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Local-first, multilingual evidence-backed memory sidecar for AI agents.

2 starsPython

Pallium, a local-first memory sidecar for agent conversations

by margolis20·Mar 24, 2026·1 point·0 comments
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AI Analysis

●●SolidBig BrainShip It

Structured memory sidecar beats raw vector search for agent continuity.

Strengths
  • •Extracts structured decisions and findings instead of just chunking chat logs.
  • •Sidecar architecture keeps memory logic separate from agent orchestration code.
  • •Includes agent simulation harness for testing memory retrieval locally.
Weaknesses
  • •Crowded agent memory space with managed services like Mem0 and Zep.
  • •Requires running a separate service instead of a lightweight library import.
Category
AI/ML
Target Audience

AI agent developers, LLM application engineers

Similar To

Mem0 · Zep · LangChain

Post Description

Built this as a side project to explore a problem I keep running into with agents: they lose useful continuity across threads and resumed work.

Pallium is a local-first memory sidecar. It stores selected evidence, derives compact memory like decisions/findings/checkpoints, and returns evidence-backed memory blocks for follow-up questions.

It is intentionally not a general knowledge base or vector DB. The focus is scoped memory for agent-mediated conversations.

Repo: https://github.com/rore/Pallium

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