QVAC vs Private AI Assistants: The Engine vs the Products
QVAC vs private AI assistants: many claim privacy, few actually run on your device. Here's how to tell the real ones apart.
A lot of products now market themselves as "private AI assistants" — chat tools that promise not to train on your data, to encrypt it, or to keep it anonymous. That's a meaningful improvement over the default. But most of them still run in the cloud, which means privacy is a promise about what a server does rather than the absence of a server. QVAC is the second kind: there's no server to make promises about.
This is a slightly unusual comparison because they're not the same category — one is an engine, the others are end products — but the privacy distinction is worth spelling out.
The one-line difference
Private AI assistants are (usually cloud) chat products that add privacy protections on top of a server-based service. QVAC is an on-device SDK where inference happens locally, so there's no server involved and nothing leaves the device in the first place.
Two very different kinds of "private"
Policy-level privacy. Many private assistants still send your prompts to a data center; they just promise good behavior once the data arrives — no training on it, encryption in transit, anonymization, short retention. This is genuinely better than the careless default, and for many people it's enough. But it rests on trust: you're trusting a policy, an implementation, and a company that could change any of them, and on data that did leave your device.
Architecture-level privacy. With QVAC, the prompt never leaves the device, because the model runs on the device. There's no server to log it, no policy to trust, nothing to breach, nothing to subpoena. Privacy isn't a promise about a server's behavior — it's the fact that there's no server. This is a stronger guarantee, bounded by device hardware rather than a company's good intentions.
Side by side
| QVAC (on-device) | Typical private AI assistant | |
|---|---|---|
| Where inference runs | On your device | Usually the cloud |
| Data leaves the device? | No | Usually yes |
| Privacy comes from | No server exists | Server policies + encryption |
| Works offline? | Yes | Usually no |
| Trust model | Structural (auditable, open-source) | Promissory (policy-based) |
| Capability ceiling | Device-bounded | Can use frontier cloud models |
Where private AI assistants are the stronger choice
If you want a ready-made, general-purpose assistant today and are comfortable with policy-level privacy, these products are convenient and often use very capable frontier models you couldn't run locally. For non-sensitive questions where you just want a good answer and a company you trust to handle data responsibly, they're a reasonable pick — and clearly better than assistants with no privacy stance at all.
Where QVAC is the stronger choice
QVAC isn't an assistant you use — it's what you'd build a truly private assistant on. If you're a developer who wants the strongest possible privacy guarantee for your users — no server, no data leaving the device, auditable open-source engine — QVAC gives you that foundation across platforms. The privacy isn't marketing; it's the architecture.
The honest trade-off
Private assistants trade architectural privacy for frontier capability and ready-made convenience, backed by policies you have to trust. QVAC trades some capability ceiling for a privacy guarantee that doesn't depend on trusting anyone, because there's no server in the loop.
We're building the second kind. Our apps won't ask you to trust a privacy policy — they'll run the AI on your device so there's no policy to trust. That's only possible because QVAC makes on-device the default, not a premium tier. Here's how it works, and what we built on it.
Note: specific assistants differ in how much they run on-device vs in the cloud; check each product's current architecture before relying on its privacy claims.