We built a way for two people's AI context to talk to each other (without sharing their conversations)

Two developers have prototyped a federated AI context-sharing system that synthesizes relationship insights from two users' independent LLM conversation histories without exposing raw chat logs. The architecture appears to extract latent relational embeddings or summarized priors from each user's context, then merges them into a shared inference layer. No benchmark data or formal privacy guarantees are published yet, making cryptographic claims unverifiable. Therapists, couples counselors, and conflict-resolution tooling developers should watch this space, as it directly challenges the single-perspective limitation inherent in all current personal AI assistants.