Manage a multi-store Etsy shop's full operations from custom order intake through design and production to publishing.
Use AI to parse customer custom product requests and automatically extract structured product requirements for your team.
Track and coordinate custom product workflows across design, production, and multiple selling platforms from one system.
Self-host an ERP system using Coolify on AWS EC2 with PostgreSQL and S3 for a personalized product business.
This is a demo repository with no public installation instructions, access to a running demo is by invitation only for investors, partners, and selected collaborators.
LycheeOS is an internally developed ERP and workflow system built for businesses that sell highly customized products, originally created to manage the operations of a personalized product shop on Etsy. ERP stands for enterprise resource planning, which refers to software that tracks and coordinates business operations across departments. Here, it covers the full chain from a customer's custom request through design, production, and marketplace publishing. The workflow described in the README follows a fixed sequence: a customer's custom request comes in, AI parses it to extract structured product requirements, those requirements drive a SKU generation step, the ERP records are updated, the work is routed to designers, a production workflow runs, and the finished item is published to one or more marketplace platforms. The system manages multiple stores and multiple selling platforms simultaneously. The README states the system has been through several months of internal testing and currently supports operations doing seven-figure annual revenue. The infrastructure listed includes Cloudflare, Coolify (a self-hosted deployment tool), AWS EC2, PostgreSQL, and S3 object storage. The frontend is built with Vue. This repository is a demo version of the system. A whitepaper is linked from the README, but architecture and infrastructure documentation pages are listed as still in progress. No public installation instructions are provided, access to a running demo is by invitation only, available for investors, partners, and selected collaborators who contact the team directly. The README is brief and does not describe the AI parsing in technical detail or document the data model.
← bianen on gitmyhub — every repo by this author, as a profile.
Verify against the repo before relying on details.