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Memory
Context limits run out. Threads sprawl. "Paste the previous conversation" doesn't scale. Lippa's carry-forward engine extracts what matters from every turn, and hands it to whichever model you use next.
01 · capture
Every turn, observed
Work with any model inside Lippa, no special prompts, no rituals. The pipeline watches the conversation itself, whichever vendor is answering.
02 · extract
Structure, not transcripts
Facts, decisions and open questions are distilled into a canonical memory, separate from raw logs, deduplicated, and scoped to the project it belongs to.
03 · continue
Any model, mid-sentence
Each project keeps one live context pack, a ranked, budgeted selection of what matters, regenerated within minutes of any memory write. Every model gets the same pack.
Memory in Lippa is not a black box. The Memory Explorer shows every item, where it came from, what it says, and which scope it lives in.
memory explorer · project: Q3 launch
decision · pinned
Launch pricing is €25 Pro / €55 Pro Max.
fact · confirmed
The audience is SMB owners, not enterprise.
open question
Do we localise the onboarding for launch?
ChatGPT · 214 conversations
imported → 96 memory items
Claude · 158 conversations
importing…
Gemini · 61 conversations
queued
The browser extension imports your existing conversations from ChatGPT, Claude and Gemini, so Lippa's memory starts rich, not empty. Months of context, available to every model, on day one.
About the browser extension →Every long conversation eventually hits a model's context limit. In Lippa that's one click: continue. A fresh chat opens with your project memory and the thread's essentials already in place, the model picks up mid-sentence.
No re-pasting transcripts, no mass-dumping documents to get a new chat up to speed. The memory layer already did that work.
Q3 launch planning
context 98% fullQ3 launch planning, continued
memory carried overPicking up where we left off, decisions, constraints and open questions are in place. Nothing to re-explain.
Memory is stored in Lippa, on EU infrastructure, not inside any model vendor. It is never training material, never sold, and always exportable. Shared links never expose it.
