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Sekha – What if AI remembered 3 years of conversations, not 3 hours?

Sekha – What if AI remembered 3 years of conversations, not 3 hours?

by sekha-ai·Feb 17, 2026·1 point·1 comment

AI Analysis

●●SolidNiche GemSolve My Problem
The Take

The core idea is simple and pragmatic: attach a persistent, SQLite-backed vector store to any model so conversations don't vanish after a single context window. The repo leans into portability (Rust, self-hosted, AGPL) and the UI shows sensible controls like conversation folders and a context-budget token slider — useful details that suggest this is built for real use rather than a demo. My worry: retrieval quality, scaling and access controls will be the real battleground, not the clean chat UI.

Category
Target Audience

Developers, AI engineers, privacy-conscious teams and hobbyists who integrate LLMs and need long-term conversational memory

Post Description

Every AI assistant today has amnesia. Context windows fill up and you're starting over with a stranger.

Sekha gives your LLM a permanent memory: - Unlimited conversation history with semantic search - Works with any model (Claude, GPT, Llama, local) - Self-hosted, your data stays local - Built with Rust + SQLite + embeddings. AGPL-3.0.

GitHub: [github.com/sekha-ai/sekha-controller] Docs: [docs.sekha.dev] | Site: [sekha.dev] Proof: https://imgur.com/a/Dgti8cO

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