Akogun ImoleayoVerified StackedHQ member

I built an AI email draft workflow that attaches necessary files and sends them to an independent consultant (my client) for them to review. It is an 8-node workflow.

I built a session confirmation and follow-up workflow for a tutorial agency. The workflow checks for sessions a day before the actual session and sends a WhatsApp message to the parents of their tutees to confirm the availability of their wards and also sends a follow-up message a day after to check up and also know if they would like to book another session. These all get updated on Google Sheets, and the tutorial agency gets a notification of messages sent. Tool stack: Make.com, Google Sheets, whatsapp api, telegram

Reads inbound customer inquiries from Gmail and a web form. Extracts action, deadline, preferred time, and open questions using an LLM (Groq Llama 3.3), then routes the result to team email (the CEO, in this case) and a Google Sheets log. Stack: n8n, Groq, Gmail node, Webhook, Google Sheets. Flow: Gmail Trigger + Form Webhook → Normalize (unify field names across both sources) → Merge → HTTP Request to LLM → Parse JSON (with a fallback for malformed output, flagged urgent for manual review) → team email + sheet log. Confirmation branch: looks up the exact row by a unique ID, checks status, sen

I built an automated lead intake system for a marketing agency using n8n, Tally, OpenAI, and Google Sheets. It solves the problem of losing leads due to the massive compilation of forms submitted. This workflow does the heavy lifting of reading the forms, extracting necessary info, storing the info and alerting the person in charge of leads. It eliminates manually reading each submission, which takes time and can lead to lost leads. The flow runs like this: Tally form submission triggers n8n, OpenAI turns the raw message into a one-line summary, the lead gets logged to Google Sheets with a tim

I built a reminder engine for a travel agency. What the workflow does is, every morning by 6am, it checks through a Google Sheet containing client info such as their WhatsApp number, destination, departure date and return date; using a filter (status=pending), it calculates the date for departure (1-3 days before) and the return date (1 day after); and it drafts up a message, which is then sent to the client based on whether it is pre- or post-trip. Then, to prevent duplicate messages being sent, the engine auto-updates the Google Sheet status from pending to pre- or post-trip, based on whic

Built two mini AI workflows, using Gmail, Google Sheets, GroqAI, Google Docs API and Telegram. Email is received, summarised and logged into a Google Sheet, then a draft is made and documented, and the link lands in the Teams Telegram account.

Built an email tracker that summarises and logs each summary from donors into a Google Sheet. Then a second workflow picks the logged information and creates a draft using a given template and notifies the team to review the document. Stack: Make, Gmail, Google Sheets, Google Docs, GroqAI, Google Docs and Telegram.

I build a lead caption, prioritisation and outreach engine that receives prospective leads, classifies the lead into hot, warm and cold, sends dedicated emails to each, alerts the team and enters the information and request into a CRM tool. It also has an error handler that ensures that the workflow does not stop and the team is alerted of every error encountered. Stack: Webhook, Fillout form, HubSpot, Slack, Gmail.

Built a workflow that handles the boring, repetitive and mind-numbing job of handling support tickets manually. The workflow handles support emails received by an e-commerce shop, drafts a response based on the company's policy and drops it in the email of a team member. If the response to a support ticket isn't in the policy doc provided, it escalates and sends a Slack alert to the team. All these get logged to the CRM (Airtable). Approximately 30 mins/request saved. Stack: Gmail, Google Docs, Slack, Airtable, OpenAI, Make.com

The problem Small SaaS teams answer the same support questions on repeat. Someone reads each incoming email, copies the answer out of a help doc, sends the reply, then logs the ticket in the CRM by hand. It's repetitive, slow, and doesn't scale as ticket volume grows. What I built An n8n workflow that reads incoming support emails, checks them against an FAQ knowledge base, and drafts a reply using AI; an actual person still reviews and sends it. Nothing goes out automatically. If the AI isn't confident the FAQ covers the question, it skips drafting and flags the email for a human instead of g

Quick Lead Qualify & Team Alert An n8n workflow that automatically captures form submissions, uses AI to score each lead as hot, warm, or cold and tag the project type, logs everything into Airtable, then instantly notifies your sales team via Slack for hot leads and sends the prospect a personalized email confirmation all within seconds of form submission, no manual triage required.

Missed-Call Text-Back Automation, Bright Smile Dental Built a missed-call detection and follow-up system using MacroDroid (Android automation), n8n, and Google Sheets. Twilio substitution: Twilio trial accounts don't support Nigerian number provisioning, blocking the intended stack. Rebuilt the call-detection layer using MacroDroid's native Missed Call trigger instead, which fires locally on-device and requires no telecom API or paid account. Flow: MacroDroid detects a missed call, sends caller number, timestamp, and status to an n8n webhook (POST, JSON) n8n normalizes the timestamp and lo