Artificial Intelligence can transform the information assets of a company into a strategic resource.

The use of algorithms allows us to know what already exists within the company, understand the relationships between information and documents, but also make predictions about future scenarios.

These technologies can extract and interpret data even from all those documents that were not originally conceived to be managed and analyzed by software, for example a receipt.

In all those companies that have to manage a large amount of information, Artificial Intelligence would make work process and document management more agile and efficient, allowing a document to be automatically classified and its content to be returned dynamically.

Imagine having a mountain of emails, invoices, contracts and other documents. Manually sorting them would be time-consuming and prone to human error.

AI document classification templates are sophisticated tools that use machine learning algorithms to automatically analyze and categorize large volumes of documents.

AI templates are able to:

• Analyze content: they examine the text, keywords, and the context of each document to identify its main theme.
• Classify the document: they learn to recognize patterns and characteristics common to similar documents, such as structure, format and the language used.
• Profiling: based on the analysis, they assign one or more default labels to each document (e.g. “invoice”, “contract”, “curriculum vitae”).

The semantic search feature of ARXivar allows you to understand the meaning of a query formulated in natural language, returning results relevant to the user’s search intent.

This technology allows the system to automatically gather relevant information by extracting it from documents stored in ARXivar, ordering them based on their degree of reliability and relevance to the request.

Unlike traditional full-text searches, which are limited to identifying the occurrence of one or more keywords in documents, semantic searches are able to interpret the context and meaning of a query even when generic or inaccurate terms are used.

The new Semantic Search Chatbot allows users to interact with the platform using natural language, following the flow of a real conversation.

The system understands the intent behind each request and delivers relevant results by retrieving information directly from the documents stored in ARXivar. The semantic index automatically updates whenever a document is modified, ensuring responses are always accurate and up to date.

By combining semantic indexing with generative AI, the chatbot can reprocess retrieved information and deliver clear, comprehensive, and context-aware answers based on a Retrieval-Augmented Generation (RAG) approach.

Finding the right information within complex, data-rich documents can be time-consuming and frustrating.

The Document Chatbot changes the game. By combining generative AI with intelligent AI Agents, the system analyzes documents, answers specific questions, and performs advanced actions such as comparing different versions of the same document, generating summaries, or creating new content from available templates.

Users simply start a conversation with the chatbot to access the most relevant data and interact with ARXivar’s archived content in a smarter and more efficient way. Custom commands can also be configured to automate recurring tasks, while fully complying with the platform’s security and confidentiality policies.

SAVE TIME

Automate manual document classification, freeing up valuable time for more important tasks

INCREASING EFFICIENCY

Improve organization and document work flow, making information easier to access

ERROR REDUCTION

Reduce and remove human errors in manual classification, ensuring greater accuracy