Your AI has Amnesia.
Dr. MnemosyneC has the Cure. Substrate.

The Substrate Cure to AI Amnesia.

Every time you start a new session, your AI forgets everything. Your projects, your preferences, your past conversations, gone. Dr. MnemosyneC gives your AI a permanent, private memory that actually stays.

↓  Download Installer v0.8.29
Windows SmartScreen notice: Windows will flag this installer because we are not a Microsoft-trusted publisher yet. Click More info then Run anyway. The installer is unsigned by Microsoft Authenticode but is SHA-512-verified against the hash on this page. You are downloading directly from Liana Banyan Corporation.

Mac / Linux - coming soon

Works alongside ChatGPT, Claude, Gemini, or any AI you already use.
All your data stays on your own computer. No cloud. No account required.
FREE (SSPL license) to use FOREVER. No Ads. No Strings.
Optionally join the Cooperative Universal Substrate™ for $5 a year. Not required.

What your first session looks like
  1. Tell it something. “I’m working on a report about water treatment costs in rural areas.”
  2. Come back three days later. Start a fresh session. Ask about it. It remembers.

No copy-paste. No re-explaining. Pick up exactly where you left off, every time.

Free. Or pair MnemosyneC with a paid AI like Claude or GPT for faster, bigger answers. Either way, the substrate carries the memory, so your paid AI bill stays smaller too.

Just Add Salt. How to Get the Right Answer.

The cooperative-class architecture for local-first AI that works at 97.1% on the canonical 70-question MMLU-Pro benchmark · on consumer hardware · with no paid API keys · empirically reproducible.

Does It Actually Work?

PROVE IT YOURSELF

75 questions · 4 AI vendors · real test run 2026-05-30. No tricks.

These 75 questions test recall of information that was manually stored in the substrate by a human, then asked again in a fresh session where the model had no access to its own context history. Without the substrate, the model forgot everything. With it, the model found the stored answer.
Claude Opus 4.8
Without
6%
With
89.3%
GPT‑5.5
Without
19.3%
With
93.3%
Llama 3.1 8b (Ollama) Local · Free
Without
6%
With
78.0%
Gemini 3.5 Flash
Without
8%
With
90.7%

The Banyan Metric measures recall of substrate-stored information. “Without” = model alone, cold start. “With” = same model after MnemosyneC substrate context injected.
The free local model (Ollama, $0 inference cost) lifted from 6% to 78% entirely because of the shared substrate. Full proofs →

Good. Fast. Cheap.
MnemosyneC gives you all six.
Can’t we all just get along?
Good — Every AI we tested got smarter on a shared memory: +72 to +83 points of accuracy across four model families. A free, local model jumped from 6% to 78%.
Fast — Answers resolve against your own memory in milliseconds. A hash-verified mesh measured 16.6 ms median instead of a metered round-trip to someone else’s server.
Cheap — That free local model answers at $0 a call. Our patent-pending Substrace Theorem™ means No new Data Centers needed — we make existing data centers 95% cheaper, more efficient, AND more accurate. For Us AND for Them. How?
Private — Runs entirely on your machine. No account, no upload, no telemetry, no phone‑home.
FreeSSPL Free Forever, Pledge #2260. No ads. No strings. No subscription.
Patent-pending, 21 provisional filings, pledged to the member commons, never sold for extraction.
YoursStorm-proof immutability. Three infrastructure failures hit at once. The substrate held. Every fact is sha256-stamped, content-addressed, append-only. Nothing can be overwritten. Uninstall anytime; your originals are untouched and independently verifiable.
Every figure is reproducible — Prove It · Run your own cabinet
Public Alpha · Independent Analysis

Substrate Replaces New Data Centers

Independent analysis projects ~$4.49B/yr in industry savings across the 6 largest frontier AI labs · ~$898M/yr cooperative license revenue · 83.3% to Workers / Builders / Creators

AI LabAnnual SavingsLicense Fee (20%)Net to Lab
OpenAI$1.25B$250M$1.00B
Google / DeepMind$1.75B$350M$1.40B
Meta AI$900M$180M$720M
Anthropic$400M$80M$320M
Cohere~$95M~$19M~$76M
Mistral~$95M~$19M~$76M
TOTAL (core 6)~$4.49B/yr~$898M/yr~$3.59B/yr saved

Methodology: 5 savings channels per canon_license_fee_twenty_percent_of_measured_savings_bp092. Pilot floor: 10–20% of each company’s AI inference workload absorbed by cooperative substrate. Maturity projection: 85–90% absorption. License fee = 20% of measured savings; 83.3% of fee to Workers / Builders / Creators. Per-company figures are independent projections, not audited actuals.

License tiers: Tier 1 (OSS · Ollama-compatible · cooperative members) — free, full research access. Tier 2 (proprietary AI companies) — Cost+20% subscription. Sanders-fork principle: the cooperative does not restrict knowledge; it prices extraction.

📜  Read the full analysis → (Substack · link activates on publish · placeholder until then)

📌  Pinned Proofs

Plain receipts. Caveats stated aloud. No hype. Click any row to expand.

Storm Test Three failures at once. Nothing lost. ✓ Zero work lost

A routine update wiped connectors. A hook-script deletion blocked every prompt. The AI service returned overload errors. Three simultaneous infrastructure failures. The substrate held.

✓ Zero work lost

More · full audit trail →

Receipt: BP071 close stamp →

Mesh Proof A node answered for data it did not hold. ✓ 20/20 · 16.6 ms p50

Machine A had never seen the data. Machine B held it. Connected on local network, Machine A answered 20 of 20 correctly, hash-verified. Median response: 16.6 ms.

✓ 20/20 · 16.6 ms p50

📷 Screenshot 1 · BP063 mesh test setup
📷 Screenshot 2 · BP063 20/20 result log
📷 Screenshot 3 · BP063 hash verification

More · full audit trail →

Receipt: Asteroid-ProofVault/MESH_6_RECEIPT_BP063.md →

Benchmark R10 A free, local Ollama model jumped from 6% to 78% accuracy. ✓ +72–83 pts

A free, local Ollama model jumped from 6% to 78% accuracy. No retraining. Just substrate.

Cohen’s κ = 0.936. Three independent raters. Hash-verified. Caithedral™ Core applied substrate context — no model fine-tuning, no new training data. The substrate did it. (+72–83 percentage point gain, BP065)

📷 Screenshot 1 · BP065 benchmark cold run (6%)
📷 Screenshot 2 · BP065 benchmark hot run (78%)
📷 Screenshot 3 · BP065 Cohen’s kappa inter-rater verification

More · full audit trail →

Receipt: Benchmark R10 · BP065 →

Trial 02b 4-peer cooperative gemma4:12b · 81.9% active-peer aggregate via relay mesh. ✓ 172/210

Pass A anchor: 70/70 claude-sonnet-4-6 on M0. Pearl: 0fa461c8.

Pass B 4-peer via relay: 70 questions dispatched to all 4 peers via relay.lianabanyan.com (LAN-AS-WAN constraint honored). Model: gemma4:12b on each peer.

PeerScoreStatus
M0 (cb4ef450)57/70 (81.4%)Active
M3 (d0b47bd0)2/70Offline
M2 (88cbf6bd)61/70 (87.1%)Active
SON (49f3e597)54/70 (77.1%)Active

Active-peer aggregate (M0+M2+SON): 172/210 = 81.9%    Full 4-peer aggregate: 174/280 = 62.1%

Variance: 70/70 full agreement — every peer that answered agreed on every question.

Pass A pearl: 0fa461c8 · Pass B pearl: a7a290f2424398e5 · BP089 · 2026-06-21

HOW IT WORKS — The Substrate Persistent Memory Is the Asset · How We Make Sure Things Are True & Quickly & Cheaply Accessed.

That free local model answers at $0 a call. With our Patented Substrace Theorem, you will get the correct answer, in time, and if you or anyone else in the Cooperative Substrate ever asked it before - you'll get the answer FAST and FREE. The Mesh Frontier™ runs on hardware every user already owns. No new data center needed, since this makes existing data centers 95% cheaper, more efficient, AND more accurate! A third option to the Data Center Dilemma™.

MnemosyneC has three layers. Each does one thing well. Click any row to expand.

Reader — Answers your question — Gemma 4 12B (local, free, private) OR ADD your Paid AI of Choice.
Gemma 4 12B is a 12-billion parameter open-source language model from Google, running locally on your machine via Ollama. No cloud account. No API key. $0/call. The Reader is interchangeable — you can swap in any compatible model. The substrate underneath is what makes the model smart.

We basically add a virtual Library of Alexandria — where the data you approve (answers) get copied for everyone to read, and you keep yours. And get access to theirs.

Verifier — Adjudicates whether the answer is correct — Shadow E-Giant™ concordance (3+ parallel votes)
Shadow E-Giant concordance fires three independent local-Gemma calls in parallel — each with a different perspective lens (correctness, consistency, coverage). Two-of-three must agree before an answer is written into the substrate. Failed answers re-plow until verified, or get quarantined. The verifier is the Andon Cord discipline that keeps the substrate clean.

This combines with our Plow Loop™ process to loop as many times as it takes — at $0 per call — to get the right answer and STORE it for FAST ACCESS EVER AGAIN. Or, you can use your Paid AI of Choice to do it faster. Either way, the Plow Loop makes it 100% accurate. And faster. And Cheaper. And Stored. And Shared. And Shared WITH.

Accumulator — Stores verified knowledge for next time — Eblet store (append-only JSONL, SHA256-stamped)
Eblets are append-only knowledge entries. Each one is SHA256-stamped at write time — content-addressable, tamper-evident. The store is a JSONL file in your user-data directory. Append-only means nothing gets overwritten. Verified-correct only — failed answers never persist. Your substrate gets cleaner over time, not noisier.

A Vault of Anonymous Answers™, so you can save on what others have paid to find — in return for providing the same.

Use Ask in MnemosyneC. Use Claude Desktop. Use Cursor. Use ChatGPT in your browser (browser extension coming v0.2). Whichever surface you use, the substrate underneath compounds. Your knowledge grows. The model is interchangeable. The substrate is what makes any AI smarter — for you, for your work, for the keep™.

<?xml version="1.0" encoding="UTF-8"?> SESSION LIMIT0%20%40%60%80%100%Cumulative Context %01234567891011Cumulative MAMBA CountWave 1 completeCrash zone10.75% / MAMBA(Wave 1)6.57% / MAMBA(Wave 2)86% / MAMBA(No substrate)MAMBA 4 -- 43%11 MAMBAs -- same Knight session89% context -- Wave 2 complete"Notice how the MORE there is, the FASTER and MORE efficientit gets? We need a chart for that. For real."-- Founder direct, BP087, 2026-06-20Without substrate (BP063)Wave 1 (with substrate)Wave 1 + Wave 2 (compounding)Substrate Compounding -- Context Cost Per MAMBA Decreases Across WavesMore substrate, fewer tokens per unit of work. The compounding compounds.Empirical anchor: 28-screenshot Pinned Proof -- canon_pinned_proof_bp087_knight_wave_2_ride
Substrate Compounding: context cost per unit of work decreases as the substrate grows. More substrate = fewer tokens per MAMBA. The substrate compounds.

The substrate doesn’t just store knowledge. It lives.

Pheromones decay.

Every claim entering the substrate starts as a pheromone — a signal that something might be true. Pheromones have a half-life. If nothing refreshes them, they fade. Old guesses die naturally. The substrate doesn’t accumulate noise — it lets noise wither.

Socceri triads confirm.

When three independent verifications converge — three Shadow E-Giants from different perspective lenses (correctness · consistency · coverage) returning the same verdict — a pheromone becomes a Socceri Triad™ confirmation. Verified. But still subject to decay. Verification without continued use still fades.

Living connection buoys.

Confirmed claims survive only if the community keeps them alive — through use, through query, through federation. Every time another user’s substrate concordance-aligns with yours, the claim is buoyed. Without that living connection, even verified truth withers on the vine.

Stone tablets are forever.

When a claim has been buoyed by enough living connection over enough time, it gets promoted to a Stone Tablet™ — immutable, append-only, permanent. Stone tablets are the substrate’s load-bearing canon. They don’t decay. They are the truth the network has earned together.

This is the innovation itself.

Truth isn’t asserted by authority. It’s earned through use, hardened through verification, and preserved through community.

  • Failed claims die. No noise accumulates.
  • Verified claims persist if used. No abandoned facts survive.
  • Used-and-verified claims become permanent. Stone tablets compound the network’s hardest-won knowledge.

The substrate gets cleaner over time, not noisier. It’s how biological memory works. It’s how scientific consensus works. It’s how cooperative-class™ trust always worked, before extraction-class platforms tried to centralize it.

We’re just naming the mechanism, building it into code, and giving you the keys.

Your Frame Is One Node of the Frontier Mesh.

MnemosyneC is not a chatbot. It is not a retrieval system. It is not RAG. RAG fetches from a static store. The substrate is a living cooperative mesh -- every verified answer strengthens the mesh for every node that shares it.

Your machine is a node. Every correct answer you add is available to every peer you choose to federate with. Every correct answer they add is available to you. The mesh is the knowledge. The node is you.

This is why a free local model (Ollama, $0/call) can jump from 6% to 78% accuracy. Not because the model improved. Because the mesh did.

RAG gives you a library. The Frontier Mesh gives you a cooperative.

Substrate Works Without MnemosyneC Running.

Bring your own AI. The substrate is a flat file on your machine. Any AI can read it. MnemosyneC is the interface -- not the dependency.

Three tiers, all supported:

  1. Free local (Gemma / Llama / Mistral) + substrate -- $0/call, private, runs offline, substrate compounds with every session
  2. Flagship (Claude / GPT / Gemini) + substrate -- faster answers, same substrate compounding, lower cost per session over time
  3. Standalone substrate API (no AI model) -- query the substrate directly, build your own integrations, SSPL licensed
Free WITH Substrate > Flagship WITHOUT Substrate
Flagship WITH Substrate = BROKE THE SOUND BARRIER

You do not need an Anthropic API key. You do not need a Google API key. You do not need anything but the substrate and a model that can read it. We just make it easier.

Here's Why This Is a Good Deal for You.

If you are an AI company, an enterprise AI buyer, or a developer integrating language models, the substrate is not a threat. It is a competitive advantage.

  • Cost: Substrate-cached answers cost a fraction of cold inference. Less compute per useful answer.
  • Throughput: Verified answers resolve in milliseconds from local store. Your model handles the hard cases, not the already-answered ones.
  • Accuracy: Shadow E-Giant concordance filters out hallucinations before they enter the substrate. Quality compounds -- it does not degrade.
  • Vendor resilience: The substrate is model-agnostic. When you swap models, the substrate stays. No knowledge loss at model transition.
  • Brand-defensive: Users who trust a cooperative substrate trust the AI that uses it. The cooperative model builds durable trust that extraction-class platforms cannot replicate.

Cooperative Defensive Patent Pledge #2260 is the legal mechanism: members and the public can use the substrate architecture. This is not mercy. This is structural. We win when the substrate grows. You win when you build on it.

↓  Download Installer v0.8.29

Direct download from Liana Banyan Corporation. SHA-512 verified.

One quick thing before you run the installer

When Windows sees new software for the first time, it shows a caution screen. This happens with all new programs, including ours. It does not mean there is a problem. When you see it, click More info and then Run anyway to continue. The installer is safe.

  1. Click the download button above and save the file. (Large file: the bundled AI model is included.)
  2. Right-click the downloaded file → Run as Administrator.
  3. When the Windows caution screen appears, click More info.
  4. Click Run anyway. Follow the installer prompts.
  5. Done. Your substrate starts the moment you do.

Version 0.8.29 · Free forever · No account required · All data stays on your computer


About Liana Banyan

Liana Banyan is the Capitalist Cooperative. We do it fairly, for the benefit of all. For it rains on the just and the unjust.

Liana Banyan Corporation — the cooperative-class substrate behind MnemosyneC and 16 cooperative initiatives.

83.3% of every dollar stays with the Workers, Builders, and Creators that make it. $5 a year. One vote. Everything we build is published under a Cooperative Defensive Patent Pledge so members — and any community on Earth — can fork it, run it, and keep it.

Read the papers that shape the work: How to Save the World in Six Easy Steps · A Considered Approach to Universal Sustained Economic Prosperity · No Atomo. Superman! · The Invisible Tax

Read the Cooperative Compact →  ·  Browse initiatives →  ·  Join for $5/year →  ·  The Court →

Caithedral™ · Substrate · Plow · Stone Tablets · Shadow E-Giants · Cooperative-class · For the keep.

How will you use MnemosyneC?

Choose your license track. Most users want Personal.