, invoices, spreadsheets, reports, scans, notes and text files, e-mail... Finding what we need can be like looking for a needle in a haystack. It is the conversational and generative Artificial Intelligence that solves the problem, allowing you to ask direct questions and receive accurate, well-contextualised and reliable answers.

To address a need felt by more and more organisations, we have created Hyperchat, an AI agent that provides a conversational experience for users to better disseminate, search, use and share knowledge in their organisation. Using it is just like talking to an intelligent, but above all very erudite and always helpful colleague.
Hyperchat, which is part of the Hyperdoc ecosystem, is developed with the refinement of the Retrieval Augmented Generation (RAG) approach, integrating advanced information retrieval techniques with text generation (Large Language Models). Following this paradigm, Hyperchat is highly flexible and adaptable to any domain and sector - a versatile and agnostic solution with respect to business processes. In addition, this AI app provides the ability to manage documents in different languages and to 'converse' with them in your preferred language.

One tool, many possibilities

With Hyperchat you can count on different functionalities according to your needs:

• Natively multilingual;
  
  
• memory persistence: the bot understands and remembers what was discussed in the conversation, allowing for more fluid and natural communication;
  
  
• targeted and differentiated access to different information based on user roles and authorisations, with content visibility managed by an administrator;
  
  
• self-monitoring and correction system;
  
  
• free activity, without predefined routes;
  
  
• indication of the sources (documents) from which information was retrieved to generate the answers;
  
  
• organisation of content into independent thematic collections;
  
  
• selective chat storage;
  
  
• flexibility in architectural choices, such as customisation of the interface, integration of the knowledge base, etc.