Automated Reminder Booking + Reminder System
"Being a consultant comes with a headache of managing the meetings and keeping track of them"
For this purpose, this workflow is like the painkiller.
About the workflow :
-> Triggered when someone books a meeting on Cal.com(can be some other platform as well).
-> An AI Agent sees the meeting, reads the description and classifies it as none, light or high prep needed (can also be some other criteria).
-> Based on the prep level needed, the workflow divides:
1. None - An AI Agent checks the client's data against the provide ICP (Ideal Customer Profile) and then sends the data over to Slack.(The meetings are ignored or rejected by this lead scoring.)
2. Heavy - Does a research on the internet via SerpAPI about the client and his company and gives a brief report on him so that the consultant can be prepared for what to prepare for the meeting.
3. Light - Does research too but not as thorough as Heavy one.
As heavy prep takes around a whole day, if there were to be more than one bookings in that time the consultant won't be able to research and prepare sufficiently which feels quite embarrassing when the client asks you something and you can't answer it.
So for this, I made the 24 hours after a heavy prep needing meeting is booked as "Busy" on google calendar so that Cal.com won't allow to book further meetings in that time.
I did the same for Light prep needing meetings but they only need around 2 hours of preparing so I made the 2 hours busy only.
Stack:
n8n
Cal.com (webhook trigger)
Google Gemini (LLM — 5 separate model connections across agents)
Google Docs (ICP knowledge base, attached as a tool)
SerpApi (web search — Google Search, ×2 instances)
Google Calendar (auto-blocking prep time)
Gmail (briefing emails)
Slack (hot-lead / intro-call notifications)
Time to build : 1 hour
For this purpose, this workflow is like the painkiller.
About the workflow :
-> Triggered when someone books a meeting on Cal.com(can be some other platform as well).
-> An AI Agent sees the meeting, reads the description and classifies it as none, light or high prep needed (can also be some other criteria).
-> Based on the prep level needed, the workflow divides:
1. None - An AI Agent checks the client's data against the provide ICP (Ideal Customer Profile) and then sends the data over to Slack.(The meetings are ignored or rejected by this lead scoring.)
2. Heavy - Does a research on the internet via SerpAPI about the client and his company and gives a brief report on him so that the consultant can be prepared for what to prepare for the meeting.
3. Light - Does research too but not as thorough as Heavy one.
As heavy prep takes around a whole day, if there were to be more than one bookings in that time the consultant won't be able to research and prepare sufficiently which feels quite embarrassing when the client asks you something and you can't answer it.
So for this, I made the 24 hours after a heavy prep needing meeting is booked as "Busy" on google calendar so that Cal.com won't allow to book further meetings in that time.
I did the same for Light prep needing meetings but they only need around 2 hours of preparing so I made the 2 hours busy only.
Stack:
n8n
Cal.com (webhook trigger)
Google Gemini (LLM — 5 separate model connections across agents)
Google Docs (ICP knowledge base, attached as a tool)
SerpApi (web search — Google Search, ×2 instances)
Google Calendar (auto-blocking prep time)
Gmail (briefing emails)
Slack (hot-lead / intro-call notifications)
Time to build : 1 hour
