AI Agents
See what AI agents can do for your industry or process: the jobs they take on, how each agent runs, and a worked example with sample data.
Direct Answer
AI agents are software given a goal instead of a fixed script: they plan steps, call tools, check the results, and stop or hand off to a person when a decision carries risk. Pick your industry or process below to see what an agent can do, how it runs, and a worked example.
AI Agents for Packing Optimization in Warehousing
This page shows how AI agents plan and execute packing optimization in warehousing, including goal framing, tool calls, result checks, and a worked example of end-to-end execution.
AI Agents for Packing Optimization
Shows how a goal-driven AI agent plans and executes packing optimization tasks, including tool use, result checks, and a concrete worked example from goal to finish.
AI Agents for Partner Settlement in Telecommunications
This page documents how AI agents handle partner settlement in telecommunications, outlining the goal-driven loop, required tools, and a concrete worked example.
AI Agents for Partner Settlement
This page demonstrates goal-driven AI agents for partner settlement, including the run loop, required tools, and a concrete worked example that ends with a human decision point.
AI Agents for Parts Inventory in Automotive
AI agents for parts inventory in automotive show how goal-driven agents manage stock, locate parts, check vendors, and update records while preserving audit trails and human review points.
AI Agents for Parts Inventory
This page shows how AI agents manage parts inventory, from goal to tool calls, checks, and handoff, with a concrete worked example of a complete run.
AI Agents for Parts Obsolescence in Defense and Aerospace
This page shows how an AI agent handles parts obsolescence in defense and aerospace, detailing the loop, tools, and a concrete worked example.
AI Agents for Parts Obsolescence
Defines a goal-driven AI agent for parts obsolescence, detailing goals, tools, loop steps, and a worked example from goal to hand-off.
AI Agents for Passenger Information in Transportation and Mobility
This page shows how an AI passenger information agent plans steps, calls tools, checks results, and stops, with a concrete worked example in transportation and mobility.
AI Agents for Passenger Information
This page shows how AI agents manage passenger information tasks, from goal to action, including planning, tool usage, result checking, and hand-off. It provides a concrete worked example for guidance.
AI Agents for Patch Management in IT Services and MSP
Shows how a goal-driven AI agent handles patch management tasks, tool calls, and result validation in IT services and MSP contexts, with a concrete worked example.
AI Agents for Patch Management
Shows how an AI agent manages patch cycles: goal setting, planning, tool calls, result checks, and hand-off, with a concrete worked example for patch management workflows.
AI Agents for Patient Discharge in Hospitals
AI agents for patient discharge in hospitals demonstrate a goal-driven loop that plans steps, calls clinical tools, checks results, and hands off when criteria are met.
AI Agents for Patient Discharge
A practical reference showing how AI agents manage patient discharge tasks, tool use, and decision handoffs in a goal-driven loop with a concrete worked example.
AI Agents for Patient Engagement in Healthcare
Shows how a goal-driven AI agent handles patient engagement tasks end-to-end, including goal framing, tool calls, result checks, and escalation to humans when needed.
AI Agents for Patient Engagement
A practical reference showing how an AI agent handles patient engagement goals, the tools used, and a concrete worked example from goal to finish.
AI Agents for Patient Flow in Hospitals
A practical reference showing how AI agents manage patient flow in hospitals, including loop, tools, and a concrete worked example from goal to finish.
AI Agents for Patient Flow
This page specifies how AI agents manage patient flow, including goals, planning loops, tools, and a concrete worked example from goal to finish.
AI Agents for Patient Intake in Healthcare
This page shows how AI agents handle patient intake tasks, how the loop runs, and a concrete worked example from goal to finish in a healthcare setting.
AI Agents for Patient Intake
This page shows how an AI agent handles patient intake tasks, plans steps, uses tools, and hands off when needed, with a concrete worked example.
AI Agents for Patient Scheduling in Healthcare
A practical reference showing how AI agents schedule patients, plan actions, call tools, verify results, and hand off when needed in a healthcare setting.
AI Agents for Patient Scheduling
This page shows how an AI agent for patient scheduling pursues goals, plans steps, calls tools, checks results, and finishes or hands off with a concrete worked example.
AI Agents for Payment Operations in Banking
This page explains how payment operations AI agents plan, execute, and adapt workflows within banking systems, with a worked example of a credit card settlement task.
AI Agents for Payment Operations
This page documents how AI agents run in payment operations, including goals, planning, tool calls, checks, and handoffs, plus a concrete worked example showing end-to-end execution.
FAQ
What is an AI agent?
An AI agent is software given a goal rather than a fixed script. It plans steps, calls tools, checks the results, and either finishes or hands off to a person.
What is the difference between an AI agent and AI automation?
AI automation runs a defined process with AI at certain steps. An AI agent chooses its own next step toward a goal, which suits work where the path changes from case to case.
Which AI agent should a business build first?
Start with one narrow goal, read-mostly tool access, and a clear owner. Widen what the agent may do alone only after its logged runs show it can be trusted.