Personalisation that feels uncanny.
Power product, content and feed recommendations with real-time vector similarity. Endee serves personalised picks at every page view without breaking your latency budget.
Capabilities
Every pattern of personalization, one index
Content-Based Filtering
Encode item attributes as vectors and find semantically similar items in real time. "More like this" for products, articles, videos, and music, without requiring user history. Works from day one of launch.
Collaborative Filtering
Encode user behavior sequences as vectors using Item2Vec or similar models. Find the nearest-neighbor user vectors and recommend items those users interacted with. Personalization that improves with every action.
Cold-Start Handling
New users and new items get recommendations immediately via content-based similarity, no interaction history required. As interactions accumulate, the system smoothly transitions to collaborative signals.
Sub-5ms Response
Every millisecond of recommendation latency is a lost engagement. Endee serves the nearest-neighbor item and user vectors in under 5ms, inline with page load, not as a deferred async fetch.
Filtered Recommendations
Constrain recommendations to in-stock items, region-specific catalogs, or content the user hasn't seen. Filters run inside the ANN search, no post-retrieval filtering that degrades precision.
Cross-sell & Upsell
Encode cart contents and compare against complementary product vectors. Surface "frequently bought together" and upgrade suggestions in real time, not from pre-computed tables that lag behind catalog changes.
Real-time
From user action to new recommendations in <5ms
Use Cases
Who builds recommendation systems on Endee
E-commerce
Product recommendations on PDPs, "complete the look," and dynamic homepage carousels.
Streaming & Media
Content recommendations based on viewing history and real-time behavioral signals.
News & Publishing
Related articles and personalized feeds that adapt to reader interests without cookies.
B2B SaaS
Feature discovery and workflow suggestions based on how similar users navigate the product.