Self-Hosted AI Agent Architecture
How host control, container execution, credentials, memory, tools, and channels fit together.
Read the architecture guide →Technical insights
These articles explain the decisions behind self-hosted agent infrastructure, multi-agent review loops, memory boundaries, tool use, and reliable workflow delivery.
How host control, container execution, credentials, memory, tools, and channels fit together.
Read the architecture guide →How planners, workers, reviewers, synthesis, gates, and retries create an auditable workflow.
Read the orchestration guide →See how these architectural principles appear in a public TypeScript project.
Review project evidence →Engineering services
Each service page describes a distinct delivery scope with public project evidence, technical boundaries, and a clear handoff path.
Workflow automation across CRM, email, calendars, reporting, lead response, and business APIs.
Explore AI automation →Tool-using agents with memory, approvals, multi-step execution, and failure handling.
Explore AI agent development →Client-owned runtimes with Docker isolation, host-side secrets, storage, and monitoring.
Explore self-hosted AI →OpenClaw and Hermes-Agent deployment, hardening, skills, integrations, and migration.
Explore OpenClaw development →Project-based AI agent and automation delivery for distributed teams worldwide.
Explore remote delivery →Review the architecture and public repository behind Mark’s self-hosted agent work.
Review the case study →Available for remote builds
I’ll help identify whether it needs an AI agent, deterministic automation, an OpenClaw deployment, a custom integration, or a simpler system.
Email Mark Carmona →