eCommerce
AI Solutions for eCommerce
Modern eCommerce is a personalization arms race: relevance, speed, and consistent experience across web, app, and store. Zianova builds the data and ML plumbing that turns catalog and behaviour data into measurable revenue lift.
The challenges
What eCommerce teams hit
The patterns we see across eCommerce engagements — and the work that moves the needle.
- Generic listings drag down conversion in large catalogs
- Inventory and demand forecasting are usually still spreadsheet-driven
- Every channel has its own search, recs, and content stack
- Search relevance lags behind shopper intent
How Zianova helps
Capabilities for eCommerce
Personalized recommendations
Hybrid collaborative-filtering + LLM-driven semantic similarity for hero rails, cart up-sell, and email.
Demand & inventory forecasting
Time-series + causal-lift models for stock-out reduction and smarter buying decisions.
Semantic search
Vector + keyword hybrid search with re-ranking that understands shopper phrasing, not just SKUs.
Omnichannel platforms
Unified storefront and back-office stacks that share one customer record across web, app, and POS.
Typical stack
Tools we reach for
Next.jsTypeScriptPostgreSQLElasticsearchVector DBsPython
Outcome
“Higher conversion, fewer stock-outs, and a shopper experience that feels personal at scale.”