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Dual-wave marketing assets (Receipt Lock + cognitive memory), GitHub Pages landing, comparison doc, ready-to-post copy, growth-engine scripts, and a dedicated marketing Vestige data-dir setup path. Co-authored-by: Cursor <cursoragent@cursor.com>
3.8 KiB
3.8 KiB
Vestige vs Mem0 vs RAG vs Native AI Memory
Canonical comparison for launch posts and arguments. Grounded in SCIENCE.md and LAUNCH_STATS.md.
One-line thesis
RAG is retrieval. Native memory is a black box. Mem0 is a strong cloud memory API. Vestige is a local cognitive system that forgets, strengthens, dreams, and can block unverified agent claims.
Comparison table
| Capability | RAG / vector DB | Native AI memory (Claude, ChatGPT) | Mem0 | Vestige |
|---|---|---|---|---|
| Runs local | Often cloud embeddings | Cloud only | Cloud API (local option limited) | 100% local default |
| You own the data | Your infra | Vendor | Vendor / API | SQLite on your disk |
| Forgetting curve | None — equal weight forever | Opaque | Categories + metadata | FSRS-6 power-law decay |
| Duplicate handling | Manual | Opaque | Some dedup | Prediction Error Gating on ingest |
| Retrieval strengthens memory | No | Unknown | Partial | Testing Effect on every search |
| Offline consolidation | No | No | No | dream — replay + connect |
| Contradiction awareness | Returns both chunks | No | Some products | deep_reference / contradictions |
| Active suppression | Delete only | No | Delete | suppress — inhibited, not erased |
| Agent overclaim guard | No | No | No | Receipt Lock (optional Sanhedrin hooks) |
| Visualization | None | None | Dashboard (cloud) | 3D graph + WebSocket events |
| Protocol | Custom | Proprietary | API + MCP | MCP (25 tools) |
| License | Varies | Proprietary | Apache / commercial | AGPL-3.0 (local use = free) |
When to use what
Use RAG when
- You have a fixed document corpus (PDFs, wiki, codebase index).
- You need one-shot Q&A over static content.
- You do not need memory lifecycle or session continuity.
Use Mem0 when
- You want a hosted memory API with minimal setup.
- Team sync and cloud dashboards are acceptable.
- You do not need FSRS decay or local-only air-gapped deploy.
Use native Claude/ChatGPT memory when
- Casual personal context is enough.
- You do not need inspectable storage, decay curves, or contradiction tooling.
Use Vestige when
- You run Claude Code, Cursor, Codex, or any MCP client daily.
- Context bloat from "remember everything" hurts retrieval quality.
- Contradicting memories have burned you (config changed, lib upgraded).
- You want Receipt Lock so agents cannot fake "tests passed."
- Privacy / air-gapped matters — embeddings run locally via ONNX.
Honest limitations (Vestige)
- AGPL-3.0: hosting as a service without source disclosure is not allowed.
- First-run download: ~130MB embedding model (then offline).
- Receipt Lock requires optional Claude Code Cognitive Sandwich hooks + a verifier endpoint for Sanhedrin.
- Neuroscience modules mix faithful implementations and engineering heuristics — see SCIENCE.md for citations vs approximations.
- Solo project: no enterprise SLA; GitHub issues are the support channel.
Receipt Lock (Vestige-only)
Coding agents often end sessions with:
"All tests passed. Build is green. Ready to merge."
Receipt Lock checks those operational claims against structured command receipts from the transcript. No matching successful receipt → claim blocked, local veto receipt written under ~/.vestige/sanhedrin/.
vestige sandwich install --enable-sanhedrin
Details: README Receipt Lock section.
Install
npm install -g vestige-mcp-server@latest
claude mcp add vestige vestige-mcp -s user
Full stats: LAUNCH_STATS.md · Repo: https://github.com/samvallad33/vestige