Document Interpretation Automation

A path of progressive adoption of technologies based on Artificial Intelligence has been defined.

Client Situation
‍Challenge

The organization managed a high volume of destructured documents on a daily basis — such as orders, invoices, commercial, or operational requests — coming from heterogeneous sources (e-mails, portals, attachments, PDF forms, scans).
These documents, often different in format and content, were analyzed manually by operators to extract relevant information and upload it to management systems or internal flows.
This operating mode involved significant time expenditure, transcription errors, poor data traceability and an increasing difficulty in scaling processes effectively. The main need was to introduce an intelligent system capable of automating the interpretation, validation and structuring of the data contained in the documents received.

Our Approach

A path of progressive adoption of technologies based on Artificial Intelligence has been defined, with the aim of automating the cycle of acquisition, interpretation, and transformation of destructured documents into data ready for integration with business systems.

We have brought an improvement in governance, with full visibility and control over corporate document flows.

Technological implementation

The solution was designed according to a modular and scalable logic, with the following key elements:

· Automatic document capture from multiple sources (mailboxes, portals, direct upload, API...).

· Recognition and classification document types to route each file to the correct processing flow.

· Intelligent data extraction using advanced language models (LLM), possibly accompanied by OCR or RAG (Retrieval Augmented Generation) techniques to improve accuracy on complex or mixed documents.

· Assisted validation via web interface, where the operator can review, correct or approve the data before they are formalized.

· Generating structured outputs (JSON, XML, CSV, etc.) ready for integration into ERP, CRM, DMS or other business applications.

· Process orchestration through specialized AI agents, coordinated by a central system that oversees the end-to-end flow.

The design immediately provided for the possibility of adapting the models to different types of documents and future use cases, ensuring a continuous evolution of the solution.

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The project demonstrated how the combined use of AI and automation can represent an enabling factor for the digital transformation of document management in any business context.

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Significant results of the project

Thanks to this structured and integrated approach, the organization has achieved tangible benefits both in operational and strategic terms:

Automation of destructured document flows

With a drastic reduction in manual activities.

Increased operational efficiency

Thanks to the standardization of input data.

Increased data quality and reliability

With full traceability of each document processed.

Reduced loading and response times

For the benefit of both internal teams and the customers and suppliers involved.

System scalability

On multiple departments or document types, without the need for infrastructure interventions.

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