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AI agents don’t actually see images — they guess. This becomes a real problem in n8n and automation workflows where accurate product recognition matters.
I solved this by embedding a unique product code directly into the corner of each image. When an image is sent through WhatsApp or Telegram, the AI reads the code instead of relying on visual interpretation. That single change makes image recognition deterministic and reliable.
I built and tested the full n8n workflow: image intake → code extraction → backend product match → accurate response. The result is zero hallucination, higher accuracy, and production-ready automation for ecommerce and support bots.
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Connect with clients, get discovered, and run your business 100% commission-free
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Built a full-stack AI automation system that transforms how the company responds to RFPs.
Users upload RFP documents (PDF/Excel) through a web portal. An n8n pipeline processes the upload: AI parses the document to extract key fields (issuer, scope, budget, deadline), classifies the service line, matches content from an Airtable library (team bios, references, portfolio), and generates 80-90% complete proposal drafts with cover letter, company overview, technical approach, and more. Output is a formatted Word document ready for review.
Results:
✅ Reduced proposal creation from 4-6 hours to under 30 minutes
✅ 90% auto-complete rate on proposal sections
✅ 14+ RFPs processed through the pipeline
✅ Full proposal dashboard with status tracking
Tech: n8n, OpenAI, Airtable, Vercel, Webhooks
This is a really interesting automation workflow, Peter. Using AI to parse RFPs and streamline proposals is a smart use case.
AI-Powered Outreach Automation (n8n)
Built a workflow that turns outreach into a structured pipeline.
The system:
• Pulls verified leads from Supabase
• Uses AI to generate personalized emails
• Sends outreach via Gmail
• Monitors replies and analyzes sentiment
• Routes responses automatically (book meeting, review, or archive)
• Sends follow-ups if there’s no reply after 48 hours
Result: a fully automated pipeline that moves leads → conversations → booked meetings.
Designed for creators, agencies, and teams running outbound outreach at scale.
Nice workflow. Using AI to personalize outreach and track replies in one pipeline is really useful.
Built an AI-powered triage bot (WeSki Bot) for a ski travel company using n8n, Slack, HubSpot, Jira, and GPT-4.
Agents trigger the bot in Slack with a booking ID. It verifies trip details in HubSpot in real-time, then walks through a structured triage flow via threaded replies: collecting issue description, urgency, OPS needs, actions taken, and refund details.
GPT-4 processes inputs and auto-creates a Jira ticket with booking details, triage notes, SLAs, and refund amounts. A Slack notification posts with links to the Jira ticket and HubSpot deal.
Results:
✅ 60% faster response times
✅ Zero manual data entry
✅ 100% lead capture
✅ 24/7 automated triage
Tech: n8n, Slack, HubSpot, Jira, GPT-4, Google Sheets
really nicee work
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