About SybreSoft

SybreSoft started the way most good tools do — out of frustration.

Who we are

We're Chris and Colby — brothers and business partners. Chris has an accounting degree. Colby has a master's in sports management. Neither of us is a software developer by training, education, or career path. We've been Amazon sellers since 2010 — over 15 years of hands-on experience running and growing an ecommerce business across multiple platforms and international marketplaces.

Our entire company is the two of us and one employee. There is no engineering team, no CTO, no outside development agency. We sell on Amazon, eBay, and Shopify — managing thousands of SKUs across 16 Amazon marketplaces including the US, UK, Germany, France, Italy, Spain, Canada, Australia, Mexico, Netherlands, and more. We run active advertising campaigns in 10 of those marketplaces, all managed through Sybre.

Every piece of the platform was built by two business owners directing AI — the same way we're proposing you can too.

The problem we were solving

We were running our Amazon business across multiple marketplaces, juggling 15+ SaaS subscriptions, each solving one piece of the puzzle. Ad management here. Inventory there. Accounting somewhere else. Settlement reconciliation in an Excel spreadsheet held together with prayer and VBA macros.

Each tool cost $50 to $500 per month. Each had its own login, its own data silo, its own way of doing things. And each did far more than we needed while somehow never doing exactly what we wanted.

The realization

When AI coding assistants became capable enough to build real software — not toy demos, but production tools — we asked a simple question: what if we just... built our own?

Not from scratch in the traditional sense. We started with the tools we already had. Excel models. Python scripts. Database queries. We fed them to AI agents and said "make this better, make it part of a real application." And it worked.

The Excel tool that took 3 days to debug? AI fixed it in 20 minutes and turned it into a proper web component. The settlement reconciliation? Now it's automated with scheduled tasks and real-time notifications. The ad management? A sophisticated bid engine with similarity analysis that runs circles around the $400/month tool we were paying for.

And we did all of this without writing code in the traditional sense. We describe what we need. AI builds it. We test it, refine it, and move on to the next thing. Our domain expertise — understanding the business, the data, and what the tools actually need to do — turned out to be far more valuable than knowing how to write a for-loop.

What Sybre is today

Sybre is a full business management platform — React frontend, Python backend, MySQL databases, Celery task scheduling, real-time WebSocket notifications, encrypted credential management, and a native desktop manager app. Every piece of it was built with AI assistance, and every piece of it is designed for AI to continue improving.

We use it every day to run our business — not as a side project, but as our actual production infrastructure. We manage our Amazon advertising, process settlements, create listings, handle photo workflows, and coordinate shipping integrations all through Sybre. We're simultaneously building the platform and running our business on it. That dual use is the best proof that it works: we couldn't afford downtime or broken tools, because the same system we're developing is the one keeping our business running.

That's also what makes it a real example of the cost reduction and streamlining we're talking about. We didn't stop selling to build software. We built the software while selling — and each new tool we added immediately started saving us time and money. The SaaS subscriptions dropped off one by one as each piece of Sybre replaced them.

It's not a SaaS. It runs on our hardware — regular Windows desktops, nothing exotic. Our data never leaves our network. There are no monthly platform fees, no per-seat charges, no vendor who can raise prices or sunset features.

Software that improves itself

Here's the part that surprised us most. Because Sybre is open source and runs on our machines, the AI agents we use to build it can also see how it's running. They read the source code, query the database, check the logs, and understand the full picture — not just an API surface, but the actual implementation.

That means when something isn't working right, the AI doesn't just report a symptom. It traces the problem through the code, finds the root cause, fixes it, restarts the service, and confirms the fix is live. When we want a new feature, the AI reads the existing system, understands how it's structured, and adds the feature in a way that fits naturally — because it can see everything.

This is something fundamentally new. Traditional software is inert — it runs, and humans modify it from the outside. Sybre has AI embedded within the system, capable of observing, reasoning about, modifying, and verifying its own code. We think this is an entirely new class of software — self-evolving software — and it's only possible because the source is open and the system is ours.

Yes, it's vibe coded

We say that openly. Every piece of this platform was built by non-developers directing AI — not by writing code from scratch. We've read the criticism: AI-generated code has scaling problems, security blind spots, and architectural gaps that surface when real users hit real workloads.

Here's what that criticism assumes: that the software needs to scale to thousands of users across multiple continents. That it needs database sharding, cross-region WebSocket routing, and load balancing — the kinds of hard engineering problems that take years of distributed systems experience to solve properly, and that justify the very high salaries of the engineers who specialize in them.

Sybre doesn't face any of those problems. Not because we solved them, but because the self-hosted model eliminates them entirely. Your Sybre instance serves your team — maybe 2 to 10 people on your local network. One database. One server. The infrastructure engineering that SaaS companies spend millions on simply doesn't apply when the software runs on a PC in your office.

The things AI builds well — business logic, user interfaces, API integrations, database operations — are exactly what a self-hosted business tool needs. The things AI struggles with — massive scale, distributed infrastructure — are problems that don't exist in this model.

Why we're sharing it

Building the framework — the scaffolding that everything else sits on — was the hardest part. The navigation system, the notification center, the credential vault, the task scheduler, the component standards, the AI project guides. Once that foundation existed, building new business tools on top of it became fast.

But that foundation took over a year of active development and thousands of dollars in AI processing costs to build. That's a year of trial and error, architectural dead ends, framework decisions, and hard-won lessons about what works and what doesn't. It's also thousands of hours of AI-assisted iteration — each conversation, each code generation, each debugging session costs real money in API usage.

We want to give other business owners that foundation so they can skip all of it — the year of scaffolding work, the thousands in AI costs, the architectural mistakes we already made and fixed — and go straight to building the tools their business actually needs. Not everyone will want to — and that's fine. But for those who are tired of renting software and ready to own it, the barrier shouldn't be "spend a year and thousands of dollars building infrastructure." With Sybre, you start where we are now, not where we started.