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Sales calls are goldmines of information that almost nobody actually uses.
A client was recording every discovery call but the insights just sat in transcripts — no one had time to read 30+ calls a week. Their CRM notes were whatever the rep remembered to type before moving on.
I built them a pipeline in n8n: call transcripts come in, an LLM processes each one and pulls out structured data — pain points mentioned, objections raised, buying signals, next steps, competitor names dropped. Everything lands in Google Sheets, auto-tagged and ready to filter.
No more "what did they say about pricing?" — just pull up the sheet and search.
The interesting part wasn't the AI piece. It was deciding what to extract. We went through three iterations before landing on a schema that the sales team actually used. Too much data and people stop reading it. Too little and it's not worth the workflow.
The final schema has 9 fields. That's it. And it gets checked every single day.
If you're sitting on call recordings and not feeding them into any kind of structured review process, you're leaving real signal on the table.
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Sales teams already have the data. The problem is finding what actually matters.
We built an AI Sales Intelligence Agent that brings together CRM activity, emails, calls, meetings, Slack and WhatsApp into one intelligent layer.
It helps sales teams:
• Identify leads that need follow-up
• Detect opportunities that are going cold
• Understand common customer objections
• Summarize conversations and client history
• Highlight deals that need immediate attention
• Turn sales activity into actionable insights
Instead of spending hours going through CRM records and conversations, teams can simply ask:
"Which leads need follow-up today?"
"Which opportunities are at risk?"
"What objections are prospects raising?"
"What did this client ask for in our last 3 calls?"
The goal is simple: give sales teams the right insight at the right time.
Cold email sequence that turns leads into booked meetings. Growth Flow CRM's outreach was getting under 2% replies generic subject lines, zero personalization, weak follow-up. I built a 4-email sequence using curiosity-driven subject lines, specific personalization, and a 'then I'll stop' final ask that removes pressure instead of adding it. Projected: 8%+ reply rate, 3%+ meeting booking rate (vs. 2-3% industry average). (Sample project demonstrates process)
Hi everyone!
A lead fills out a form on your website. What happens in the next 5 minutes
decides whether they become a customer — or forget you exist.
THE PROBLEM
Leads sit in a mailbox or a spreadsheet until someone notices them. By then,
78% of buyers have already contacted a competitor.
THE SOLUTION
Lead Machine — an n8n pipeline that handles every inbound lead automatically,
from form submission to follow-up email in about 30 seconds, 24/7:
webhook → validation → duplicate check → Google Sheets → welcome email
→ Telegram alert to the manager → automatic follow-up in 24h
Every step is plain n8n nodes: no AI keys, no token fees, no monthly SaaS.
Validation rules, email texts, follow-up delay — all editable in the n8n UI.
It runs on YOUR infrastructure: credentials stay with you.
LIVE DEMO — send a test lead and watch the pipeline:
https://dvc-shared.dvc-ai.workers.dev/t/leadmachine-demo
Full case study on my profile.
Amazing