Private AI

Use AI without giving every workflow to a third party.

Private AI is an operating choice: decide where a model runs, which data may leave a device, and who controls the surrounding policy. Glyph gives individuals and teams a local-first workspace while leaving the destination visible and selectable.

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What private AI changes

A private workflow reduces unnecessary disclosure by running suitable models on hardware you control. It also makes the exceptions explicit. If someone selects an external provider, that destination has its own data handling terms; local execution and cloud execution should never be described as the same boundary.

A practical control model

Start with the data, choose an approved model destination, and apply policy before content leaves the device. Glyph supports local models and customer-controlled deployments, while enterprise controls can restrict destinations and record security metadata without placing prompt or document text into analytics labels.

Where to begin

Individuals can download Glyph and run compatible local models. Organizations can scope a pilot around a small group, a defined set of data, and an approved model server before expanding. Review the trust material and deployment options with the people who own identity, endpoints, and data policy.