Launching today
Flipns
Bring your local shop online. Reach buyers nearby.
2 followers
Bring your local shop online. Reach buyers nearby.
2 followers
Buy, sell, and explore local products. Bring your shop online with AI-assisted listings, a shareable catalogue, and nearby discovery. Built with GPT-6 Astra to connect offline sellers with online buyers.
Hi Product Hunt! I'm Arvind, the maker of Flipns.
I built Flipns with GPT-6 Astra across the whole product: a marketplace that helps offline sellers bring their shop online and reach buyers nearby. GPT-5.6 Sol also contributed to development.
The problem is practical: a local shop can have great products and still be hard to discover online. Flipns connects the steps a seller needs in one place:
ā¢ Create an editable product draft with AI listing assistance.
ā¢ Build a catalogue and share a public seller profile.
ā¢ Help nearby buyers explore products and their details.
ā¢ Connect buyers and sellers directly through conversations.
Astra helped me develop the seller and buyer experiences, the backend workflows, and the engineering that connects them. The ambition was to build a complete local-commerce experience, from getting a product online to helping someone nearby discover it.
You can see the result at flipns.com. The gallery includes a real Sell chat interaction: I described my Canon camera, supplied the price and location, and received a structured draft to review and edit. The public profile at flipns.com/u/arvind shows the catalogue and product-discovery side. Catalogue import is another AI-assisted path for bringing products online.
The build also involved the less visible work that makes a marketplace useful. For example, Astra helped diagnose a Cloudflare image transformation failure, implement a targeted original-image fallback, and add six passing regression tests. That is one concrete engineering example within the wider product build.
OpenAI models, including GPT-5.6 Luna, support listing assistance and catalogue import inside Flipns. The development tools and the app's runtime models have different roles.
If you run a local shop, what would make bringing your catalogue online easier? If you buy locally, what helps you decide to contact a seller? I'd love your feedback.