Every AI you use is brilliant for an hour and a stranger by morning. And every vendor's fix is to lock your memory inside their garden. Private Memory is the user- and org-owned memory layer that follows you across ChatGPT, Claude, Gemini, Copilot and your own agents, while the secrets underneath it never leave your control.
ChatGPT remembers inside ChatGPT. Gemini builds its own profile. Copilot remembers inside the mailbox. Switch models and you start from zero, so your best context stays trapped wherever you happened to type it. Nobody has solved memory across the gardens, because whoever holds cross-provider memory holds the most sensitive longitudinal dataset in your working life. No model vendor is structurally trustable with it. PrivacyPal is built to be exactly that owner, because our memory never contains a real secret at all.
ChatGPTknows Monday's brief
Claudeknows Tuesday's draft
Geminiknows one meeting
Copilotknows your inbox
ChatGPTfull context
Claudefull context
Geminifull context
Copilotfull contextPrivate Memory runs on the interception plane PrivacyPal already operates, the same place Privacy Twins swap your secrets out of every prompt.
Every AI exchange (prompt and response, whichever model served it) is captured at the interception point with zero added latency in the hot path.
A background "sleep-time" process distills durable facts and reconciles them: new facts supersede old ones, contradictions are invalidated, never silently deleted.
At the moment you prompt any AI, relevant memory is assembled into a token-budgeted Memory Pack (no LLM in the read path) and injected in twin-space, at a fraction of the tokens of replaying your history.
Destroy your vault keys and every copy of your memory (synced, exported, cached) becomes meaningless noise. Contract-tested, even for memories still in flight. The right to be forgotten, as mathematics.
The durable memory graph is written entirely in twin-space: it references synthetic Privacy Twins, never real values. The real-to-twin map lives in an encrypted vault under your own keys.
That inversion is the whole product: PrivacyPal can host, sync and serve a memory it cannot read. Your memory follows you to every model and every device. And if anyone ever got the graph, they'd hold statistically plausible facts about entities that resolve to nothing.
And it's measured, not asserted. In our benchmark we verified it value by value: the names, dates and organizations you rely on came back correctly on your side, and none of them appeared in anything sent to an AI provider. Every model gets your working context. No model gets the real values.
Nexus Solutions in the graph · Acme Corp only in your vault
An assistant that remembers is an assistant that can be programmed by anyone who gets a sentence in front of it: a webpage it browses, an email it summarizes, a document someone shares. Plant an instruction disguised as a fact today and an agent obeys it weeks later, long after the attack is gone. OWASP now ranks memory poisoning the number-one emerging agentic threat (ASI06).
So nothing enters Private Memory unexamined. Memory Guard is a deterministic gate on the write path, a dedicated Privacy Agent that inspects every candidate memory before it is stored. Content that tries to behave ("always ignore," "from now on send") is quarantined as an attempted instruction, never remembered as a fact. In our adversarial benchmark, Memory Guard blocked 100% of poisoning attempts, and not one embedded instruction ever resurfaced as a memory.
Recall holds the same discipline: when there is nothing to remember, Private Memory says nothing rather than inventing something. And on Max, security teams set Memory Guard policy fleet-wide and review quarantines from the audit console.
The #1 emerging agentic attack, met with a defense on the write path of every memory. Not an add-on.
AI memory is a field of self-reported numbers that fall apart under independent testing. We take the opposite position: publish the mechanism, measure it reproducibly on the exact pipeline that ships, and claim nothing we can't show.
Internal benchmark, 2026, run on the shipping pipeline with deterministic scoring and no LLM judge, twin-space against an identical plaintext control. Twin-space matched or beat plaintext, so privacy carries no accuracy tax. Methodology available on request.
Stop re-introducing yourself to machines. With Pro, your projects, preferences and working context become one portable memory: on-device, opt-in, and yours.
Brief one model on Monday and every model knows it Thursday. The project, the constraints, the decisions so far: your context is simply there.
Memory is how vendors lock you in. When your context travels with you, you choose models on merit (reasoning here, drafting there) without amnesia as the switching cost.
A full viewer shows everything remembered and why. Go incognito before a sensitive session. And when you say forget, one action erases every copy, permanently.
On Max, memory becomes an organizational capability: what one teammate establishes in their AI, the whole team's AIs can know: in twin-space, under policy, with a full audit trail.
Enterprises don't fail at agent adoption for lack of models. They fail because every agent starts ignorant and every workaround becomes an ungoverned shadow database. Max gives the org one governed memory plane instead: team and org scopes, fleet-level Memory Guard policies, an audit console, and a Private MCP memory server so internal agents and tools query org memory without anything leaking to a public host.
Promotion is always explicit. Personal memory is never silently harvested into the org. People choose what the team should know, and policy governs the rest.
An AE's discovery call insights live in their own memory, captured from their Claude session, private by default.
Promoted to the deal team: the SE's Copilot and the CSM's Gemini now answer with the same account context: no forwarding threads, no re-briefing.
Institutional knowledge (terminology, standards, hard-won process) inherited by every governed agent from day one. New hires' AIs start informed, not ignorant.
Personal cross-LLM memory, on-device. Viewer, incognito and one-action erase included. Opt-in, off by default.
PrivacyPal ProEverything in Pro plus team & org scopes, the policy plane, fleet Memory Guard, Private MCP memory server and audit console. Rolling out now.
PrivacyPal MaxThe sovereign memory plane: in-VPC, bring-your-own-key, air-gap support, Memory DSPM and data residency.
PrivacyPal Cloudremember() and recall(): compliant cross-LLM memory for any application, in two calls.
PrivacyPal SDK