A privacy first companion AI
On-device AI companion avoiding Replika's privacy risks by keeping chat data local.

Local inference for AI companions when Replika stores everything on their servers.
Privacy-conscious users seeking AI companions
Off Grid · Replika · Character.AI
The only thing I think actually solves this is local inference. I remember browing r/LocalLLaMA and years ago and thinking this is the future. Local models are finally good enough. I was playing with the bonsai 8B 1-bit quant model a few weeks back and I think we're almost there. I built friendAI to see if there's market demand for local inference. Everything runs on your phone.
What's actually on-device:
- Bonsai-8B (1-bit quantized Qwen3-8B, ~1.3GB) via MLX for speed - Gemma 4 E2B (~4.5GB, GGUF) via llama.cpp for vision - A unified client that routes between them
A few things I'm reasonably proud of solving in about a week:
- Turns out the hardest part was actually managing the background model downloads that survive crashes, network drops and reboots. You can start chatting before the download finishes. - Runtime thread auto-tuning that benchmarks your actual device at startup rather than guessing with a static heuristic - Local memory without a vector DB. TF-IDF style ranking with recency decay. No embedding model needed.
Happy to go deep on any of it. www.friendai.pro
On-device AI companion avoiding Replika's privacy risks by keeping chat data local.
Useful research but it's a static report, not an interactive tool.
Signal + Wire already offer disappearing E2E messages; code-based rooms add friction, not security.
iOS AI companion with proactive check-ins in a saturated market.
Directory of AI privacy policies with compliance scores, competing with ToS;DR.
TypeScript-defined privacy policies that auto-generate GDPR-compliant text and track consent.