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Quote requests on autopilot ⚙️
An e-commerce seller I'm working with was answering every incoming quote request by hand. That meant hours of copy-paste each day and slow replies to buyers.
I built them a system that collects the requests, matches them against their inventory, and prepares the offer drafts. Someone on their team still reviews and approves every offer before it goes out.
They now reply faster, do much less manual work, and nothing goes out unchecked.
Built with Python, Playwright, PostgreSQL and Next.js.
If your team spends hours on repetitive work in a browser or spreadsheet, I can help automate it. Send me a message.
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Join 1.25M professional creatives like you
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Quote Follow-Up Automation for HVAC & Plumbing
Most home-service quotes don’t get rejected, they just go quiet. I built a system that follows up on them automatically.
What it does
Takes each quote through a simple form
Schedules up to 8 timed texts over 30 days
Stops instantly on a reply, a STOP, or a booked/lost update
Uses AI to draft replies to objections, with a human approving every one
Built with safety first
No duplicate texts, even when processes overlap
Only contractor-approved wording is sent
Texts go out only during local business hours
Opt-outs are honored immediately
Stack: n8n, Postgres, Groq, Docker, Twilio
Status: built and tested end to end, ready to pilot.
I build automation systems like this for service businesses. Message me if you’d like one for yours😊 .
Clients often start with the same request: "Let's build an AI agent."
My counter-question is always: which manual process actually costs you time, errors, or money right now?
My selection rule: remove it first. If it can't be removed, simplify it. If it's still needed, automate it with a plain script. Only then add an integration or an agent. Often the best result is the process that no longer exists.
Safe automation means real scenarios, error handling, and alerts. Without alerts, a workflow can silently lose data for weeks. I always define what stays with a human and what goes to the system.
Question for you: which process would you automate first, and why is it still manual?
Service for audit and implementation: https://contra.com/s/BmWLbgFU-ai-automation-from-your-dream-to-working-implementation?r=auto_booster
I gave a dental clinic a receptionist that never sleeps. 🦷
Today I finished building a WhatsApp AI Receptionist — and tested it live, end to end.
A patient messages the clinic on WhatsApp. Within seconds they get a polite, human-sounding reply with the clinic's REAL fees, timings and doctors — because the AI answers only from the clinic's own database. It never invents a price. If it doesn't know, it says it will confirm with the owner.
The honest part? Halfway through testing, it broke. Spectacularly. 😅
WhatsApp sends invisible "delivered" signals — and my system was answering those signals too. 192 executions later, I found the cause hiding in one execution log: no message, just a delivery status. One guard node later, the loop was dead and the replies were clean.
That debugging session taught me more than any tutorial:
→ Always guard your trigger. Not every webhook event is a message.
→ Read the raw execution JSON before guessing. The answer is always in there.
Now I'm setting this up for clinics and local businesses that live on WhatsApp — instant replies, appointments captured, every lead saved, even at 2 AM.
If your business answers the same 10 questions on WhatsApp every day — what would you automate first?
