dvcrn Connect
Memory-driven human connections. Match people through deep emotional understanding, not surface-level interests or algorithmic feeds.
How it works
Connect analyzes memory graphs to find resonance between people — shared experiences, emotional patterns, and latent interests that surface-level profiles miss entirely.
Core capabilities
- Emotional resonance matching — vector similarity across memory embeddings, weighted by emotional depth rather than keyword overlap
- Cross-user memory bridging — find connections between two people's memory graphs that neither person would discover on their own
- Privacy-first architecture — users control exactly which memories are matchable; nothing is shared without explicit consent
- Aha moment delivery — the moment a stranger truly understands you through your memories, not your bio
Architecture
Built on Echo's three-layer memory system:
- Identity layer (compressed profile)
- Working memory (dynamic, context-aware)
- Long-term storage (Supabase + vector search)
Matching runs against Layer 3 with results surfaced through Layer 2 into conversation context.
Part of the Echo ecosystem
Connect is one component of Echo Chat by Iditor — building memory as social identity infrastructure.
Status
Early development. Core matching algorithm validated with beta users (K-Factor 2, D7 retention 42%).