An agent reads messages written the way people actually write them, asks the one or two things that are missing, drops the enquiries that were never customers, and hands your team a structured summary. Built on your own infrastructure, on your accounts, yours to keep.
One message, three questions, no product code, half of it misspelled. That is what real inbound looks like, and it is where button-tree bots give up.
Budget, timing, quantity, region - whatever your team would have asked on the call. The agent asks it while the person is still there, not the next morning.
Agencies pitching services, suppliers, students, wrong numbers. In most inboxes this is a third of the volume, and someone on your team is reading all of it today.
Name, contact, what they want, what stage the conversation reached, and a link back to the original thread. Your team starts the call already knowing the situation.
Every classification is written down with its reasoning. That log is how you find the mistakes in week one and fix the rules, instead of guessing why a lead was dropped.
Saying this up front saves both of us a month. If your case is on this list, an agent is the wrong purchase.
A few hundred actual messages, not a description of them. This is where the volume, the noise share and the repeated questions become visible.
Prices, lead times, what counts as a qualified lead. Usually the slowest step, because the answers exist in people's heads in several conflicting versions.
The agent works alongside your team without touching customers, and you read its decision log. Rules get corrected against real cases, not against a specification.
On your accounts, on your infrastructure, with the logic open. Two weeks of support included, after which it is yours to run.
A chatbot follows a script: press a button, get a prepared answer, step off the path and it stalls. An agent has no decision tree. It reads what the person actually wrote, works out what is being asked, requests whatever is missing and then performs an action: books a call, creates a record, routes the thread to a human.
It will, if you let it. A model never says it does not know, it fills the gap with something that reads true. Anything that can be looked up must be pulled from your own systems rather than left to the model. This single rule is what separates a working agent from an embarrassing one.
Usually four to six weeks, and most of that is not engineering. The slow part is getting written answers to questions your team answers differently today, and agreeing on what counts as a qualified lead. The build itself is the short part.
Closing complex or high-value deals, handling complaints and refunds, and standing in for a process that does not exist. If nobody records what customers ask today, an agent will not fix that. It will only make the gap more visible.
You do. It runs on your accounts and your infrastructure, the logic is open and readable, and it keeps working if we stop working together. There is no platform subscription in the middle.
Four tasks where an agent pays for itself, and the ones where it does not.
Everything else that repeats daily and does not need a person: reporting, integrations, monitoring.
Ad spend, CRM and revenue on one screen, so qualified leads can be traced to money.
Where the messages come from, roughly how many a month, and what your team does with them today. I will reply with what an agent would and would not take off your hands.
or go straight to a messenger