AI integration pays off where working with messengers consists of many small actions and describing the task is easier than programming it.
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Marketing
A segment is described in words: “those who replied but did not buy”. The assistant finds them, prepares the text and shows the draft before sending.
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Sales
The assistant reads customers' replies, separates those who are interested from those who refused and suggests who to write to today and with what offer.
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Support
Routine questions are closed without a manager: the price list, the terms and the instructions go out at once, and a difficult dialog is handed over to a person.
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HR and recruiting
Invitations go out across the candidate base, and the assistant sorts the responses itself: who agreed, who refused and who to write to later.
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Surveys and reviews
A survey after a purchase or a visit, and instead of reading hundreds of conversations — a summary by meaning: what gets praised and what gets complained about most often.
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Analytics
Ask “how did yesterday's mailing go” and delivery, reads and replies come back as plain text, with no exports and no spreadsheets.
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Day-to-day work
Topping up the base from a file or from a conversation, checking numbers in the messenger, keeping segments and contact properties — without opening your account.
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Your own agents
Scenarios on n8n or your own platform: the agent starts touchpoints on a schedule and on events in your system, with no person involved.
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Working with a CRM
One-off tasks on top of your CRM: a selection by deal stage or a mailing “to one country only”.
The set of capabilities is the same as in the messenger API: the MCP server works on top of it and on the same keys, so automation in your systems and the assistant's work live in one project and see the same accounts, segments, mailings and customer replies. The difference is the way in: the API describes a scenario in code once and for all, while the assistant only needs the task explained in words — and changed at any moment.