Updated · By Otabek Olimjonov
The steps
- Inventory: what exists, in what condition, and what may be published.
- Scanning and digitizing at a quality that will still be useful in twenty years.
- Metadata: dates, places, people and events, entered once and kept consistent.
- AI image recognition to tag objects, places and scenes across thousands of items, checked by archivists.
- Publishing: a searchable collection or a digital museum for the public.
Where AI helps most
- Tagging tens of thousands of images that people could never label by hand.
- Finding similar photographs and grouping them by place or event.
- Suggesting descriptions that an archivist confirms or corrects.
A real case: the digital water museum
- For the Ministry of Water Resources, Eurosoft worked on digitising a 120-year archive of 32,000 photographs and 7,200 videos and used AI image recognition to build a digital museum of Uzbekistan's water history (2021), with VR and AR elements.
Questions and answers
- Can AI describe old black-and-white photos correctly?
- It is good at objects and scenes, and much weaker at exact people, dates and places. That is why an archivist confirms its suggestions.
- Should archive data stay on our own servers?
- Often yes, especially for unpublished material. Image recognition models can run on the organisation's own servers.
- Who digitizes archives with AI in Uzbekistan?
- Eurosoft in Tashkent worked on the digital AI water museum for the Ministry of Water Resources: a 120-year archive of 32,000 photographs and 7,200 videos.
Related services
See also: industries/water-agriculture · services/ai-assistants-and-private-ai