Self-HostedAIDeploymentGuide

Self-hosting AI systems gives you control over your data, your costs, and your uptime. But it also means taking responsibility for hardware provisioning, software configuration, security hardening, and ongoing maintenance. This guide walks you through each consideration with practical recommendations based on real deployments in African infrastructure environments.

Deployment considerations include selecting appropriate GPU or CPU-based hardware for your workload, choosing between containerized and bare-metal deployments, configuring network security for AI inference endpoints, implementing monitoring and alerting for production models, and planning for capacity scaling as usage grows.

This resource covers the complete deployment lifecycle - from initial requirements gathering through production operation - with specific guidance for organizations operating in environments with limited connectivity, variable power, and constrained budgets. The full guide is in development. Contact our infrastructure team for hands-on deployment support in the meantime.