Why we exist
Most companies don't have an AI problem — they have an operations problem. Repetitive manual work. Systems that don't talk to each other. The same data typed in twice. Processes that only work because one person keeps them in their head. Technology can remove that friction, but only when someone takes the time to understand how the work actually moves.
We read the operation like operators and engineer the system like engineers.
LB Labs exists to close the gap between how a business really operates and what technology can make possible. Then we decide together what should be automated, what should be integrated, what should be redesigned, what genuinely benefits from AI, and what should be left alone.
What we keep finding
- Repetitive manual work
- Disconnected systems
- Duplicated data entry
- Slow internal processes
- Knowledge trapped inside people
- Software that doesn't communicate
- AI opportunities without a clear path
Our point of view
Understand before automating.
The audit comes before the build. If we can't explain your process back to you, we're not ready to change it.
Remove friction. Never add it.
A system that creates new work for the team it was meant to help has failed, however clever the technology inside it.
It has to work after the demo.
Production is the standard — monitored, governed, documented, and still earning its keep long after launch day.
Build around the business, not the tool.
The stack serves the operation. We fit technology to the way your team works, never the other way around.
You should own what we build.
Accounts, infrastructure and systems stay in your name wherever possible. No manufactured dependency.
The people
Every engagement is led by the two people who founded LB Labs — one reads a business the way an operator does, the other builds the way an engineer does.
Co-Founder | Operations & Commercial strategy
Experience · Expertise
Akif is a business operator and systems strategist with over 15 years of experience across operations, technology implementation, commercial delivery and business ownership.
His background spans safety-critical rail-signalling technology/ construction, automated retail and self-service systems, business development and operational leadership. This experience shapes his practical approach to AI: understand how the business operates, identify where time and revenue are being lost, and then determine what technology—if any—will create measurable value. His focus is building systems that support real teams, include clear ownership and human escalation.
Business Operations · Revenue · AI Systems · Practical Implementation
The operational lens: how work moves through the business, where time and revenue are being lost, what the numbers reveal, and what a system must do for the people relying on it every day.
Two perspectives, one team. The operational lens decides what a system must do for the people running it; the technical lens makes sure it holds up in production. A client gets both, in the same room, for the life of the engagement.
Partnership
Bring us the messy problem.
We want to work with ambitious companies that have meaningful operational problems — processes worth improving, systems that don't talk to each other, repetitive work that deserves better, and an appetite to build something properly.
- Meaningful operational problems
- Processes worth improving
- Disconnected systems
- An appetite to build properly