360 Technology

AI agents

Designing AI Agents Around Real Enterprise Workflows

How leaders can move agentic AI from demos to governed work across systems, teams, and measurable outcomes.

Start with accountable work

The right starting point is a workflow with measurable volume, cycle time, quality gaps, or customer friction. Define what the agent can draft, decide, recommend, route, or execute before choosing tools.

Connect agents to controls

Agentic systems need identity, permissions, source data, audit trails, exception handling, and human approval paths that match the risk of each action.

Scale through operating patterns

Reusable orchestration, prompt evaluation, tool-access policies, monitoring, and support playbooks help teams move from one useful agent to a managed portfolio.

Leadership actions

What to do next.

Map high-friction workflows
Define agent authority and escalation
Measure cycle time, quality, adoption, and risk

Let us build what is next

Turn insight into an executable roadmap.

Talk with 360 Technology about the platforms, teams, and operating model your transformation needs next.