Conversational AI: The Next Step on Document Management

Urdaten is introducing Document Understanding, a conversational AI solution designed to transform document management. This solution allows organizations to interact with their files using natural language, optimizing structured data extraction and knowledge generation from unstructured information to reduce operational costs and management times.

This development addresses the business need to free human capital from mechanical and repetitive tasks, allowing employees to focus on activities of greater strategic value. The technology aims to increase operational efficiency by enhancing, not displacing, human talent.

“Our vision is not to replace people but to give them more time to focus on what truly generates value. Today, many employees dedicate hours to mechanical tasks like searching, validating, or capturing documents. With this technology, that time can be allocated to decision making, innovation or customer service. AI should be an ally, not a replacement,” says Sergio Haro, Co-Founder, Urdaten.

Traditional document management presents a significant challenge to business productivity. McKinsey data, cited by Urdaten, shows that employees can spend between 20%–30% of their workday searching for internal documents and information. This time translates into a direct loss of efficiency and an increase in operational costs.

Furthermore, Haro says that only 11% of companies globally operate in a completely paper-free environment, which indicates a high dependence on manual or semi-digitized processes. The document lifecycle — from creation, classification, and storage to retrieval and regulatory compliance — is a complex process that requires precise organization, he adds. The inability to manage this cycle efficiently leads to risks such as outdated data, information inconsistency, and fraud exposure. In this environment, AI emerges as a tool to automate and optimize these tasks. Its application can reduce document management time by up to 60% and associated operational costs by 40%, says Haro.

Document Understanding focuses on extracting knowledge from data. Through its AI engine, the system not only digitizes and classifies documents but also allows users to make direct queries in natural language. For example, instead of searching for a contract by its file name, a user can ask, “What is the expiration date of the contract with company X?” or “Summarize the penalty clauses of this agreement.”

The solution is designed to handle common imperfections in physical documents, such as stamps or signatures that may obstruct text. If digitization is affected, the system allows the user to edit the extracted information to ensure maximum accuracy. This intelligent data extraction functionality identifies and structures key entities such as names, dates, and figures. It can even make inferences, for example, calculating totals from the concepts listed in an invoice.

To ensure its adaptability to different corporate environments, Document Understanding offers integration flexibility. Companies can use it directly on the Urdaten interface or connect it to their own infrastructure through an API, which guarantees the service's scalability, says Haro.

Although the initial use case has focused on the legal sector for analyzing contracts and files, its key applications cross multiple industries:

• Human resources: Automates onboarding and validates identity documents, proofs of address, and other key certificates.

• Finance: Optimizes Know Your Customer (KYC) processes, credit risk analysis, and audits.

• Health: Provides rapid and consolidated access to clinical histories, lab results, and patient diagnoses. According to IDC, AI can accelerate decision-making in this sector by up to 50%.

• Logistics and government: Supports mass processing of shipping guides and the management of public records and procedures.

With this launch, Urdaten aims to position conversational AI as a strategic component for operational efficiency, facilitating the transition from mere information accumulation to the generation of actionable knowledge.