Why We're Building SybreSoft
The subscription bill that broke us
At one point, we were paying for over fifteen SaaS subscriptions. Ad management. Inventory tracking. Settlement reconciliation. Accounting. Listing tools. Shipping calculators. Photo editing. And a handful of tools we’d signed up for, used twice, and forgotten to cancel.
The total monthly bill was staggering. But worse than the cost was the fragmentation. Each tool had its own data silo. Getting a complete picture of the business meant exporting CSVs from six different dashboards and stitching them together in — you guessed it — another Excel spreadsheet.
The Excel tipping point
Every business has that Excel file. The one with 47 tabs, VBA macros that nobody fully understands, and a formula chain so deep that changing one cell takes 30 seconds to recalculate. Ours was a settlement reconciliation tool that matched Amazon payouts against QuickBooks entries.
When it broke — and it broke regularly — fixing it consumed days. Not hours. Days. Because understanding what went wrong in a complex Excel model requires understanding every formula, every reference, every macro. It’s archaeology, not debugging.
Then one day, we fed the entire Excel file to an AI coding assistant. “This is broken. Figure out what’s wrong and fix it.”
It found the issue in about 90 seconds. A VLOOKUP was referencing a range that had shifted when we added a new column three weeks earlier. A cascade of downstream formulas were pulling bad data. The AI identified the root cause, traced the impact, and suggested the fix.
That was the moment we realized: if AI can debug this nightmare in 90 seconds, what else can it build?
The experiment
We started small. We took the settlement reconciliation Excel tool and asked AI to rebuild it as a web application. Not a toy prototype — a real tool with a database, proper error handling, scheduled execution, and notifications when things completed or failed.
It worked. Not perfectly on the first try, but the iteration cycle was hours instead of weeks. Each version was better than the last. Within a week, we had something that was more reliable, faster, and easier to use than the Excel original.
So we kept going. The ad management tool. The inventory tracker. The listing creator. One by one, each SaaS subscription became a candidate for replacement with a custom-built, AI-assisted alternative.
What we learned
Three key insights emerged from this process:
1. You don’t need to start from scratch. The hardest part of building custom software isn’t the features — it’s the infrastructure. Navigation, user management, notifications, scheduling, credential storage, database connections. Sybre provides all of that as a foundation, so AI can focus on building the actual business logic.
2. Gradual migration works. You don’t need to replace everything at once. We migrated one tool at a time, running old and new in parallel until we were confident. Some tools migrated in a day. Others took a few weeks. The important thing was that the pace was ours to set.
3. AI gets better, and so does your platform. Every tool we built became a little better over time as AI capabilities improved. Because we own the code, upgrading is just a conversation: “make this faster,” “add this feature,” “fix this edge case.” No feature requests into a vendor’s black box. No waiting for the next release cycle.
What SybreSoft is
SybreSoft is the result of that experiment, packaged so others can do the same thing. It’s a locally-hosted business management platform with AI-assisted development at its core. The scaffolding is ready — you just need to start building.
We’re documenting everything as we go. Architecture decisions. Migration strategies. The tools we’re building and how we’re building them. Follow along on this blog, and if you’re interested in owning your business software instead of renting it, get in touch.
The SaaS era gave us incredible tools. But the AI era is giving us something better: the ability to build our own.