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Inbox intake that becomes a shipment
Connected mailboxes surface quote and status threads. AI extracts lane, equipment, dates, and missing fields onto a shipment record the whole desk can see.
Logistics
Dispatch lived in the inbox. Quote requests, carrier replies, rate confirmations, and “where is this load?” emails arrived all day. Status lived in the TMS if someone had updated it, and in a spreadsheet if they had not. Asking “what needs action before noon?” meant searching threads, not opening a board.
AI workflow + inbox consolidation
01
Connected mailboxes surface quote and status threads. AI extracts lane, equipment, dates, and missing fields onto a shipment record the whole desk can see.
02
Operators can ask what arrived, which shipment it belongs to, what a document says, and what the next step is — from the dashboard, not by hopping tabs.
03
Outreach, quotes, and bookings are proposed, then approved. Suspicious senders hit a review queue instead of entering the live board. Booked loads hand off to the TMS when the team is ready.
It reads them and drafts the next step. Connected mailboxes surface quote and status threads, and the model extracts lane, equipment, dates, and missing fields onto a shipment record. Automation is allowed to draft; it is not allowed to send.
By never giving it the send button. Outreach, quotes, and bookings are proposed and then approved by an operator, and suspicious senders go to a review queue instead of onto the live board. Operators told us automated sending was a non-starter, so it was designed out rather than bolted down.
No. The TMS stays where it is. This is an operations layer over email, documents, and the TMS, and booked loads hand off to it when the team is ready. Replacing a working system of record is rarely the cheapest way to fix an inbox problem.
Yes. Documents become context attached to the shipment rather than a parallel pile of attachments, so operators can ask what a document says and which load it belongs to from the dashboard instead of searching threads.
Most AI pilots stall because they are built as a demo beside the workflow instead of inside it. We put AI into the step that actually costs your team hours — reading documents, triaging inbound requests, drafting the routine reply — and let deterministic code make the decisions that have to be auditable.
Workflow automation fails when teams buy generic tools that do not match the process. We build custom workflow software around your approvals, handoffs, documents, and operational rules — then add AI only where it removes real work.
Most businesses do not have a software problem because one tool is old. They have a problem because legacy systems, modern SaaS, spreadsheets, and manual steps were never designed to share one workflow.
Construction
Estimators were reading plans into spreadsheets, then emailing suppliers one by one. We built a desk where uploaded drawings become a reviewable material list, a quote, and a side-by-side RFQ — without another SaaS seat for each step.
Read the case studyField service
Crews were requesting material by text. Warehouse counts were a week old. We built a requisition workflow across trucks, the warehouse, and contract budgets, and left the ERP in place as the system of record.
Read the case studyTell us the tools, spreadsheets, or legacy systems in the way. We will say whether it should become one custom app.