The memory your AI should have had from the start.

Why · Quick Start · Compare · Tiers · Benchmarks · API · Docs · FAQ

It finds signal in the noise. Your AI sees thousands of messages. TrueMemory figures out which ones actually matter and throws away the rest. No manual tagging, no prompt engineering. It just knows.

It gets sharper over time. It's not a static database. It's a living memory that grows with you. It resolves contradictions when you change your mind, updates stale facts, and consolidates what it knows. The longer you use it, the better it gets.

It works without you thinking about it. TrueMemory automatically captures memories from your conversations and automatically injects the right ones into your next session. You never have to store or search for anything manually. It just happens.

It's 100% local. One SQLite file on your machine. Nothing leaves your device. No cloud, no API keys needed. Your data is yours.

Without TrueMemory: "What framework are we using?" Asked for the 12th time this week. Your agent starts every session with amnesia. It doesn't know your name, your stack, or anything you told it yesterday.

With TrueMemory: Your agent already knows you use FastAPI, prefer Pydantic v2, and that your auth middleware lives in src/auth/. It remembers your corrections, your preferences, and your decisions. Across every session, forever.

All benchmarks independently reproducible. Scripts included in benchmarks/.

curl -LsSf https://raw.githubusercontent.com/buildingjoshbetter/TrueMemory/main/install.sh | sh

Installs everything in an isolated environment. Downloads ~1.5GB of AI models. No data leaves your machine. No sudo required.

irm https://raw.githubusercontent.com/buildingjoshbetter/TrueMemory/main/install.ps1 | iex

That's it. TrueMemory remembers your conversations automatically from here.

pip install truememory

from truememory import Memory

m = Memory()
m.add("Prefers dark mode and TypeScript", user_id="alex")
print(m.search("preferences", user_id="alex"))

Same architecture, three tiers. All included in a single install. Switch anytime by saying "switch to Pro" or "switch to Base."

Edge works everywhere. Base is the strongest fully-offline tier. Pro adds AI-powered query expansion for the highest scores.

Tested across three major benchmarks with all systems sharing the same answer model (GPT-4.1-mini), judge (GPT-4o-mini, 3x majority vote), and scoring pipeline.

Every benchmark script is self-contained and runs on Modal.

• LoCoMo Scripts — 8 systems (TrueMemory, Mem0, Zep, Engram, etc.)
• LoCoMo Results — per-category breakdowns, latency, cost
• LoCoMo Eval Config — exact models, prompts, parameters
• LongMemEval Scripts — oracle + strict variants
• LongMemEval Results — 6 TM Pro runs + 5 competitor results
• BEAM-1M Script — 35 conversations at 1M+ tokens
• BEAM-10M Script — 10 conversations at 10M tokens
• BEAM Results — 3 runs (1M) + 1 run (10M)

All benchmarks use the same eval pipeline. Nothing is hidden. Full details: LoCoMo | LongMemEval | BEAM

Claude Code · Claude CLI · Cursor · Codex CLI · Gemini CLI · Claude Desktop

Lifecycle hooks capture conversations automatically. No manual work needed. Your memories stay local in a single SQLite file.

from truememory import Memory

m = Memory()

m.add("Prefers dark mode and TypeScript", user_id="alex")
m.add("Works at Anthropic as a senior engineer", user_id="alex")

results = m.search("What are Alex's preferences?", user_id="alex")
results = m.search_deep("career history?", user_id="alex")  # multi-round, higher accuracy

Full API reference →

pip install truememory

Questions? Open a Discussion. If TrueMemory saves you time, give us a ⭐

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TrueMemory is backed by a peer-reviewed research paper on retrieval-centered agent memory.

Storage Is Not Memory: A Retrieval-Centered Architecture for Agent Recall (arXiv 2605.04897)

@article{adler2025storage,
  title   = {Storage Is Not Memory: A Retrieval-Centered Architecture for Agent Recall},
  author  = {Sauron Labs},
  journal = {arXiv preprint arXiv:2605.04897},
  year    = {2025},
  url     = {https://arxiv.org/abs/2605.04897}
}

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• Open a Discussion for questions or ideas
• Read the paper on arXiv · Google Scholar · Semantic Scholar
• Visit truememory.net · sauronlabs.ai

If TrueMemory saves you time, give us a ⭐

AGPL-3.0. Free for personal and research use. Commercial use requires a separate license. Contact josh@sauronlabs.ai.

TrueMemory, a sauron company