Product

Your company's memory. Owned, not rented.

Mnemma is a company brain you own — running in your own environment, never our cloud. Own it. Compound it. Trust every answer; every important fact carries a receipt.

Own it This is the CEO's driver — the company finally knows what it knows →

The brain is yours — and it stays.

Problem 04 · Sovereignty vs. capability

Stop choosing between safe and capable.

Today, companies with the most valuable knowledge face a choice: hand it to a cloud AI vendor, or stay safe and fall behind. Mnemma runs in your environment, gated and locked down, and still reaches frontier-class intelligence through escalation paths you approve. Private by default, capable by design — and nothing you know accumulating in a vendor's product that your competitors can rent.

Problem 06 · Knowledge that walks out

Make institutional memory an asset, not a retention risk.

What your company knows is scattered across twenty tools and a few people's heads — and when they leave, it leaves. The census pulls the decisions, assumptions, and hard-won lessons into one owned map; the daily loop is designed to keep capturing it. Twenty years of know-how stops being one exit interview away from gone.

Problem 05 · Vendor lock-in

Buy the best new system every time; keep everything you've learned.

Models improve monthly. Tools turn over yearly. Mnemma's asset is the brain, not the model — models, tools, and harnesses are swappable by design. Your accumulated knowledge stays in your own graph, as a Markdown projection and an export you already hold. You're never betting the company on one vendor's roadmap.

What it means

It's an asset on your balance sheet, not a subscription on someone else's.

The knowledge graph, its receipts, and its access rules live in infrastructure you control. You can point any tool at it, move it between deployment models, or export it wholesale. It's yours. Cancel us tomorrow and the map stays.

Compound it This is the CFO's & CTO's driver — spend becomes an asset →

AI spend stops being rent.

Problem 01 · Every tool starts from zero

Every tool you buy starts already knowing the company.

Today, each AI tool re-learns your business on every query. It re-explores the documents, re-derives the context, and pays the "get-to-know-me" token tax again — per tool, per vendor, forever. On Mnemma, that work happens once, in an asset you own. Any model, any future agent starts knowing the company and pays only for the new thinking.

Problem 02 · Answers die in chat logs

What your AI learns is designed to write back into what you own.

Query results that confirm, contradict, or establish a fact are designed to write receipted updates back into your graph — under its access rules, with provenance. Receipt · what we claim and what we don't On the recordVerified, receipted work is designed to write back into a map you keep, even if you cancel. No amortization schedule and no ROI dollar figure is claimed.

The overnight brief speaks five states. Corrections must survive the run.

A brief that cannot say what changed is a newsletter. Ours classifies every material line against the map you already own:

new — not on the map before changed — same entity, different value confirmed — source agrees with memory contradicted — source disagrees with memory old — still true, not news

A human correction is a first-class write, not a chat aside. If it does not survive the next run, it was never a correction. Receipt On the recordA correction that does not survive the next run was never a correction VocabularyThe brief names five states: new, changed, confirmed, contradicted, old

The machinery underneath — the graph, the ontology, the model slots — stays invisible. You get outcomes: knowledge you own, answers you can trust, and spend that is designed to compound.

Trust it The unmatched claim — and the CISO's driver. Govern once, on the data itself →

Act on answers without re-researching them.

Problem 03 · Unverifiable answers

Every important claim carries its receipt.

Where it came from, when, at what confidence — and the system re-checks facts on a schedule so stale ones get caught. Receipt On the recordEvery important fact carries source, date, confidence, and last-checked Re-checkFacts are re-checked on a schedule set by how critical their freshness is If nobody can verify an answer, they must re-research it before they act — which erases the time it saved. Trust the answer, or audit it in one click. Either way, no re-research loop.

Problem 07 · Governance per tool

Buy any AI tool next year without a new security review.

Today each AI purchase triggers a fresh "what can this thing see?" — configured per tool, wrong per tool, forgotten per tool. In Mnemma, the classification lives on the knowledge itself (container-based, default-closed). Every tool that connects — today's and next year's — inherits those rules mechanically. Govern once; everything downstream obeys.

Why one adjudicator

Independent crews amplify their own errors. A supervisor contains them.

A published wiring study held prompts, tools, and compute fixed and moved only how agents were connected. Independent crews amplified errors 17.2× versus a single agent; a centralized supervisor held that amplification to 4.4×. Receipt · not our measurement On the recordA published wiring study held prompts, tools, and compute fixed and moved only how agents were connected. Independent crews amplified errors 17.2× versus a single agent; a centralized supervisor held that amplification to 4.4×. What we takeThe builder is never the judge. Papers appear there as evidence, not as Mnemma benchmarks.

That is why Mnemma does not run a debating crew over your knowledge. Extractors propose. One adjudicator commits. The brief can be wrong in public, with a receipt — it cannot quietly vote itself into the map.

See it measured against your own data estate.

Seven questions, a published formula, a planning band. If the numbers are low, we find out in week one of the paid engagement — then you reprice, shrink, or walk.

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