AI lead capture in n8n: a web form sends each lead to an LLM that scores it from 0 to 100 and drafts a reply, the lead is logged in a Google Sheet CRM, and hot leads trigger a Gmail alert. In the 2-minute demo a hot lead scores 88 and a cold one scores 12: https://youtu.be/SOm5txaL9L4
Processing incoming PDF attachments and logging key email data manually takes hours of tedious, repetitive work. Every time a new invoice, quote, or report lands in your inbox, you have to manually open the email, download the PDF, read through dense pages to extract important details, format the data, and log it into Google Sheets row by row.
Which one is faster, saves more time, and prevents mistakes?
The manual-vs-automated framing is clear, but I'm curious how the workflow copes with PDFs that don't share a layout, like scanned invoices versus quotes. Do you parse them with a fixed template or an extraction step, and what happens to rows it can't read confidently?
Moving the card to Booked off the Appointment Status trigger is a nice touch. What happens when the same person submits the form twice, does the opportunity get updated or do you end up with a duplicate in New Lead?
Resolve: an AI support agent that answers from a company’s own policies, looks up orders, and escalates weak matches to a human instead of guessing. A human approves replies before they go out.
For the human approval step, I'd show the exact policy passage and its effective date beside the draft. Does Resolve flag a reply for re-review if the policy changes while it waits for approval?