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How I Cut Support by 70% for a 3,000-Member Telegram Community
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Creatives on Contra have earned over $150M and we are just getting started
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Just crossed 100 followers on Contra! ⚡
To celebrate, I didn't want a generic thank-you graphic, so I algorithmically arranged 49 tiles of my actual shipped work (Palm, Direct Edits, and recent client builds) into the number 100 using parametric squircle math.
Huge thank you to everyone following the journey, supporting my work, and trusting me to build fast, clean web apps that actually look good.
We’re just getting started. Onto the next milestone! 🚀
Seeing this makes me want to keep going. Congrats!
Resolve: an AI support agent that answers from a company’s own policies, looks up orders, and escalates weak matches to a human instead of guessing. A human approves replies before they go out.
Live demo: support-resolver.vercel.app
For the human approval step, I'd show the exact policy passage and its effective date beside the draft. Does Resolve flag a reply for re-review if the policy changes while it waits for approval?
Processing incoming PDF attachments and logging key email data manually takes hours of tedious, repetitive work. Every time a new invoice, quote, or report lands in your inbox, you have to manually open the email, download the PDF, read through dense pages to extract important details, format the data, and log it into Google Sheets row by row.
Which one is faster, saves more time, and prevents mistakes?
1 voted
25%
3 voted
75%
4 votes
Closed
The manual-vs-automated framing is clear, but I'm curious how the workflow copes with PDFs that don't share a layout, like scanned invoices versus quotes. Do you parse them with a fixed template or an extraction step, and what happens to rows it can't read confidently?