We built this for ourselves.
Every AI conversation starts from zero. Claude doesn't remember your architecture decisions from last month. GPT forgets your preferences the moment the session ends. We hit this wall building software with AI agents — and decided to fix it.
Context that took an hour to establish would vanish overnight. The AI we were directing was brilliant in the moment and amnesiac by morning. So we built Parametric Memory — not as a product first, but as infrastructure for ourselves.
It worked. Claude started remembering. Decisions made in March applied correctly in April. Corrections stuck. The relationship deepened. After months of running our entire development operation on it, we knew: this is the missing layer. And it's missing for everyone.
What it is
Parametric Memory is a persistent, cryptographically verifiable memory substrate for AI agents. That's a sentence worth unpacking.
Your AI's memory survives between sessions. When you start a new conversation, your agent bootstraps — loading relevant context, past decisions, corrections you've made, and a prediction of what it'll need to know today. You don't re-explain. You continue.
Every memory has a Merkle proof. Not “we promise your data is intact.” Mathematical evidence it hasn’t been tampered with or quietly replaced. You can verify the integrity of any atom at any time. That’s not how other memory tools work. That’s how we believe they should.
We run alongside your existing setup — a dedicated layer your AI connects to over MCP, the protocol that Claude, GPT, and every major AI platform is converging on. One config line. Your agent has memory in 60 seconds.
How it's different
Most competitors give you a vector database and call it memory. Similarity search finds what's related — useful, but not enough. Memory is also true, corrected, structured, and anticipatory.
Facts, procedures, corrections, events, relations. Not undifferentiated text blobs. A correction is stored as a constraint — it comes back as a rule, not a suggestion.
Every bootstrap learns from every prior session. Over time, the system predicts what context you'll need before you ask. 64% hit rate and rising.
Atoms connect to each other. Decisions link to the facts that drove them. Corrections constrain the behaviours they fixed. Included at every tier — not a $249/mo upgrade.
Every atom, every write, every state transition has a cryptographic proof. You own your memory — and you can prove it.
The architecture choice we're proud of
When we designed MMPM, the easy path was multi-tenancy. One database, all customers, shared compute. Cheaper to run, faster to build — standard SaaS playbook.
We didn't do it.
AI memory contains the most intimate data an AI system produces: your thought patterns, your corrections, your architecture decisions, your business logic. A multi-tenant memory store is a single bug away from catastrophic data breach — one customer's context leaking into another's.
Every customer gets their own substrate.
Their own PostgreSQL instance. Their own Merkle tree with its own root hash. Their own container pair with its own API key. Isolation by architecture, not by policy. It costs more to operate. We think it's the only defensible choice for a product selling memory.
How we built it
One founder. A fleet of AI agents. Zero employees. Sixty days.
Every line of code was written in collaboration with Claude. Architecture decisions made together, reviewed together, tested together. The sprint plan, the API contracts, the security review — all of it was a dialogue between human judgment and AI execution.
We don't think this is a party trick. We think it's the future of software. And we operate the same way we sell.
“We don't just sell you a second brain — we trust it with ours.”
Our internal operations — every health check, every billing event, every customer signup — is a Merkle-sealed atom in our own MMPM substrate. The morning briefing agent reads last night's ops atoms and surfaces anything that needs attention. The security review agent runs weekly. We built a second brain for our AI, then built a company on top of it.
How it works for us
The platform that runs itself
Every operational event — signups, billing, health checks, security alerts — flows into our own MMPM substrate as a Merkle-sealed atom. AI agents read that substrate to produce briefings, surface anomalies, and generate intelligence. The same system we sell runs the company that builds it.
The same architecture available to every customer — we just happen to use it on ourselves.
Who it's for
Building systems where AI agents need to remember state, decisions, and corrections across sessions. Stop embedding context in every prompt. Let the agent remember.
Running AI-powered workflows where consistency and auditability matter. Every memory has a proof. Every correction sticks. Every decision is traceable.
Using Claude, GPT, or any MCP-compatible AI who want their AI to actually know them — their preferences, their projects, their rules. Not from a pasted document. From memory.
Your AI has been waiting to remember you.
14-day free trial. No credit card required.
Parametric Memory is built and operated by Entity One, from New Zealand.