Transitioning from ECM to intelligent information management
Modern businesses are gradually moving away from traditional enterprise content management (ECM) systems in favor of intelligent information management (IIM). Traditional document repositories are proving inefficient for handling large volumes of unstructured data. According to the international standard ISO 15489-1:2016, documents should be treated as active data containers that automatically integrate into business processes using artificial intelligence and intelligent document processing (IDP) technologies.
IDP technology and its use cases
IDP technology automates document classification and metadata extraction without manual data entry. Key use cases include:
- automatic extraction of mandatory fields to populate ERP systems;
- intelligent routing of incoming correspondence;
- automatic verification of qualified electronic signatures (QES).
According to the Law of Ukraine "On Electronic Documents and Electronic Document Flow," electronic documents hold legal validity only when they contain mandatory fields. Therefore, modern IDP systems must integrate with government services to verify QES.
Hybrid model and process maturity scale
Complete AI autonomy is currently out of reach. Mature systems operate on a hybrid model (human-in-the-loop): AI processes standard documents, and in cases of a low confidence score, the system triggers fallback rules and routes the document to a human for verification.
Experts identify four levels of document processing maturity:
- Manual — entirely manual entry and classification.
- Template-based — using rigid OCR rules.
- Hybrid — a combination of AI extraction and human verification.
- Intelligent — end-to-end automation from recognition to smart contract execution.
Ukrainian technology solutions for automation
The low-code platform UnityBase serves as the foundation for building enterprise solutions. Several domestic products have been developed on its basis:
- Megapolis.DocNet — a document management system supporting up to 60,000 users that utilizes LLM models to automate classification.
- Scriptum — a solution featuring its own AI center for smart search and an archive exceeding 130 TB.
- Nectain Platform — a tool for automating mail processing and evaluating the performance quality of artificial intelligence algorithms.
What it means for companies
The shift to intelligent information management and IDP technologies allows enterprises to handle massive volumes of unstructured data efficiently while maintaining legal compliance. Integrating AI-driven verification of qualified electronic signatures (QES) ensures that digital workflows remain legally valid under Ukrainian law, while hybrid processing models reduce operational risks by keeping humans in the loop for low-confidence tasks.
What to do next
To successfully transition to intelligent document management, organizations should take the following practical steps:
- Assess your current document processing maturity level, aiming to move from manual or template-based systems toward hybrid and intelligent automation.
- Implement hybrid (human-in-the-loop) verification workflows to handle low-confidence AI extractions safely.
- Deploy domestic low-code solutions built on platforms like UnityBase (such as Megapolis.DocNet, Scriptum, or Nectain Platform) to automate classification, smart search, and mail processing.
Prepared by a Software Ukraine member. Original publication.