Solutions / Retail and e-commerce
A Swiss catalogue speaks German, French, Italian and often English, sometimes in the same search box.
These scenarios are illustrations. None of them describes a client.
E-commerce
What we would build
A content pipeline that turns supplier data into product pages in German, French, Italian and English, following your tone guide and glossary. Editors review each batch side by side with the source data before publishing.
Mistral, Akeneo API, Python
Digital
What we would build
A hybrid search that combines keyword matching with multilingual semantic search over the catalogue, so a query finds the right products whatever the language or wording. It runs next to the current engine and is tuned on real search logs.
OpenSearch, BGE-M3, Python
Supply chain
What we would build
Daily demand forecasts per store and product that account for cantonal holidays, weather, promotions and local events. Planners get suggested order quantities with the main drivers listed, and the models retrain on a weekly schedule, with accuracy tracked per store.
LightGBM, dbt, Airflow, MLflow
Customer service
What we would build
A service agent that reads each ticket, looks up the order and the return policy, and drafts the reply in the customer's language. Routine answers go out after a quick check; refunds and exceptions wait for a person, with the case already summarised.
LangGraph, Zendesk API, FAISS
Logistics
What we would build
A grading station that photographs returned items, detects damage and missing parts, and proposes a route: resell, refurbish or recycle. Warehouse staff confirm the route with one scan, and disputed items go to a supervisor.
PyTorch, ONNX Runtime
Swiss retail runs on small, demanding markets: four languages, cantonal holidays, high service expectations and margins that leave little room for stock mistakes. Each scenario below connects to systems you already run, such as your PIM, shop platform and warehouse management system, and leaves the final call with your team.
Product data, search and service have to work in German, French, Italian and English, including Swiss terms that generic models miss.
Cantonal holidays, school breaks and cross-border shopping shift demand by region, so forecasts work at store level.
Shops already run on a PIM, an ERP and a helpdesk. New tools connect to them through their APIs.
Order and contact data fall under the nFADP, so service tools read them through the systems that already hold them.
Yes. We work from your supplier data, your glossary and examples of copy you like, with Swiss spelling such as ss for ß. An editor approves each batch before it goes live.
Not necessarily. It often runs alongside the existing engine, which keeps handling exact matches while the semantic layer handles intent and synonyms.
Two years of sales per store and product is a comfortable start. With less, we lean more on similar products and on known events.
Only if you want it to, and only with a person approving. In the scenario on this page the agent prepares the action and a person confirms it.
Yes. A smaller shop can start with product content or service replies, which need little integration. Our page for SMEs, linked below, describes how a project runs at that size.
We start with a feasibility study on your own data, so you see results before anything is promised.