Liros as a Dixa alternative
Dixa is a conversational customer service platform out of Copenhagen, built to bring every channel into one agent workspace. Liros shares the Nordic footing and the EU data posture, and takes the opposite starting point: keep the conversation away from the workspace in the first place.
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Where Liros is different
Resolution first, workspace second
The measure is how many conversations close without a person. Around eight in ten do, and the rest arrive with the order, the shipping status and the customer's details already gathered.
The Nordic logistics stack, connected
PostNord, DAO, Shipmondo, PeakWMS, Returnflows, Traede, Selveo. These are the systems a Nordic webshop actually runs on, and the answers are only as good as the data behind them.
Every language your customers write in
A question in Swedish gets a Swedish answer, one in German a German one. Selling across the Nordics from one shop does not mean staffing support in four languages.
Data stays in the EU
EU infrastructure, encrypted in transit and at rest, GDPR by design and aligned with the EU AI Act. Your data is never used to train anyone's models.
What buyers ask us
Where is our data processed?
On EU-based infrastructure, encrypted in transit and at rest, with data processing agreements in place with the vendors that require them. Our Trust Center sets out the detail.
Do we still need an agent workspace?
You need somewhere for the conversations a person has to own, and Liros gives you that: every chat and every email in one place, readable, and takeable over mid-conversation. What you probably do not need is a seat for every one of the questions Liros already closes.
We sell across the Nordics from one shop. Does that work?
That is the case it is built for. One setup, one price, and the customer is answered in the language they wrote in — with the carrier and warehouse data behind whichever market their order shipped from.
Put both tools in front of your own tickets
Thirty minutes with your own shop's questions, no slides. That is usually all it takes to tell two platforms apart.