How an AI agent differs from a chatbot
Both reply to the client in a messenger, and from the outside they look the same. The difference shows up on the very first question that wasn't in the script. Here's a plain look at the substance, no marketing.
A script knows the questions. An agent knows the goal
A scripted chatbot is built like a tree: every client message has a branch prepared for it. As long as the person follows the branches, everything looks reasonable. Ask the wrong thing, and the bot replies "I didn't understand" or offers to start over.
An AI agent works differently. It isn't given a script but a goal: find out what the client needs and book a call. It decides how to get there as the conversation unfolds. So a question nobody planned for isn't a dead end for it, just an ordinary reply.
The difference shows up in a simple line. The client writes: "What if we have two warehouses and our own delivery, can you handle that?" A scripted bot searches its tree for a branch about warehouses and finds none. The agent answers on point and asks for whatever is missing to work out the numbers.
Free text versus buttons
Scripted bots almost always reduce the conversation to buttons. That's not developer laziness but necessity: a button keeps the person inside the planned branch, while free text takes them out of it.
Clients feel it. Someone who wrote to a live rep and got buttons back realises they're talking to a machine, and starts choosing words to fit the program instead of explaining their actual need.
The agent reads what's written as it is: with typos, abbreviations, two questions in one sentence. You can reply to it the same way you would to a person.
Memory of the conversation
A scripted bot lives in a single message. It remembers which branch it's on, but not what was discussed yesterday or what the client has already said about themselves.
The agent keeps the history. If someone wrote about warehouses a week ago and today asks about deadlines, the reply will take the warehouses into account. The customer doesn't have to repeat themselves — and that's exactly where people tend to drop off.
Voice, photos, and everything people actually write with
People send voice messages. They send a photo of the space instead of a description. A scripted bot responds by asking them to type it out instead.
The agent recognizes voice messages and understands what's in a photo. For the customer, this is the difference between "I got a reply" and "I was asked to redo it".
What happens with a hot lead
A scripted bot walks the person to the end of the branch and hands the manager whatever it collected: name, phone number, the menu item chosen. The manager starts the conversation from scratch.
The agent hands over a ready customer along with the substance of the conversation: what they need, what terms matter, where they're hesitating. The manager steps in where the decision is almost made already, and talks about the deal itself instead of filling out a questionnaire.
This is the very boundary the whole thing is built around: the program brings a person to the conversation, then a live salesperson takes over. More on this — in the description of the sales robot.
Where a scripted bot still makes sense
A script isn't useless. Where the client's path is genuinely fixed and no questions come up, a branching tree is cheaper and more predictable. Booking a free slot at a hairdresser's is a job for buttons.
The difference shows up once the conversation stops being a questionnaire: when the client has conditions, doubts, and a situation of their own. In sales of complex services, that's almost always the case.
What the agent does not do
The agent doesn't replace the salesperson. It takes on what surrounds the sale: the first reply, clarifying questions, scheduling, updating the CRM record. The sale itself — a conversation with a person — remains with the person.
It also doesn't make things up. The agent replies based on what it's been given about your business, and in an unfamiliar situation it hands the customer over to a live employee instead of making up something plausible.
Where the agent's knowledge of your business comes from
On its own, the agent knows nothing about your company. Its knowledge is whatever has been put into it: services, terms, common objections, what not to promise. Without that, it will answer in generic phrases, and the client will notice right away.
So the rollout starts not with the software, but with an analysis: what questions clients ask, what managers reply, where the conversation most often breaks down. This is what the agent's answers are built on.
A separate boundary is set: what the agent never states on its own. Deadlines, discounts, promises of results — anything a person needs to decide, the agent doesn't decide.
How the agent is tested before it goes live with clients
We don't release the program to real people on faith. We test it on past correspondence: we take conversations where the customer asked a question and ask the agent to reply, without showing it what the live manager answered.
Then both answers are compared blind, so the reviewer doesn't know which is which. On our current project, 80% of the time the program's answer turned out no worse than the human's. The remaining cases were analysed and turned into rules.
This is the only honest way to find out whether the agent is ready to talk to customers. Everything else is an impression from a demo shown on convenient examples.
How to work out what you need
A useful check is to look at what clients actually write to you. If they ask questions that aren't in any prepared list, a scripted bot will lose them. If everyone asks the same thing, a decision tree will manage fine.
The second check is response time. More than a quarter of enquiries in our live project come in the evening and on weekends, when the manager isn't working. Whatever is in this place, it needs to reply when the person writes, not when the workday starts.
How this looks in numbers and how the conversation review works, we show in the section sales analytics.
Frequently asked questions.
Are an AI agent and a chatbot the same thing?
No. A chatbot is given a script, an agent is given a goal. The bot follows a branch drawn in advance and gets lost at any step aside; the agent understands what is written in words and chooses what to do next itself.
Will the client realise they are not talking to a person?
Most likely yes, and passing the agent off as a human is not worth it: it comes out quickly and spoils the impression. In practice people are annoyed not by a robot but by silence.
What if the agent answers wrongly?
A properly configured agent answers from your materials and hands everything it doesn't know to a person. For the first weeks after launch you have to read real conversations and refine the answers — without that step the launch cannot be considered finished.
Does an AI agent need a CRM?
Formally no, it works without one. But then most of the value is lost: the correspondence stays in the messenger, no history accumulates and there is nothing to measure the result with.
Will an AI agent replace salespeople?
No, and there is usually no such goal. It takes over the first contact and the routine so that a person can deal with what needs a person: negotiation, difficult cases and money.
How much does an AI agent cost?
The price depends on the number of channels, the complexity of the scenario and the integrations needed. A sensible order of operations is to first count how many enquiries are being lost now, and decide on payback with that figure in hand.
See how it works.
Write a couple of lines about your business to our agent — it will reply and book you a free review. That is the demonstration.