A lean agentic AI installation and managed-services shop for teams that need practical automation inside real workflows.

Arbiter is led by Daniel Evans, a Detroit-based analyst and builder with a background in equity research, financial modeling, risk assessment, data analytics, and practical AI-agent operations.
The work starts with a simple idea: AI systems only matter when they survive real workflows. Arbiter exists to install useful agent stacks, connect them to the work, and keep them stable after launch.
If you have a workflow that should be supported by agents, send the use case, constraints, and what success would look like. No customer names required.