We show the work we are in. We do not invent logos.
One current client engagement — replacing a third-party ticketing tool with a private, in-house AI system the client controls. It starts with mapping the work, then recommending where AI belongs.
Support operations · in progress
The mailbox was the ticketing system. The third-party tool was the extra hop.
Support already lived in client-facing email. People wrote to the company. Staff either copied that mail into a separate ticketing tool or worked the inbox and the ticket queue as two desks. The mailbox was the real ticketing system. The ticketing tool was the extra hop.
Recommendation: Do not bolt a chatbot onto a third-party tool and hope the extra hop disappears. Take in mail where it already arrives, open a ticket in a system the client controls, let AI close the routine work, and escalate what the model cannot manage. The system runs on a local model, so message contents and attachments stay inside the client's own environment and never reach a public AI service. That is a go on intake and close — and a stay-human on everything else.
We are building that path now: a private AI app that watches the client-facing mailboxes, opens a ticket from each message, closes what it can close, and escalates the rest to a person. No invented outcomes. The work is in flight.
01
Mailbox intake
The client-facing mailboxes are the intake — the work is taken in where it already arrives, with no second desk to keep in sync.
02
Ticket the message
Each message is opened as a ticket by an AI app the client controls, not by a second desk.
03
Close what AI can close
Routine, well-bounded requests are resolved and closed by the app.
04
Escalate the rest
What the model cannot manage is handed to a person. That gate is the point.
The system runs on a local model inside the client's own environment — message contents and attachments never reach a public AI service.
In progress — no invented outcomes
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Response within one business day. Toledo, OH and Orlando, FL.
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