The use case: how Qonto deploys Dust
Qonto built specialized AI agents on Dust and made the platform available across the company. One agent classifies companies by legal sector and screens for prohibited activities during onboarding, and another localizes content for its four markets.
More reported results
Figures published in Dust’s case study. They are not independently measured by usedby.
Content teams have reduced time spent on localization tasks by up to 70%.
These are just two examples out of 50 specialized AI agents used every day by over a thousand Qontoers to increase efficiency and improve accuracy.
Tolki uses a comprehensive database containing over 200 localization instructions.
In the customer’s words
We estimate that Dust AI agents can remove at least 50,000 hours of work per year, and perhaps a lot more. Some use cases pay off in a matter of hours!Other AI tools used by Qonto
Other public relationships recorded on usedby.
Explore Qonto’s AI stack
Dust users in Fintech & Payments
Companies in the same sector, with public evidence.
See all Dust customers
Go straight to the source
Based on Dust’s published case study. We check the public evidence; the results are reported by the vendor.
dust.tt- Source published
- Sep 19, 2024
- Last checked
- Oct 24, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 50,000 hoursChecked
Printed word for word on the page, near the name of Qonto.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Qonto.
- The publication dateChecked
Read from the page’s own metadata, never guessed.
- Qonto uses DustChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
We estimate that Dust AI agents can remove at least 50,000 hours of work per year, and perhaps a lot more. Some use cases pay off in a matter of hours!