Social Networking

Personalize Feeds Without Invading Privacy

PULSE infers user interests from behavioral signals in real-time, no tracking pixels, no cookie walls, no PII collection. Deliver relevant feeds, content discovery, and ad matching that users trust.

+40% session timeaverage improvement

Problems We Solve

Users leaving due to irrelevant feed content

Cold start for new users with empty interaction history

Privacy regulations limiting traditional personalization

Declining ad relevance as cookies phase out

See It In Action

Feed Curation

The Late-Night Tech Scroller

A friend at a party notices you're in tech, talking about AI and startups. They don't recommend reality TV; they say 'Have you seen this deep-dive on transformer architectures?' They read the room.

Signals Detected

├──Time:11:30 PM (late-night session)
├──Device:MacBook Pro (developer)
├──Engagement:Reads full articles, not just headlines
├──Pattern:Skips viral/entertainment content
Persona Detected92% confidence

Deep-Dive Tech Reader

Result

Feed prioritizes long-form tech content and analysis over viral clips and memes.

+40% sessionConversion Lift

How PULSE Works for Social Networking

Step 1

Observe

Capture non-invasive behavioral signals from your platform, device, referrer, time, geo, and engagement patterns.

Step 2

Infer

Build a real-time persona using Bayesian inference. Understand intent, preferences, and context in milliseconds.

Step 3

Deliver

Match the inferred persona to your content via vector space. Serve personalized responses via API in <50ms.

Integration

Feed Ranking API and Content Discovery SDK. RESTful endpoints for real-time feed re-ranking and content scoring.

Drop-in SDK
RESTful API
Webhook events
OpenAPI spec

Ready to Personalize Your Social Networking Experience?

Get a free audit tailored to your industry. We'll show you exactly what PULSE can do with your data.