In my hunt for an excellent open-source ERP, I couldn't help but be disappointed with the available options. No true lightweight, modern solution exists that I felt I should invest my time with. My other open-source project, QuanuX, is about to launch, and I wanted to set it up from the outset with a highly modern, scalable ERP solution.
I've recently rebuilt the CLI for QuanuX in Go and had a fantastic experience. It quickly occurred to me that I could build my own ERP atop Google's IAM-based role management and Google Workspace—completely eliminating the need for Twilio, WhatsApp, and a million third-party apps via the Workspace API. And since the Workspace API made this all possible, why not build the whole thing on GCP to complete the hat tip?
But I had to take it a step further. It's 2026—who wants to run a boring ERP when agents or bots can manage it 100x better than humans?
Enter SKILL.md and what I call the "Knowledge Vector." By utilizing Google's GCP data suite (Vector/ScaNN) and Qdrant, GERP turns all SKILL.md files, Unix man pages, and developer docs into a perfect vector graph. This ensures any developer—human or AI—can enter the repository anywhere and instantly understand the laws of physics governing the system via semantic search.
Speaking of AI, my favorite tool in GERP is the native Model Context Protocol (MCP) server. It exposes the ERP's CLI tools directly over STDIO, allowing LLMs and AI Agents to natively read the immutable audit logs and trigger complex workflows without expensive context switching.
GERP is a headless ERP infrastructure built almost entirely in Go with a GraphQL-ready schema for your frontend integration. To achieve infinite horizontal scale, it uses zero SQL foreign keys. Instead, it uses a "Golden Thread" architecture across 8 perfectly isolated Google Cloud Spanner databases, and is orchestrated by Temporal Sagas to handle distributed ACID compensations.
There's a lot to add and a ways to go before it replaces NetSuite, but we aren't that far off!
In my hunt for an excellent open-source ERP, I couldn't help but be disappointed with the available options. No true lightweight, modern solution exists that I felt I should invest my time with. My other open-source project, QuanuX, is about to launch, and I wanted to set it up from the outset with a highly modern, scalable ERP solution. I've recently rebuilt the CLI for QuanuX in Go and had a fantastic experience. It quickly occurred to me that I could build my own ERP atop Google's IAM-based role management and Google Workspace—completely eliminating the need for Twilio, WhatsApp, and a million third-party apps via the Workspace API. And since the Workspace API made this all possible, why not build the whole thing on GCP to complete the hat tip?
But I had to take it a step further. It's 2026—who wants to run a boring ERP when agents or bots can manage it 100x better than humans?
Enter SKILL.md and what I call the "Knowledge Vector." By utilizing Google's GCP data suite (Vector/ScaNN) and Qdrant, GERP turns all SKILL.md files, Unix man pages, and developer docs into a perfect vector graph. This ensures any developer—human or AI—can enter the repository anywhere and instantly understand the laws of physics governing the system via semantic search.
Speaking of AI, my favorite tool in GERP is the native Model Context Protocol (MCP) server. It exposes the ERP's CLI tools directly over STDIO, allowing LLMs and AI Agents to natively read the immutable audit logs and trigger complex workflows without expensive context switching.
GERP is a headless ERP infrastructure built almost entirely in Go with a GraphQL-ready schema for your frontend integration. To achieve infinite horizontal scale, it uses zero SQL foreign keys. Instead, it uses a "Golden Thread" architecture across 8 perfectly isolated Google Cloud Spanner databases, and is orchestrated by Temporal Sagas to handle distributed ACID compensations.
There's a lot to add and a ways to go before it replaces NetSuite, but we aren't that far off!
Check it out: https://github.com/quantDIY/GERP This is MIT Licensed and ready for you to explore.
@quantDIY