The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
Just shipped a production serverless system on AWS, and it's live:
🚨 RescueHacks Alert: a discreet emergency-alert system. Dial a USSD code and it instantly notifies your emergency contact via WhatsApp, no visible screen, no app needed, works on any GSM phone.
Stack: AWS Lambda, DynamoDB, API Gateway, EventBridge, SNS, Africa's Talking, WhatsApp Cloud API.
Video below shows the full build and a live demo at the end.
If you need a serverless backend for USSD, SMS, or WhatsApp-based notifications, that's exactly what I build. Open to remote work. 👇
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
🚀 Built a Gmail AI-Tagging + Slack Alerts System — Because Important Emails Should Never Get Missed
The problem every B2B team faces:
❌ Client emails sit unanswered for days
❌ Bank or government emails get buried in the inbox
❌ Deadlines are missed because no one flags them
❌ No daily view of what's pending vs overdue
I built a system that fixes all of this:
🎯 WHAT IT DOES:
✅ Watches Gmail inbox every 5 minutes
✅ Uses AI to classify every email into 5 categories:
• URGENT (deadlines, overdue, time-sensitive)
• BANK_GOV (banks, .gov domains, tax authorities)
• CLIENT_ACTION (awaiting response)
• FOLLOW_UP (needs follow-up)
• FYI (informational)
✅ Pushes real-time Slack alerts to the right channel:
• #urgent — for time-sensitive items
• #finance-legal — for bank/gov emails
• Assignee DM — for client action items
✅ Sends a daily 8 AM digest with:
• Overdue items
• Awaiting client action
• Pending tasks
✅ Auto-applies Gmail labels (AI/Urgent, AI/Bank-Gov, etc.)
✅ Hourly overdue scanner with automatic escalation
⚙️ TECH STACK:
n8n | Gmail API | OpenAI GPT-4o-mini | Slack API | Google Sheets
📊 RESULT:
→ Zero missed urgent emails
→ 15+ minutes saved per team member per day
→ Complete audit trail in Google Sheets
→ Full visibility into what's stuck and where
Gmail stays the primary interface. Slack becomes the reminder layer that ensures nothing slips.
Want this deployed for your team? Let's talk.
#AIAutomation #GmailAutomation #SlackIntegration #n8n #B2BSaaS #Productivity #WorkflowAutomation
Splitting BANK_GOV out on its own is smart. Those are the emails that hurt most when they get buried. When GPT-4o-mini tags one wrong, does the corrected label feed back into the prompt, or is it fixed by hand?
A chatbot can sound helpful and still create a messy order.
When a customer changes a quantity or delivery detail, the real test is whether the system keeps the context, checks the information, and records the right request for the team.
In an 80-hour WhatsApp automation project, I built the conversation flow with structured AI output, input validation, order recording, logging, and error handling. The client rated the completed work 5.0.
That’s the part I care about most: turning a chat into a record people can actually work from, with errors visible when something goes wrong.
If your team takes orders through WhatsApp, what happens between the AI’s reply and the order record?
Order changes mid chat are where most WhatsApp bots fall apart. Did you confirm the changed details back to the customer before recording, or validate silently?
WhatsApp chats piling up at a small business? I built an AI assistant that handles them, with 3 rules it never breaks.
Answer only from the business's own documents, and show the source.
If the answer isn't there, it says so and offers a person. No guessing.
Book appointments step by step, checked against the opening hours.
Sunday? Closed. Friday at 10:30? Recorded, and the owner gets a WhatsApp message.
Hand the chat to a real person the moment the customer asks.
The bot goes quiet, and the owner replies from their own WhatsApp.
The test that surprised me:
Before publishing, I ran real conversations through it. "Quiero hablar con una persona" (Spanish) reached a person. "I want to talk to a person" (English) didn't: the bot asked the customer to type "human". English was missing the word "person". Fixed, with a test so it can't come back.
Under the hood: Python, FastAPI, the official WhatsApp Cloud API and Claude, plus an offline mode that needs no API key. Signed webhooks only, no double replies, flood control. 245 tests, 98% coverage.
Full case study and code: https://contra.com/p/YAEPQRqk-whats-app-ai-assistant-answers-booking-handoff
Does your team answer the same WhatsApp questions every day? Send me your top 5 and I'll tell you which ones a bot can answer safely.
The detail about the English trigger failing while Spanish worked is a perfect example of why multilingual edge cases break production systems. Standardizing the handoff phrase across all supported languages prevents that kind of silent failure.