Industry · AI support for appliances

Washing machines, ovens, dishwashers — solved at home

Guided fault isolation before a technician is dispatched. Customers identify the issue, follow a clear repair path, and book the technician with a populated ticket only when needed.

Hosted in the EU GDPR

Three problems specific to this sector

01

Cryptic error codes per brand and model

Cryptic error codes per brand and model

02

Customers wait days for a simple repair visit

Customers wait days for a simple repair visit

03

Field technicians arrive without context

Field technicians arrive without context

Typical results — first 90 days

~50%
Avoided technician visits
4.6 / 5
Customer satisfaction (CSAT)
< 5 min
Avg. resolution time

Typical workflow

01 Upload. Manuals, schedules, brand documentation — indexed in minutes with chunking tuned for the vertical.

02 Tuning. Your reviewer validates the most-asked questions and the team tunes hybrid retrieval on the first-run false positives.

03 Deploy. Web widget, mobile or voice — whichever channel your customers already use. SSO to your CRM, CSV log export.

04 Iterate. Dashboard surfaces unanswered questions. Add a manual → indexed in 4-8 minutes → live.

Frequently asked questions

How quickly can we go live for home appliances?
It depends. You can be live in minutes — upload a few PDFs and you already get meaningful value. Timelines extend only when you want to connect more of your infrastructure (CRM, ticketing, knowledge base, voice channel, SSO).
How is data isolated between customers?
Per-tenant database + per-tenant retrieval scope. No training on customer data. DPA + sub-processor list public.
Languages supported?
Eight by default — English, German, Italian, French, Spanish, Dutch, Polish, Portuguese. More on request.
Can we integrate with our CRM / ticketing system?
Yes — bi-directional webhook to Salesforce, HubSpot, Zendesk, Freshdesk, Jira Service Management, Intercom, or any HTTP endpoint.