Hey HN,

  I'm shipping my first open-source project and I'm pretty nervous about it.

Aethene is an AI memory API – it gives your AI apps persistent memory. Store conversations, extract facts automatically, search semantically, handle contradictions gracefully. It works well thank most of the memory projects available on the market currently.

Why I built this: I was building AI agents and kept running into the same problem – they forget everything. Every conversation starts from zero. I wanted something that could: - Auto-extract facts from conversations (not just store raw text) - Handle "user moved from SF to NYC" without keeping both as true - Search by meaning, not just keywords - Version everything (who said what, when)

  Tech stack:
  - TypeScript + Hono (fast, edge-ready)
  - Convex (real-time DB + vector search)
  - Gemini (embeddings + extraction)

  What it does:
  # Store memory
  curl -X POST /v1/content -d '{"content": "User loves hiking, lives in SF"}'

  # Recall naturally
  curl -X POST /v1/recall -d '{"query": "outdoor hobbies"}'
  # Returns: "User loves hiking" with assembled context

  It handles the boring stuff – chunking, embeddings, deduplication, contradiction detection, versioning – so you can focus on your actual product.

  Links:
  - GitHub: https://github.com/akhilponnada/aethene
  - API Docs: OpenAPI spec in repo

This is my first time launching anything publicly. Would love feedback – what's missing? What would make you actually use this? Roast my code if you want, I can take it.

Thanks for reading.