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Intelligent document analysis powered by LLMs
A new approach to document processing
In every organization, documents form the foundation of operational processes. Invoices, contracts, reports, technical documentation, and tender materials contain key information necessary for making business decisions.
In practice, this data is most often stored in an unstructured format and requires manual analysis. This process is time-consuming, costly, and difficult to scale. It engages operational teams, increases the risk of errors, and leads to inconsistencies in data. As document volumes grow, both processing time and the overall complexity of the process increase.
DocMiner transforms this way of working. The solution automates document analysis and converts their content into structured data that can be directly used in business systems, reporting, and further process automation.
Documents as a source of business value
DocMiner is a solution for intelligent document processing that enables the extraction of dispersed data from documents containing text layers as well as from scans or image-based files (without OCR).
It then converts this information into a structured, transparent format ready for further use.
The solution is designed for organizations that require control, security, and flexibility. DocMiner provides:
As a result, DocMiner reduces the time spent on manual document analysis while maintaining the operational standards of the organization.
How it’s used in practice
DocMiner can be applied anywhere documents are an integral part of business processes.
In every case, the goal is to move from manual interpretation of content to automated, repeatable data processing.
Scope of supported documents
DocMiner is designed to process key document types used in business processes, such as:
The solution helps reduce the time spent on manual document analysis and automatically recognize and classify data such as dates, client names, or key financial indicators.
Core features
DocMiner supports comprehensive document processing – from analyzing their content and structure to integrating extracted data with organizational systems.
Functional capabilities include:
DocMiner automates the transformation of documents into structured formats, enabling their further use in data analysis, process automation, and the implementation of AI-driven solutions.
From document to ready-to-use data
DocMiner performs a multi-stage document processing workflow that includes content preparation, structural analysis, data interpretation, and integration with organizational systems.
Each stage is designed to ensure repeatability, quality control, and scalability:
The system accepts documents in various formats – PDF files, scans, and text documents. Regardless of their quality or structure, the document is prepared for further analysis in a way that enables full digital processing.
For graphical documents, text recognition mechanisms (OCR) are activated. A digital representation of the document is then created, including its layout, section structure, and the placement of elements such as headers or tables.
DocMiner identifies the logical structure of the document and analyzes its content within the context of a specific document type. Important sections, fields, numerical values, and relationships between data are recognized.
Key information is extracted and assigned to appropriate categories, such as dates, document numbers, contractor details, or financial values. The process takes into account context and dependencies between individual elements.
Extracted data is transformed into an organized structure, e.g., JSON format, and validated to ensure consistency, completeness, and correctness.
The final result can be stored in databases or transferred to ERP systems, CRM platforms, data warehouses, or analytical tools where the data is further used in reporting and process automation.
As a result, the document ceases to be a closed file and becomes a source of data that can be filtered, compared, and aggregated across the entire organization.
Key benefits
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DocMiner translates document analysis into measurable operational and business outcomes. By automating data processing, the solution increases process efficiency and improves the predictability of organizational operations.
Automated data extraction and processing reduces the risk of errors resulting from manual transcription. Standardization of processes increases data consistency and reduces the cost of corrections, complaints, and document re-verification.
Automatic data extraction and processing reduces the risk of errors resulting from manual data entry. Process standardization increases data consistency and reduces the costs associated with corrections, claims, and repeated document verification.
Instead of manually reviewing files, teams receive ready-to-use structured data. Document processing time can be reduced by several dozen percent, directly improving operational efficiency.
In document-driven processes, consistency of interpretation is crucial. DocMiner introduces unified data processing standards, eliminating discrepancies and increasing operational stability.
Access to up-to-date, structured information enables informed decisions based on complete and consistent data rather than scattered documents. Organized information significantly increases transparency and control over processes.
As the number of documents grows, the process remains stable and repeatable. Organizations can scale operations without the need to proportionally increase the number of employees involved in document analysis.
Technology adapted to organizational needs
DocMiner was designed for organizations that process sensitive data or operate in environments requiring strict security and regulatory compliance.
The architecture of the solution allows the document processing approach to be adapted to existing security policies and compliance standards.
The system can be integrated with existing IT infrastructure and expanded as the scale of processes grows. This approach enables organizations to start implementation in a single business area and gradually extend the solution to other parts of the organization.
DocMiner is prepared for stable use in production environments – with a strong emphasis on control, predictability, and long-term scalability.
A flexible deployment approach
The implementation of DocMiner can begin with a selected area – for example invoice analysis or tender documentation – and then gradually expand to additional processes within the organization.
This approach enables organizations to build value step by step and measure business outcomes at each stage. As a result, the scope of the solution can grow in a controlled manner and align with organizational priorities.
If documents are a key component of your organization’s processes, organizing the data contained within them may be a natural first step toward further automation.
“3Soft delivered a comprehensive implementation for us – from data analysis and standardization, through the development of a content extraction module and transformation logic, to the design of a modern architecture […] without engaging our internal IT resources.
The entire process – from invoice ingestion, through extraction and transformation of data using Machine Learning solutions, to final storage – was fully automated. This significantly shortened operational processing time and eliminated human errors.”
IT Project Manager at HAMMERmed Medical Polska
Frequently Asked Questions about DocMiner
No. DocMiner analyzes both documents containing a text layer and scans or PDF files stored as images. For graphical documents, OCR (Optical Character Recognition) mechanisms are used, enabling full analysis of both document content and structure.
Yes. DocMiner can be configured for specific processes such as invoice analysis, tender evaluation, contract processing, or HR documentation. The solution allows customization of data extraction methods, document classification, and the structure of output results to match the organization’s requirements.
DocMiner generates data in a structured format, such as JSON, enabling integration with ERP systems, CRM platforms, data warehouses, and reporting tools.
The data can be automatically transferred to the existing IT infrastructure and used for further analysis or process automation.
The solution was designed with data security and regulatory compliance in mind. The architecture allows the document processing model to be adapted to the security policies already in place within the organization.
Implementation can start with a pilot or a single selected process, such as invoice analysis or tender documentation processing. After confirming the business value, the solution can gradually be expanded to additional areas of the organization.
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