The right memory, at the right time, no duplicates, no hidden data leakage, no surprises. An architecture you can inspect.
VEKTOR is self-funded, built by an independent developer with 30 years across computing, IT, data networking, storage, cybersecurity, and telecom. Memory for AI agents that centralize a person's most private conversational history locally with privacy by design. This page exists to show the alternative, and to make its guarantees proof you can check yourself rather than something we simply ask you to believe.
Four properties of the same system, each one verifiable, not asserted.
PET isn't a promise VEKTOR makes and asks you to trust; it's a property of the architecture itself. Embeddings are computed in-process, on your device, with a local ONNX model. There is no cloud copy of your memory.
Two kinds of transparency, and most companies only give you one. VEKTOR's architecture is published, not proprietary-black-box; its pricing is flat, not metered.
Data sovereignty usually costs you convenience: self-hosting, manual backups, DIY migration. VEKTOR's bet is that it shouldn't have to.
AUDN (Add / Update / Delete / None) fires before every write, so contradiction handling is structural, not a cleanup job run later. Speed is part of that same quality bar, not a separate feature.
"Will my agent still feel instant once its memory has months of history in it?"
Speed
Yes. ~28ms average recall locally, in-process execution with no network round-trip, staying flat as history grows.
"Who can access my data, where does it live, and can I get it out again?"
Data control & privacy
Only you. Your memory graph is a local SQLite file, air-gapped by design, with no cloud copy to access.
"Will my bill change if I use this more, or is the price the price?"
No hidden costs
The price is the price. One flat subscription, no add-ons, no upsell ladder, no usage-based billing.
"Can I get my data in and out without being locked into one vendor's format?"
Ingress, egress & embedding
Yes. Embeddings are computed locally and your SQLite file is a standard, portable format, not a proprietary lock-in.
"If I switch machines, providers, or tools, does my memory come with me?"
Ease of migration
Yes. Copy the file to any machine; cancel any time and it stays exactly where it is.
"Do I have to trust a claim, or can I actually verify it myself?"
Transparency
Verify it yourself. Architecture, benchmarks, and policies are published, not just asserted.
Six different questions. One answer underneath all of them: control over your own data.
Not an abstract claim: a side-by-side of the same conversation, memory-managed two different ways.
Numbers published on /research and /ecosystem, linked here, not restated, so there's one source of truth.
We're working toward the most private, secure, and fastest agentic memory tooling available built on the best of open and closed software, so your data stays private and secure while staying technology-agnostic across LLM providers.
Every claim on this page links to the actual document behind it.
Architecture, storage model, encryption at rest, and how to report a vulnerability.
What we collect (the complete list), retention periods, and data handling in plain language before the legal text.
Current regulatory status, updated as coverage changes, not a static badge.
The exact list of third-party services involved, and what each one can and can't see.
How we handle and disclose security incidents, and our acknowledgement and remediation timelines.
Live service status, and a direct path to us for security or legal questions.
What gets retained, for how long, and how to export or delete your data.
Every trust-relevant change to the architecture, dated and public.
The commercial terms behind the flat-pricing promise made above.
Our architecture is mathematically proven to protect your privacy.
VEKTOR Memory