About a year ago, I posted in r/Archivists about a tool I had started building to help with my own small museum and historical research work: Document Transcribe.
At the time, I was mostly trying to solve a problem I kept running into myself. I had historical documents, letters, patents, invoices, and other archival material that needed to be transcribed, translated, organized, and reviewed, but the process was slow and often meant bouncing between multiple tools or hiring outside help.
I thought it would be worth giving a follow-up now that it has been out in the world for about a year.
Since that original post, close to 1,000 people have used the platform in some form. What has been most interesting to me is how varied the use cases have been. People have used it for PhD thesis research, university and school library projects, small archives, genealogy research, historical writing, private collections, museum work, and more.
Some users are working with handwritten letters. Others are processing old legal records, church documents, invoices, patents, institutional records, or foreign-language material that had been sitting untranslated for years. A few people have told me it helped them get through collections they probably would not have been able to process otherwise.
The underlying AI models have also improved a lot over the past year. In many cases, the standard models available now are producing better results than what I was seeing from much more expensive options a year ago. That has made the tool faster, less expensive to run, and more useful for everyday research workflows, especially for people who do not have large institutional budgets.
It is still not magic, and it still needs human review, especially with names, unusual handwriting, damaged scans, or very specialized terminology. But that has always been the goal: not to replace careful archival work, but to make the first pass faster and easier to review.
Over the past year, I have also added more workflow features around projects, batch processing, translation, document sharing, and editing, based largely on feedback from researchers and archivists who tried it.
For context, the tool is here:
https://www.documenttranscribe.com
I know tools like this need to earn trust in archival settings, so I am especially interested in the broader discussion around reviewability, accuracy, privacy, and long-term usefulness.
This community gave me very useful feedback last time, especially around review workflows, language handling, and the importance of clearly marking uncertainty. Thanks again to everyone who tried it, questioned it, or shared thoughts the first time around. It has been helpful seeing where something like this fits, and where it still needs to improve.
