Self-Hosted AI
Self-hosted AI treats deployment as the deciding dimension: running models, apps, or agent platforms on your own servers — weighing data control, cost, and ops burden to judge whether the effort is worthwhile.
Self-hosted AI examines the full trade-off of running AI capabilities on your own servers: data never leaves your network, usage-based bills turn into fixed server costs, while updates, backups, scaling, and incident response become your job. From local model runtimes to open-source knowledge bases to agent platforms, the bar and the payoff vary widely by scenario — readers can judge by data sensitivity, team size, and workload.
