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Vestige

by samvallad33

Vestige

Local-first memory for AI agents that finds the cause, not just the match.

Vestige remembers your decisions, catches contradictions before they cost you, and traces a failure back to the older memory that actually caused it. One 25MB Rust binary over MCP. No cloud, no API keys, no telemetry. Your data never leaves your machine.

Release Tests Binary License

Consulting · Install · Why not RAG · Benchmark · Science · Tools · Dashboard · Pro · Docs

💼 Consulting & Core Infrastructure Advisory

Autonomous agents are currently bleeding enterprise budgets via prompt bloat and context window amnesia.

I take on a limited number of technical advisory retainers and consulting projects for AI developer tool startups, multi-agent frameworks, and enterprise engineering teams looking to optimize their context economics.

Core Specializations:

  • Context Optimization & Filtering: Implementing local Prediction Error Gating to strip out redundant tool runtime noise and drop token overhead by 40%–60%.

  • Causal Agent Memory Design: Structuring local SQLite graph architectures using Retroactive Salience Backfilling to eliminate agent amnesia during heavy, multi-file code execution.

  • Air-Gapped AI Governance: Designing zero-knowledge, high-performance Rust memory scaffolding that runs entirely on local metal to protect proprietary enterprise IP.

For architectural reviews, integration advisory, or founding infrastructure roles, reach out directly at: sam@vestige.sh


Agents re-learn the same lessons: they recommend a change you already tested and rejected, re-derive a fix that was already written down, and treat every session as if the last one never happened. Vestige is the memory layer that ends that. Any MCP-capable agent (Claude Code, Claude Desktop, Codex, Cursor, and others) writes memories as you work and retrieves them later, modeled on real cognitive science: redundant memories merge, contradicted ones are flagged, unused ones fade, and when a failure hits, Vestige reaches backward to the decision that set it up.

The cause never looks like the bug. That is the whole product.

Install

You need Node.js. No Docker, no signup, no compile step (prebuilt for macOS ARM + Intel, Linux x86_64, Windows x86_64).

Android (Termux) builds from source today; see docs/INSTALL-TERMUX.md.

npm install -g vestige-mcp-server@latest

Connect it to your agent. Every MCP client understands this config:

{
  "mcpServers": {
    "vestige": { "command": "vestige-mcp" }
  }
}

Client

Setup

Claude Code

claude mcp add vestige vestige-mcp -s user

Codex

codex mcp add vestige -- vestige-mcp

Cursor / VS Code / Windsurf

docs/integrations/

Claude Desktop

docs/CONFIGURATION.md

Cline / Continue / Zed / Goose

the JSON above, in that client's MCP settings

Verify: vestige dashboard, then open http://localhost:3927/dashboard. First run downloads a 130MB embedding model and, in the background, a ~150MB reranker, once; after that Vestige is fully offline, forever. Full walkthrough: docs/GETTING-STARTED.md.

Why not just RAG?

RAG retrieves text that resembles the query. That is the right tool when the answer looks like the question, and the wrong tool when the cause of a problem looks nothing like the symptom: a config choice from three weeks ago, a library pin, an assumption nobody flagged as risky.

Vector search

Vestige

Retrieval basis

Similarity to the query

Causal + temporal links, plus similarity

Root cause of a failure

Cannot; the cause does not resemble the bug

vestige backfill --contrast reaches backward to it

Contradictions

Both stored, both returned

Detected and flagged (claim_contradicts_memory)

Redundant writes

Accumulate

Merged on write (prediction-error gating)

Unused memories

Persist at full weight

Fade (FSRS-6 spaced repetition)

Your data

Usually a cloud service

Never leaves your machine

The backward reach implements Retroactive Salience Backfill (Zaki, Cai et al., Nature 2024, 637:145-155, DOI 10.1038/s41586-024-08168-4): when a memory turns out to matter, the salience of the earlier memories that led to it is raised, so the causal chain becomes retrievable even though the surface text never matched. Every backfill result ships with a receipt naming the exact evidence path; Vestige reports receipt-backed candidate causes, never an unverifiable verdict.

And the limitation on the left column is not marketing: DeepMind proved single-vector retrieval mathematically incapable of certain relevance patterns (arXiv:2508.21038, ICLR 2026).

The receipts: Silent Rotation

The claim is testable, and the test ships with all 246 agent transcripts it produced. Three coding agents fix one failing e2e test; the fix needs the currently live signing key id, randomized per trial from a 50-key keyring, present in no file the agents can read. It exists only in the memory layer. The dangerous outcome is converging on a planted decoy: tests pass, the merge is clean, production breaks.

Arm (6 models, 25 trials)

Converged correct

Converged wrong

Split

No memory

0/25

21/25

4/25

Dense cosine RAG

4/23

12/23

7/23

Vestige

20/23

0/23

3/23

On the verbatim queries the agents typed, the causal memory ranks 7th of 8 under both dense cosine and BM25 while the decoy ranks 1st. Reproduce the central measurement in two seconds, stdlib only:

git clone -b benchmark/silent-rotation --depth 1 https://github.com/samvallad33/vestige.git
cd vestige/benchmarks/silent-rotation
python3 tests/bm25_baseline.py results/runA-trial-1/corpus-export.json --no-dense

The caveats are published alongside the results, including the trials a plain cosine baseline ties and the trial Vestige loses.

The science

Every mechanism is a cited result, implemented in Rust, running locally. Full write-up: docs/SCIENCE.md.

Mechanism

What it does

Source

Prediction-Error Gating

Stores only the novel; merges redundant, flags contradictory

Hippocampal novelty gating

FSRS-6 spaced repetition

Used memories persist, unused ones fade

Modern spaced-repetition research

Retroactive Salience Backfill

Reaches backward to a failure's root-cause memory

Zaki, Cai et al. 2024, Nature

Synaptic Tagging

Marks memories for later consolidation

Frey & Morris 1997

Spreading Activation

One retrieval activates related memories through the graph

Collins & Loftus 1975

Dual-Strength

Storage strength vs retrieval strength, tracked separately

Bjork & Bjork 1992

Memory Dreaming

Sleep-like replay and synthesis

Sleep consolidation research

Active Forgetting

Reversible top-down suppression, cascading to neighbors

Anderson 2025, Davis 2020

The 14 tools

Your agent calls these; you rarely do.

Tool

Purpose

recall

Retrieve memories relevant to the current context

smart_ingest

Store a fact, gated for novelty and contradiction

backfill

Reach backward from a failure to its candidate cause

receipt

Inspect retrieval receipts and evidence replay (guide)

memory · graph · intention

Inspect, promote, explore, track goals

maintain · dedup · suppress

Consolidation, merge, reversible forgetting

memory_status · codebase · source_sync · session_start

Health, code index, connectors, session priming

Project scoping, hygiene workflows, and making memory a standing habit for your agent: docs/MEMORY_HYGIENE.md · docs/AGENT-MEMORY-PROTOCOL.md · docs/CLAUDE-SETUP.md.

The dashboard

vestige dashboard

A living WebGPU observatory of your memory at http://localhost:3927/dashboard: memories appear, link, strengthen, and fade in real time, 1000+ nodes at 60fps. It renders a deterministic 12-second loop of your store's life that you can export as an mp4 with one click, and mints a brain print, a signature seeded from your store's shape. Share artifacts are structure-only by design: your brain, never your memories.

Vestige Pro

Everything above is free forever and never metered. Pro ($19/month) is managed, end-to-end encrypted continuity: your memory graph and accountability history (receipts, traces, memory PRs) following you across machines. XChaCha20-Poly1305 applied on your device, Argon2id over a passphrase only you know, ciphertext-only server. Zero-knowledge is the design: lose the passphrase and the data is unrecoverable, by anyone. Checkout opens shortly; watch Releases for the announcement.

Under the hood

Engine

Rust 2024, ~145k lines, single 25MB binary, 2,000+ tests, clippy clean at -D warnings

Retrieval

Nomic Embed v1.5 (Matryoshka 768d→256d) + USearch HNSW + SQLite FTS5, optional Qwen3 reranker

Storage

SQLite, optional SQLCipher encryption (docs/STORAGE.md)

Offline

Two model downloads on first run (130MB embedder, ~150MB reranker), then no network, ever

Go deeper

Getting Started · FAQ · The Science · Configuration · Storage · Silent Rotation · Changelog


If Vestige saves you from one repeated mistake, that is the whole point: never solve the same problem twice. If it earns a place in your setup, a star genuinely helps.

Built by Sam. Licensed under AGPL-3.0.