Artificial intelligence is reshaping modern corporate archive management

Discover how artificial intelligence and modern low-code platforms help businesses automate the classification, search, and secure storage of corporate archives.

Annual corporate data growth of 25-30% poses significant challenges for traditional storage systems. Modern digital archives require more than just document preservation; they need intelligent processing, fast content-based search, automatic classification, and compliance with security standards such as ISO/IEC 27001 or HIPAA.

The role of artificial intelligence in archiving

Artificial intelligence automates routine processes and structures large datasets using the following technologies:

  • Automated classification and categorization based on document content analysis.
  • Semantic search that understands query context rather than just exact word matches.
  • Intelligent Document Processing (IDP) to automatically extract key data from unstructured files.

Technological solutions for digitalization

To address these challenges, developers from the Intecracy Group consortium offer comprehensive tools. Built on the UnityBase low-code platform, the Scriptum.Repository system ensures long-term document storage and indexing. InBase is also developing the Megapolis.DocNet and Scriptum.DMS systems with built-in AI capabilities.

These capabilities are complemented by Nectain's SaaS platform for intelligent document processing. System integrator Softline ensures solution deployment, integration with ERP systems, and compliance with state security standards (KSZI) for the public sector, while Data Management IG manages data within enterprise environments.

What it means for companies

The transition to AI-driven archiving allows businesses to successfully manage the 25-30% annual data growth without operational bottlenecks. Implementing these technologies ensures compliance with international security standards (ISO/IEC 27001, HIPAA) and significantly reduces document processing times through automated classification and semantic search.

Practical steps

  • Evaluate your current archive infrastructure to determine if it can handle rapid data growth.
  • Deploy modern DMS/RMS solutions with built-in AI, such as Scriptum.Repository, Megapolis.DocNet, or Nectain's SaaS platform.
  • Collaborate with integrators like Softline to integrate archiving systems with existing ERPs and guarantee compliance with security standards like KSZI.

Prepared by a Software Ukraine member. Original publication.

Sources & materials

Materials and sources used in this article.

  1. Original publication — intecracy.com