The use case: how Tediber deploys Yuma
Tediber, a French direct-to-consumer bed and mattress brand, uses a Yuma AI agent connected to Shopify and Gorgias to handle incoming customer support queries such as returns, shipping status, exchanges and invoice requests. Tickets needing human judgment or involving dissatisfied customers are escalated to human agents.
More reported results
Figures published in Yuma’s case study. They are not independently measured by usedby.
Four months after implementation, Yuma is involved in 64% of all incoming customer queries.
In a recent week, they saved roughly €900 in outsourced email costs for that week alone.
After implementation, that number dropped by 33%.
In the customer’s words
A few months ago the first answer from a human took 72 hours. Now, for a large portion of tickets, the answer is within an hour.Yuma users in E-commerce & D2C
Companies in the same sector, with public evidence.
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Go straight to the source
Based on Yuma’s published case study. We check the public evidence; the results are reported by the vendor.
yuma.ai- Source published
- Apr 7, 2026
- Last checked
- Nov 12, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 72h → <1hChecked
Printed word for word on the page, near the name of Tediber.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Tediber.
- The publication dateChecked
Read from the page’s own metadata, never guessed.
- Tediber uses YumaChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Before Yuma, customers had to wait up to three days (72 hours) for an initial reply. That delay triggered a cycle of follow-up emails and phone calls, which created duplicate tickets and added even more pressure to the backlog.