The next level of enterprise AI: agents on the DocuART platform

Enterprise efficiency is increasingly limited not by a lack of information, but by how accessible that information is and by the volume of repetitive tasks still performed manually. Employees often have to search across documents, databases, and various business systems to find the information they need, then manually continue the processes that depend on it.

DocuART offers a new approach to this challenge. As a closed enterprise AI agent platform, it not only makes an organization’s internal knowledge accessible, but also enables companies to operate digital workers that gather information, process data, and carry out tasks in connected enterprise systems.

Enterprise AI agent platform: much more than a chatbot

Almost every company has a significant amount of documentation, internal policies, and process descriptions. These materials can span dozens or even hundreds of pages, making it extremely time-consuming to locate a specific piece of information. This can be particularly challenging when onboarding new employees or in areas where accurate answers about internal policies are needed quickly.

One of the original goals behind DocuART was therefore to create an enterprise AI assistant capable of providing relevant, source-referenced answers based on an organization’s own documents. Today, however, the platform’s capabilities go far beyond searching for information in documents. DocuART transforms enterprise information, whether stored in PDF and Word documents, databases, or ERP systems, into knowledge that AI can use. This knowledge also serves as the foundation for agents that do more than answer questions: they can perform specific business tasks, reducing the burden of repetitive and manual work on employees.

When AI does more than answer questions

A traditional enterprise AI solution primarily searches for information, summarizes content, or answers questions. An AI agent, by contrast, can carry out multiple consecutive steps in pursuit of a defined objective.

A DocuART AI agent can, for example, retrieve the information required for a task from the enterprise knowledge base, query data from a business system, process that data, and then initiate further actions based on the results. This means the same digital worker can participate in multiple stages of an end-to-end task. Agents can be fully configured to match the company’s own data sources, systems, and permission structures.

The platform evolved from enterprise requirements

The foundations of DocuART were developed together with a major Hungarian insurance company, based on real business needs and strict industry requirements. One of the main challenges was that a significant amount of organizational knowledge was available only in lengthy documents or in employees’ experience, while day-to-day operations required fast and accurate access to information.

In the first phase of development, we therefore created an interface focused on processing documents and retrieving the information they contain. The system can manage, index, and interpret document collections in a unified way, significantly reducing the time spent on manual information searches.

In the next development phase, we extended the system to handle confidential corporate documents, internal instructions, and process descriptions. This phase also included integration with Microsoft Azure cloud services. These capabilities now form the enterprise knowledge layer of DocuART, which can also be used by the agents operating on the platform.

In the third development phase, the focus shifted to agent functionality. DocuART was extended so that it could independently organize and execute the actions required to achieve a defined business objective, while also supporting operational tasks through connections to the enterprise infrastructure. Agent behavior can be configured to match the organization’s workflows and permission system, making the platform suitable for use in areas such as administration and IT operations.

From databases to enterprise systems

The next stage in the platform’s development involved integrating structured enterprise data. This included semantic annotation of database schema elements, mapping relationships between them, and establishing flexible data source integration.

DocuART also supports querying information stored in databases through a natural-language interface. Document-based knowledge and structured enterprise data can therefore be used together, providing agents with more detailed and up-to-date information. This becomes particularly important when AI is expected not only to provide an answer, but also to carry out a business task.

From administration to sales

DocuART can also be connected to custom enterprise systems, including CRM and ERP environments. This allows an agent to collect data from multiple sources, combine it with information from the enterprise knowledge base, and perform a defined task based on the resulting context.

In a sales process, for example, an agent could collect customer-related data, retrieve the necessary product and pricing information from the ERP system, prepare a quotation, and then initiate further actions according to the defined workflow.

Similar workflows can be implemented in finance, HR, administration, or IT operations. The goal is for AI not to remain a standalone tool within the company, but to become part of recurring business activities through integration with existing enterprise systems.

Enterprise knowledge gives agents context

A common challenge for companies is that information is distributed across multiple systems and stored in different formats. A policy may be found in a document, customer data in a CRM system, and product information in an ERP platform.

DocuART’s proprietary technology goes beyond simple information retrieval by interpreting enterprise knowledge in context. Its graph database-based approach enables the system to identify relationships between people, processes, events, and policies.

A platform product with implementation tailored to the enterprise

DocuART is not introduced as an off-the-shelf product. Instead, each implementation is delivered as a project tailored to the specific operation of the organization. The solution is adapted to the client’s business objectives and processes, rather than requiring the organization to adapt to the software.

Implementation is preceded by a detailed assessment of the business and its processes, ensuring that the system is optimized for the organization’s specific requirements and the input formats it uses, such as PDF and DOCX files. The graph-based architecture enables the platform to maintain stable and fast response times as the number of users or the volume of managed documents grows, supporting long-term scalability.