Foundation product

Your archive contains decades of value. We make it accessible.

Druid Learning ingests, indexes, and labels your entire content archive — regardless of format, age, or origin. The result is a clean, structured, AI-ready dataset built entirely from your proprietary content, ready for discovery, generation, and analytics.

How it works

From unstructured archive to AI-ready dataset

A four-stage automated pipeline that handles any file format, at any scale, without manual preparation.

  1. 01

    Consolidate

    Your content lives across multiple systems — file servers, CMS platforms, DAMs, legacy archives. Druid Learning connects to all of them, pulling content into a single, unified pipeline. We handle OCR, XML, IDML, INDD, SVG, PDF, WAV, MP4, MP3, Flash, and more.

  2. 02

    Index

    Every content file is split into its component parts — text elements, images, video clips, tables, and audio segments — each assigned a unique identity. Thousands of data points are generated automatically, creating a granular, searchable index of your entire archive.

  3. 03

    Label

    Druid Learning automates metadata enrichment and data labelling across your full content library. Previously unlabelled files receive metadata automatically. Existing metadata is enhanced for richer context. Every asset receives accurate, consistent data labels.

  4. 04

    Connect

    Your structured dataset is ready to connect to the AI tools, LLMs, and third-party systems your organisation uses. Druid Learning acts as the middleware layer — integrating your proprietary data into your AI stack so you own your insights.

Use cases

Who uses archive processing

News & broadcast media

Transform decades of articles, transcripts, and footage into a structured, searchable content intelligence layer that powers editorial decisions and audience tools.

Educational publishers

Bring legacy print and digital curricula into a unified, curriculum-mapped dataset — ready for AI-powered learning tools and adaptive content systems.

Research organisations

Enrich large volumes of research papers, reports, and datasets with structured metadata — creating a knowledge base that feeds deep research pipelines and discovery tools.

Enterprise content teams

Consolidate brand collateral, R&D documentation, product information, and training materials into a single AI-ready repository.

Case study

Proven in production

Medical research · Netherlands

Dutch Cancer Institute

3,000 research papers enriched for deep research pipelines

The Dutch Cancer Institute worked with Druid Learning to process and enrich a large corpus of oncology research papers — yielding hundreds of thousands of structured data points that now feed the Institute's deep research and knowledge discovery workflows.

Read the full case study
3,000
research papers enriched
100k+
structured data points generated

Ready to unlock your archive?

Book a 30-minute demo and we'll show you how Druid Learning processes your content from day one.