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Python Reporting Automation — Synthetic Data Demo
A reusable Python workflow that combines two CSV files, validates dates and amounts, handles duplicates, and produces clean data, a rejection log, a regional summary, and an audit report.
The sample reconciles 25 input records into 20 accepted and 5 rejected records, with USD3,470 in accepted revenue.
Includes source code, run instructions, and a validation test.
Demonstration using synthetic data, not client work.
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The design combines a clean, minimal interface with bold typography, futuristic visuals, interactive UI elements, and a seamless user experience. From AI-powered task automation to real-time productivity insights, every section is designed to communicate the value of intelligent automation in a clear and engaging way.
This project explores how thoughtful UI/UX design can make complex AI technology feel intuitive, accessible, and easy to use for modern businesses.
Services: SaaS Website Design, UI/UX Design, Landing Page Design, AI Product Design.
Same support inbox, one difference. Left keeps a human on every send. Right lets the AI send on its own once the draft confidence passes 90, refunds and cancellations excluded.
I built both in Relay this week and I still cannot decide.
Would you flip that switch for your own customers, and at what number?
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I'd flip it per topic, not per score. A 90 on a question the AI has answered hundreds of times is safe. A 90 on a question it has never seen is still a guess. Can Relay set a different threshold per topic?
My first n8n template is now live in the official n8n library, and it is free to use.
After a sales call, most people either rush the follow-up email or forget it. This workflow does the first draft for you.
When Fireflies finishes transcribing a call, it:
pulls the full transcript
uses OpenAI to write call notes: a summary, open questions, the next step and the outcome
saves a follow-up email to the contact as a Gmail draft
logs the call in Google Sheets and emails you the notes
Nothing is sent to the contact automatically. The follow-up waits in your drafts until you check it and press send.
Works with the free Fireflies plan and n8n Cloud.
Get it here: https://n8n.io/workflows/20963
Congrats on getting it approved. Drafting instead of auto-sending is the right default. One edge case worth a guard: calls where the transcript comes back empty or cut short, otherwise the model writes a confident follow-up from almost nothing.