LISA Core - AI Memory Library - LISA Core — semantic compression for AI conversations

Most AI tools store conversations as ambiguous text. When an AI reads a raw transcript, it guesses at meaning. LISA translates your conversation into machine-executable semantic structure: resolving ambiguity before the AI reads it. That's not compression. That's translation. And it's why LISA reconstructs context with higher accuracy than the original transcript. This insight came my 25 years as a professional translator. Meaning is fragile. Language loses it constantly. LISA preserves it.

Hi Product Hunt 👋 I'm Amar. I've spent 25 years as a professional translator — English, French, Arabic, and my whole career has been about one problem: meaning gets lost in translation. Three years ago I started using AI heavily. And I kept noticing the same thing: the AI would forget. Switch platforms, lose context, start over. The knowledge I'd built wasn't being stored — it was being approximated. Every time I loaded a new conversation, the AI was guessing at what I'd meant before. I knew exactly what was happening. It's what happens in bad translation. You preserve the words but lose the meaning. So I built LISA to fix it: not as a developer (I'm not one), but as someone who understood the problem at a philosophical level. LISA doesn't compress conversations. It translates them into machine-executable semantics. The difference sounds subtle. In practice, the AI that reads a LISA file understands your context better than one reading the original transcript. We're live today. Free tier, no card required. Try it on any AI conversation you care about. I'll be here all day, ask me anything. Especially: why this from Algeria? Why from a translator? I think those are the interesting questions. 🙏

LISA Core - AI Memory Library - LISA Core — semantic compression for AI conversations

Replies