Use Case Overview
Generic recommendation systems miss nuance and rely on third-party data. We develop AI models trained on your first-party signals—purchase history, browsing paths, support chats—to generate relevant, dynamic product suggestions for each user.
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Features
Serve the right offer at the right time, without depending on third-party cookies.
Behavior-based personalization
Analyze browsing, clicks, carts, and more to shape recommendations.
First-party data integration
Use only your owned data—no third-party tracking needed.
Dynamic models (real-time or batch)
Serve up-to-date suggestions based on the latest user activity.
Testing-ready output
Plug into your site or app and run experiments easily.
Value for Marketing + Product Teams
Personalization with real impact, built on data you own.
Higher conversion rates
Show relevant products that reflect actual user behavior.
Better engagement and session length
Keep users exploring with smarter suggestions.

Value for the Company
Stronger margins, less dependency on ads or external data.
Increased customer lifetime value
Personalization encourages repeat purchases and brand loyalty.
Compliance-friendly growth
Build advanced targeting without relying on third-party cookies or trackers.