// Case study / AI email agent
A real-estate services business whose sales team handled a steady stream of inbound enquiries by hand. We built an AI assistant that works inside the inbox they already used, rather than asking them to adopt another tool.
This engagement is shown without the client's name, at their preference. The problem and the build are described as delivered.
Every reply and follow-up was manual. Responses took hours, some enquiries were missed altogether, and slow communication was quietly costing real opportunities — the kind of loss that never appears as a line item, because nobody counts the deal that went to whoever answered first.
The assistant works inside the mailbox the team already uses. No new interface to learn, no migration, and nothing to remember to check.
It reads each enquiry, assesses what the sender actually wants, and answers accordingly — rather than firing the same template at every message.
Routine questions get answered and prospects get qualified before a person touches the thread, so the team picks up conversations that are already moving.
When a lead is ready to talk, the agent books the meeting directly onto the calendar instead of trading availability over several emails.
The point was never to remove people from the conversation — it was to make sure the conversation starts, and that the team spends its hours on the exchanges worth having.
It handles first response and qualification, and hands over to a person once a conversation is worth a human. Where a client wants approval before anything sends, that is how we build it — the balance is a decision made during scoping, not a fixed setting.
Usually, yes — the approach is to work inside the tools a team already uses rather than replace them. Whether it fits your particular setup is a scoping question, and the honest answer depends on what you are running.
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