Air-Gapped Workflows and Threat Posture Air-gapped AI is usually described as a location: a machine that is not connected to the internet. When systems hit production, air-gapping is a workflow, a set of controls, and a discipline around how information and software move. The moment a USB drive, a service laptop, a shared build server, […]

Data Governance for Local Corpora A local model is only as trustworthy as the information it sees. In real deployments, that information is not a single dataset. It is a living corpus: documents, tickets, transcripts, policies, code, runbooks, and the small notes that accumulate around work. Local corpora are powerful because they let an organization […]

Licensing Considerations and Compatibility Local AI looks like a technical decision until distribution begins. The moment a model is shipped to employees, customers, partners, or devices outside a controlled lab, licensing becomes operational. It affects what can be deployed, what can be resold, what can be modified, what can be combined with other components, and […]

Secrets Management and Credential Hygiene for Local AI Tools Local AI feels “close to the metal” because it runs on your own hardware, but the moment it connects to anything useful, it becomes a credentialed system. A desktop assistant that can read your notes, search your files, open tickets, send email, or hit an internal […]

Update Strategies and Patch Discipline Local AI deployments feel deceptively simple at the start. A model runs on a machine, a UI calls an API, and the workflow works. Then the real world arrives: drivers change, runtimes update, dependencies shift, model weights are replaced, and performance changes in ways that are difficult to explain. Patch […]