The case for local AI processing
The dominant story in AI has been that bigger is better: more parameters, more data centres, capability that necessarily lives somewhere else. That story is still mostly right about frontier models, and increasingly wrong about everything else.
What centralised AI costs
Cloud inference has delivered genuinely remarkable capability. It also carries costs that are hard to design around. Latency that makes interactive work feel sluggish. Data residency rules that rule out whole sectors. And a structural tension: the more capable the service, the more of your context it wants, and the less say you have in where that context ends up.
For regulated work, that last point is not a preference. A solicitor pasting a contract into a hosted model has disclosed personal data to a processor they may never have assessed.
Local is a different shape, not a smaller one
On-device inference is not cloud inference with the numbers turned down. It is a different set of trade-offs. A model on your laptop already has your context without uploading it. It answers without a round trip. It works on a plane, in a secure facility, and on a network you do not trust.
The hardware moved. Apple Silicon in particular made quantised transformer inference practical on a machine someone already owns, which is why Velum's desktop app ships for Apple Silicon and bundles its default model rather than calling out to anything.
Not everything belongs on-device. A frontier model answering a hard question is doing something a laptop cannot. The useful division is not cloud versus local, it is deciding which half of the work touches data that should not travel. Detection and masking are exactly that half.
What it changes for builders
Bundling a model instead of calling an API changes the shape of the problem. You trade rate limits and per-request pricing for install size and memory. Velum's macOS download is around 318MB, and most of that is the detection model sitting inside it. That is the honest cost of not phoning home, and we would rather pay it in bytes than in disclosures.
It also changes what you can promise. "We do not send your text anywhere" is a claim someone can verify with a network monitor in about a minute. Very few cloud products can offer a customer a test that decisive.
Where Velum actually is
Update, August 2026: Velum for Linux has since shipped, and the extension is now on Firefox as well as Chrome. Windows is still in development. The paragraph below reflects the product when this piece was published.
The macOS app runs on Apple Silicon. The browser extension works on Chrome and Chromium, through a popup you paste into, with an optional in-page button for ChatGPT, Claude and Gemini. The Atlassian app for Jira and Confluence is live on the Marketplace. Windows and Linux are not shipped, and we are not going to pretend otherwise while people are deciding whether to wait.
Both shipping apps run for seven days with no account and no card.
The next generation of tools handling sensitive work will not ask you to trust a remote server. They will show you there is nothing to trust.