An AI chatbot is best understood as a conversation interface; an AI Agent is often described by the goals or tasks it can help complete. These ideas overlap: an Agent can talk through a chat window, and a chatbot can be connected to tools. The useful question is not which label sounds more advanced, but what your system is allowed and able to do after someone asks for help.
Use the same customer request to compare three designs: information-only, connected to an action system, and completed only after a person approves it. The example is hypothetical. It is a way to reason about system design, not a LoopReply turnkey integration.
Separate the interface from the capability
A chatbot describes how a person interacts with software: they send a message and receive a response. That description alone does not tell you whether the software can look up information, change a record, or hand a task to a person.
An Agent label usually signals that the system is intended to pursue a goal, perhaps by gathering information, following steps, or using a tool. But the label does not prove which tools are connected, what permissions they have, or whether the system can act without approval. Some Agents only assist with a task; some systems called chatbots can use tools. Avoid choosing on terminology alone.
When evaluating a setup, ask four questions:
- What is the visitor trying to get done?
- What information must the system access to help?
- Is it allowed to change anything, or only explain and prepare?
- Who checks the result, and what happens when the request is outside scope?
The answers define the practical difference for your business. For a broader business-planning discussion, see AI Agents for Business: Use Cases and Setup.
Compare three versions of one request
Imagine a customer writes: “Please change the delivery address for my order to 18 Oak Street.” This is a hypothetical example. It does not assume that any particular product has an order-system connection.
1. Information-only
The system can explain how customers request an address change, using your published policy. It cannot look up this customer’s order or change its address. A suitable reply might be: “I can explain the steps, but I can’t update your order here. Please use the order-support form before dispatch.”
This can still be a useful chatbot. It handles an information task, sets a clear boundary, and points the customer to the next step. Do not describe it as completing an order change. If the policy is vague about when a change is possible, clarify the source or route the question to a person rather than inventing a rule.
2. Connected to an action system
In a hypothetical API-enabled design, the system could first verify that the customer is authorized, find the relevant order, check whether its status permits an address change, and submit the update through an approved connection. The response should confirm only what the system can verify. If the order is already dispatched, the customer identity cannot be checked, or the connection returns an error, the system should stop and explain the next available route.
This is a goal-and-action design, but it is not automatically autonomous in every sense. You decide which steps can run without approval, which require checks, and where a person must take over. A connection to a source of information is not necessarily permission to write to that source.
For LoopReply specifically, LoopReply’s database connector supports PostgreSQL and MySQL with a validated read-only SELECT query. A synced knowledge dataset is not proof of a live database lookup for each visitor question. Those distinctions matter when planning: a read-only query or indexed dataset should not be presented as an order-update capability. Likewise, An embed does not itself connect order data, a CRM, or other business systems. The hypothetical API workflow above is a conceptual comparison, not a claim that LoopReply supplies a ready-made order integration. See the product facts when checking supported capabilities.
3. Prepared for human approval
A third design can gather the customer’s request and relevant details, then ask an authorized team member to review and make the change. The customer-facing message might say: “I’ve sent this request for review. The address has not been changed yet.” That wording distinguishes a submitted request from a completed action.
Human approval can be appropriate when changes have consequences, the rules are unclear, or a person needs to verify the request. Decide what the Agent may collect, what it may summarize, and what only a staff member may authorize. In LoopReply, Authorized Workspace members can take over a conversation and reply as a human. Waiting or human-takeover conversations do not receive an AI response from the widget. Handover is a route for help, not a promise about when a reply will arrive. The human handover feature provides product information about this route.
Use this worksheet to choose a design
Write one row for each task you want the system to handle. Keep the task specific: “explain the address-change deadline” is different from “change the address on a particular order.” Fill in the fields before deciding whether a chatbot, an Agent, or a combination is the right fit.
| Worksheet field | Example for an address change |
|---|---|
| Customer’s goal | Change the delivery address on an order |
| Information needed | Order status, customer identity, requested address |
| Information source | Approved order system or, for information-only help, the written policy |
| Allowed outcome | Explain steps; prepare a request; or submit a permitted change |
| Approval rule | State whether a team member must approve the update |
| Stop condition | Identity cannot be verified, order is ineligible, or the system reports an error |
| Customer confirmation | Say whether the change is completed, awaiting review, or not available |
Now choose the least complex design that genuinely meets the goal. If visitors mainly need to understand a policy, information-only may be enough. If the task requires looking up or changing a record, list the required connection, access permissions, identity checks, and failure route before calling it an Agent action. If a person must authorize the change, make that approval explicit in the customer’s experience.
For each row, prepare one test question that should be handled and one that should stop or be referred. For example, test a request that lacks an order number and one that concerns an order already dispatched. Write the expected boundary before reviewing the response. This is practical advice for checking your own setup, not a claim that a particular system will pass those tests. If you are building the conversation steps, review the workflow builder information.
Make the choice by outcome, not label
Choose based on the task and its permissions. A chatbot can be a good fit for answering from approved information. A tool-connected design may support specific lookups or actions if the required connection and permissions are actually in place. A human-approved design can help organize a request while keeping the final decision with your team.
Before launch, make sure your customer-facing wording matches the real outcome. “Here are the steps,” “I’ve sent this for review,” and “Your address has been changed” mean different things. Use the last only when the action was completed and the system can confirm it. The distinction between chatbot and Agent is useful as a starting point; the task, access, approval, and confirmation rules are what make the choice concrete.
Trace one request through the system
Consider this illustrative request: “Can you change my delivery address?” A scripted chatbot can offer a menu with an address-change option. A knowledge-backed AI answer can explain the published process. An action-capable Agent needs a verified customer, an eligible order, and a working update operation before it can confirm a change.
The observable result is different at each stage: selected menu item, source-backed instructions, or confirmed operation. Save those as separate acceptance criteria. The website chatbot shortlist compares operating approaches; the business task guide helps choose which stage to build first.