We got tired of watching great operators run their businesses in spreadsheets.
We spent eight years working with fuel station operators, logistics groups, and retail chains. Every single one was running their business with some version of the same stack: a POS system, three spreadsheets, a manual payroll process, and a month-end close that consumed a week of someone's life.
AI changed what was possible. But the tools being built were aimed at enterprise software teams not the owner-operator with seven stations who doesn't have an IT department. We started Opero to close that gap.
We start with one industry. We learn how it actually runs the workarounds, the manual steps, the variance they quietly absorb every month. Then we build the system that replaces all of it. We don't build AI features. We build AI systems that own a workflow.
The principles that drive every product decision.
Outcome over output
We measure ourselves on cost reduced, hours saved, and decisions made faster not features shipped or lines of code written.
Operators over consultants
Every product is built with the people who run the business, not analysts who studied it. Designed for non-technical teams on day one.
Built to be boring
The best AI system is one you stop thinking about. It runs in the background and delivers the outputs. No dashboards to check if you don't want to.
One platform, every product
We don't rebuild the foundation for every vertical. One platform same data model, same AI layer, same security. Every new product plugs in cleanly.
Specific beats generic
Generic AI products produce generic results. We go deep in one industry before moving to the next. Depth is our moat.
Operators, engineers, and AI specialists.
A small team that moves fast, learns from operators every week, and ships systems that actually run.
Former operations consultant. Built systems for fuel and logistics operators for 8 years before starting AI Tech Solutions.
ML engineer. Previously built reconciliation systems at a tier-1 ERP vendor. Obsessed with making data pipelines invisible.
Ex-operations manager at a 14-station fuel group. Knows the close process better than anyone on the team.
Former ML researcher. Specialises in anomaly detection and time-series forecasting for operational data.
One platform. Many products. Zero migration headaches.
Every Opero product runs on the same underlying platform shared data model, shared identity layer, shared AI infrastructure. When Retail One ships, Fuel One operators don't migrate. They just turn it on.
