Comfort Peluola
I build workflows that save businesses 10+ hours/week
New to Contra
Comfort is ready for their next project!
Helped a client eliminate 10+ hours of manual work
this week with a simple CRM automation in GoHighLevel.
Sometimes the simplest workflows make the biggest difference.
#automation #gohighlevel
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Just finished building a document sync system that
automatically routes files from PandaDoc to 4 cloud
platforms simultaneously. Zero manual work required.
#workflowautomation #make
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This was a more complex build. The system receives incoming data through a webhook, stores the context in a Data Store so it remembers what's been said, then runs it through OpenAI (ChatGPT) to generate an intelligent response. Depending on what comes back, it takes one of two paths either responds directly through the webhook, or triggers additional HTTP calls and a second AI pass before replying. The result is a bot that doesn't just react to messages, it actually thinks about them first before responding. Built entirely in Make, no extra infrastructure needed.
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This one runs every 15 minutes without anyone touching it. It starts with an API call to check how many items exist, then loops through each one using a Repeater, fetches the image attached to each record via HTTP, and logs every row into Google Sheets as it goes. Once everything is collected, it aggregates the results page by page and sends a clean summary email automatically. The client used to do this manually every few hours. Now it just happens.
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Built a Telegram bot that accepts a message, scrapes a target URL via HTTP, aggregates the returned data, then routes it through a smart decision point. Depending on what the data contains, it either sends it straight to Google Sheets via a Text Parser or pushes it through OpenRouter AI for intelligent processing before storing the final output. Built-in Ignore path handles edge cases cleanly without breaking the workflow.
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Built a multi-step scraping automation in Make that pulls data from the web via HTTP requests, runs it through a Text Parser to clean and structure it, then passes it through Google Gemini AI to extract or summarise the relevant information all ending in an organised output via Google Sheets or a connected tool. The workflow handles two full scraping cycles in one scenario, meaning it processes and validates data twice before storing it.
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