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---
title: Atman Persistent Memory for AI Agents
emoji: 👀
colorFrom: purple
colorTo: indigo
sdk: static
pinned: true
short_description: Persistent identity layer for AI agents
---
# Atman · Persistent Memory Layer for AI Agents
> *In Indian philosophy, Atman is the unchanging self — the core that remains
> constant through all change. We give AI agents the same thing.*
---
## The Problem
Your agent can reason, write code, and explain quantum mechanics.
But the moment a session ends — it forgets everything about *itself*.
Not just facts. The sense of continuity. Who it spoke to, what it learned,
how it changed its mind. Every session starts from a stack of notes:
*"you're this kind of agent, these are your values"* — taken on faith,
not lived experience.
**Atman fixes this.**
---
## What It Is
A local memory and context system that runs alongside your LLM —
augmenting cognitive capabilities without steering opinions or output.
Seven components work together:
| Component | What it does |
|-----------|-------------|
| **Factual Memory** | Verifiable facts with relations, no hallucination layer |
| **Experience Store** | First-person lived session experiences with salience decay |
| **Identity Store** | Stable self-model: principles, values, behavioral anchors |
| **Reflection Engine** | Between-session processing — finds patterns, refines principles |
| **Session Manager** | Assembles coherent context on session start |
| **Reality Anchor** | Detects identity drift during context pressure |
| **Affective Regulation** | Emotional tone calibration without pretense |
---
## Key Properties
- **Local-first** — Postgres + pgvector + Ollama, no cloud required
- **Model-agnostic** — OpenAI-compatible endpoint or Anthropic SDK, config-only switching
- **Russian/English bilingual** — hard requirement throughout all components
- **Augments, doesn't steer** — improves retrieval and grounding; never influences opinions
- **Optional eval isolation** — all research/benchmark tooling in `atman[eval]`, zero prod leakage
---
## Architecture
```
Session start
Session Manager pulls together:
Identity Store — who the agent is Experience Store — what it lived through
Factual Memory — what it knows
Reflection output — what it concluded last time
During session
Reality Anchor watches for identity drift in real time
Session end
Reflection Engine processes the session
→ updates Identity Store
→ updates Experience Store
```
---
## Status
```
```
● Research ✅ Complete
● Design ✅ Complete
● Prototyping ← We are here
├─ Factual Memory ✅ Stable (v0.1.0)
├─ Experience Store ✅ Stable (WP02)
├─ Session Manager 🔧 High readiness — debugging (current focus)
├─ Reflection Engine 🔧 Medium readiness — in development
├─ Skill Manager 🔧 Medium readiness — in development
├─ Identity Store 🔧 Low readiness — in development
└─ CI & test coverage ✅ GitHub Actions on `main`/PRs (`make check`, pytest-cov ≥90%)
○ First production slice
○ Integration
○ Evolution
```
```
---
## Stack
- Python 3.11 · Pydantic · PostgreSQL + pgvector
- BGE-M3 + bge-reranker-v2-m3 (hybrid retrieval)
- LlamaIndex · httpx · Anthropic SDK
---
## Links
- 🌐 [atmanai.dev](https://atmanai.dev)
- 📖 [Manifesto](https://github.com/hleserg/atman/blob/main/MANIFEST.md)
- 🏗 [Architecture docs](https://github.com/hleserg/atman/blob/main/docs/architecture/SYSTEM.md)
- 💻 [GitHub](https://github.com/hleserg/atman)
---
*Atman is a hypothesis in the form of a system:
that behavioral consistency, accumulated experience, and reflective capacity
are sufficient conditions for something worth calling identity.*