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AI Survey & Feedback Collector
I engineered this AI automation to transform passive feedback into real-time business intelligence. The workflow starts when a user submits a response via Typeform or Google Forms, which triggers a make.com scenario via a webhook. I integrated OpenAI to perform sentiment analysis and categorization on the text, then used an API integration to route high-priority "negative" sentiment alerts to Slack while archiving all data in Airtable. This make.com automation (formerly Integromat) ensures no customer concern goes unnoticed, showcasing my expertise as a make.com expert in sentiment-driven workflow automation.
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
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Experimented a bit today with Krea and image generation for a case study I’m putting together around AI EarPods connected to OpenAI.
The focus has been on creating fashion-forward product imagery and art directing a world that feels specific to the identity, rather than just generating nice-looking AI images.
The trickiest part has been product consistency. Especially getting the EarPods to actually sit snug in the ear. If you’ve worked through this process, you probably know the struggle 😅
Simply telling AI to “make it fit more snug or in the ear” doesn’t always work. It loves to reinterpret the product every time.
Still experimenting, but getting closer. If anyone has found a good workflow for keeping products consistent across AI-generated shoots, I’d love to hear it!
TOP!
AI RAG Pipeline & Knowledge Base Chatbot Automation Built with n8n
My role. AI Automation Engineer | n8n & RAG, AI Chatbot Developer
Project description. Built an end-to-end RAG (Retrieval-Augmented Generation) pipeline and AI chatbot using n8n. The workflow automates knowledge ingestion, processing, context retrieval, and LLM-powered response generation. It demonstrates how business knowledge can be connected to an AI assistant to provide more relevant and grounded answers. The solution can be adapted for customer support, internal knowledge bases, document Q&A, and AI-powered business automation.
Skills and deliverables
n8n
CRM Automation
API Integration
Chatbot Development
LLM Prompt Engineering
🚀 Automated AI Document Processing & ATS Pipeline (n8n)
Project Summary
Replaced a manual candidate screening process with a fully automated, n8n-orchestrated backend pipeline. The system automatically intercepts incoming applications, uses OpenAI to analyze documents, updates databases, and triggers client communication—cutting manual data entry down to zero.
The Outcome & Business Value
Eliminated Manual Data Entry: Automated 100% of resume parsing, document conversions (Docs to PDF), and data extraction tasks.
Instant Candidate Screening: Integrated an OpenAI Chat Model Decider to evaluate incoming resumes against job descriptions in real-time with zero human delay.
Automated Sync & Follow-Ups: Automated instant logging to Google Sheets and launched immediate multi-path email responses based on candidate status.
How It Works (System Architecture)
Phase 1 (Ingestion & Extraction): Captures files via webhooks/emails ➡️ Cleans data via custom code nodes ➡️ Parallel-processes files to extract raw text ➡️ Uses AI structured parsing to match applicants to open roles.
Phase 2 (Database & Delivery): Routes structured applicant data ➡️ Upserts matching rows into a centralized tracking database ➡️ Triggers dynamic conditional emails back to candidates.
