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EverOS OSS gives AI agents persistent memory without external infrastructure. The core design decision: Markdown files are the source of truth for memory, not a database. A three-component embedded stack handles state and retrieval on top: 
Markdown (truth)  +  SQLite (state)  +  LanceDB (index)
This one decision drives the rest of the architecture — zero external services, human-readable memory files, offline-capable edge deployment, and a cloud migration path that requires no code or data changes.

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How the Design Cascades

Markdown-first (md is truth)
├── index rebuildable from md       →  zero external services, no ops overhead
├── md portable + API isomorphic    →  edge prototype migrates to cloud as-is
├── md partitioned by owner dir     →  user / agent / knowledge physically isolated
└── md is a text carrier            →  multimodal content unified under one protocol

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Three Memory Tracks

Memory in EverOS OSS is organized into three top-level directories, each answering a different question: 
memory-root/
├── users/      User Memory    · "Who is this user and what have they said?"
├── agents/     Agent Memory   · "What has this agent learned?"
└── knowledge/  Knowledge Wiki · "What reference material has the system been given?"
Writes are routed automatically based on message role. No manual routing or configuration required.

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EverOS OSS vs Cloud

OSSCloud
DeploymentSelf-hostedManaged
Storagemd + SQLite + LanceDBHosted infrastructure
External servicesNoneNone to configure
Offline / edge capableYesNo
Setuppip install or DockerAPI key
Data locationFully localYours, on EverMind servers
Migration pathStart here, move to Cloud when ready—
Choose OSS for full data control, edge and offline deployment, or custom infrastructure. Choose Cloud for managed scale without ops overhead. The two share the same API contract. Code written against the OSS embedded library migrates to Cloud by swapping method calls for equivalent HTTP requests — parameters and return structures are identical.

Quickstart

Install EverOS OSS and run your first memory write.

How Memory Works

The md-first storage model and embedded stack in detail.

Memory Types

User, agent, and wiki memory — types, structure, and routing.

Retrieval

How mRAG selects the right memory at the right granularity.