ESOMAR

ESOMAR: Transforming 70 years of knowledge into an intelligent, searchable archive

ESOMAR’s archive contained over 10,000 documents spanning 70 years. Papers, webinars, videos, books, reports, and guidelines. To stay ahead of the competition in , they needed to digitise their entire repository and dramatically improve the speed and accuracy of search results for their members.

Wes can tell you more in person,

What we did for ESOMAR

We digitised over 10,000 papers, talks, videos, and audio files, then engaged IBM Watson’s machine learning algorithms to find patterns, understand concepts, and build a knowledge base within a custom search engine. The system could read and understand the content, tag articles, and search through full text, titles, and metadata for instant, relevant results. The AI also learned to make recommendations and was made scalable with a simple drag-and-drop upload system for new documents and files.

The new AI-powered system revolutionised how ESOMAR’s members access knowledge. By leveraging machine learning and digitisation, the platform delivers faster, more accurate search results and continuously improves with every user interaction. Here are the key outcomes:

10,000+ documents digitised and searchable

70 years of knowledge instantly accessible

AI-powered recommendations for users

Drag-and-drop upload for new content

Continuous learning improves search accuracy

Immediate online access to all media types

The AI system goes beyond keyword matching, learning from every search query and interaction to deliver ever-improving results. Members now have immediate access to tens of thousands of resources, and ESOMAR can curate and expand their collection more efficiently, helping retain current users and attract new ones.

“This project demonstrates the power of AI to unlock decades of knowledge and make it accessible to everyone.” –

Wes Botman
Chief Executive Officer

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