AI agent

An AI agent is an autonomous or semi-autonomous system built around an AI model that can perceive context, reason about a goal, and act to achieve it. Unlike a simple chatbot that maps inputs to scripted replies, an agent can interpret intent, plan a sequence of steps, call tools or APIs, and adapt based on the results it gets back.

In practice, the defining trait of an agent is the ability to take action, not just produce text. A customer support agent might read a question, look up an order in a backend system, check a return policy, issue a refund, and then summarize what it did, all within one conversation. That tool use and multi-step reasoning is what separates an agent from a pure question-answering bot.

Modern AI agents are typically built on large language models, augmented with grounding (so answers reflect real information), tool or function calling (so they can act in external systems), memory (so they keep context across a conversation), and guardrails (so they stay within allowed behavior). These components let an agent handle open-ended, varied requests rather than only the paths someone anticipated in advance.

Because agents act in the real world, they need clear boundaries: which actions they're permitted to take, when they should ask for confirmation, and when they should escalate to a person. Good agent design treats human handoff as a feature, routing complex, sensitive, or low-confidence cases to a human with full context rather than forcing an automated resolution.

Mercateer's AI support agents follow exactly this model: they understand intent, ground answers in your knowledge, take real actions in the conversation like order lookups and refunds, and hand off cleanly to your team when a human is the right call, resolving questions instead of just replying to them.