Source data for AI agents

AI agents need reliable institutional memory, not just internet data

AI agents that run locally or within a controlled organisation environment become more valuable when they can use the organisation's own memory: files, decisions, reports, correspondence, contracts, meeting minutes and historical documents.

2dA helps turn those sources into reliable digital source data: readable, verifiable, findable and suitable as a knowledge layer for retrieval, OCR/HTR, clean chunks, embeddings and future document AI.

Discuss your source dataView AI-ready data
Digitised archives and modern documents as a knowledge source for AI agents
From storage to knowledge layer

Archives become actively usable

An AI agent can retrieve relevant information, recognise context and support actions with organisation-specific knowledge.

Quality shapes results

Better source, better retrieval

Capture quality, OCR/HTR, metadata and document structure improve chunks, embeddings and findability.

Why this becomes strategic

Many AI applications still rely mainly on general models and public internet data. For companies, public institutions, archives and research organisations, the real value is often in information that is not public, not structured or still physical.

By digitising those sources carefully, an organisation builds its own knowledge layer. The AI agent no longer works only with general knowledge, but also with the history, decisions, files and context of the organisation itself.

What an AI agent can use from archives

  • search documents by content, period, person, case or subject
  • connect files, decisions and correspondence
  • recognise earlier decisions or policy lines
  • retrieve context for analysis, service requests, research or workflows
  • ground information with provenance, metadata and document boundaries

This turns the archive from passive storage into an active source for analysis, decision support and automation.

Not just scanning

An AI agent is only as strong as the sources it uses

Blurred images, missing pages, weak ordering or poor metadata create noise later. That affects OCR, HTR, chunking, embeddings and answer quality. A strong AI route therefore starts with careful digitisation.

Human expertise remains essential

Archivists, restorers and ICT specialists look at the full route

2dA combines archival knowledge, material care, scan production, metadata, software and secure delivery. We assess not only the file, but the complete path from physical document to reliable digital knowledge source.

Who this is relevant for

This route is relevant for organisations with unique information: municipalities, archives, knowledge institutions, heritage organisations, legal teams, technical companies, research teams and high-tech organisations that need reliable domain-specific data.

Internationally, this will become more important. Organisations will not only look for AI tools, but for trustworthy source data that allows AI agents to work locally, verifiably and responsibly.

What 2dA prepares

  • high-quality digital images as a basis for recognition
  • OCR and HTR where they add value
  • metadata, structure, page order and document boundaries
  • output suitable for chunks, embeddings and retrieval
  • agreements on privacy, rights, access status and governance
  • delivery towards internal systems, platforms or controlled AI environments
FAQ

AI agents and archive data

How does 2dA support RAG, vector search and embeddings?

2dA's core work is reliable digitisation, structuring and delivery of source material. Strong image quality, OCR/HTR, metadata, document boundaries and logical structure make archive data more useful for RAG, vector search, embeddings, retrieval, document AI and AI agents.

Can this run locally or in a controlled environment?

Yes. For sensitive archives, it is often essential that data can be used locally, in a shielded environment or within the organisation's own governance model. The digital preparation should support that route.

Related routes

Continue reading

AI-ready archival dataLocal AI agentsDigital source dataOCR, HTR and image qualityMetadata and accessSoftware platform

Do you want to explore whether your archive can become a knowledge layer for AI agents?

2dA helps define the digitisation quality, metadata, recognition and delivery needed to use archival data responsibly later on.

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