One Missed Lunch. A Century-Old Problem. The Origins of Flight Optimal.
By Muharrem Mane, Founder & CEO, Flight Optimal
I didn’t intend to skip lunch that day. It just happened.
One moment I was stepping out of a conversation at the 2023 World Aviation Training Summit; the next, I was hunched over a table with a notebook, sketching ideas so quickly I barely noticed the hours pass. Lines, grids, constraints, little arrows. It looked like the scribbles of someone trying to break an impossible code. And in many ways, that’s exactly what it was.
Earlier that day, a pilot-training leader had walked me through his world: hundreds of students advancing through complex syllabi, instructors with constantly shifting availability, aircraft rotating in and out of maintenance, unpredictable weather, last-minute cancellations, simulators breaking, the necessity of regulatory compliance, and unyielding graduation deadlines. All of it, every moving part, was being managed in Excel.
I remember thinking: This is one of the most operationally complex parts of aviation. Why is it still being held together with spreadsheets and optimism?
That question was the beginning of everything.
The Gap No One Was Addressing
For many years before that day, as I built and marketed PlaneEnglish - the AI-powered aviation-training platform used by top academies to improve pilot communication skills -I saw the same imbalance emerge again and again. Airlines invested in teams of PhDs to engineer sophisticated optimization systems built around passenger-related scenarios: delays, reassignments, crew rotations, and network disruptions.
But the academies training the very pilots those airlines depended on had none of that support. Instead, their reality was heroic manual planning: whiteboards, spreadsheets, and an endless game of Tetris where the pieces never quite fit.
As pilot demand climbed, the situation became even more untenable. Academies ran highly structured programs - often with 300 students, 100 instructors, and more than 60 aircraft to manage, but were meeting the moment with tools never meant to operate at that scale.
Schedulers were spending hours adjusting flights one at a time.
Leaders were constantly guessing at future graduation timelines because there was no way to see the downstream impact of resource changes.
Maintenance teams were juggling aging aircraft while navigating new directives.
Students were at the mercy of systems that couldn’t reflect the complexity of their real-world progress.
It wasn’t sustainable, and everyone knew it. But the industry had accepted this dysfunction as part of the job.
I couldn’t. Not any longer.
The Moment the Vision Took Shape
That day at the summit, the question kept echoing: Why not build the scheduling engine this industry actually deserves?
As I filled page after page in my notebook, I started to see a path forward. Not a better-looking spreadsheet or a nicer whiteboard, but a true automated engine: one that could ingest every constraint, model all available resources, and produce schedules that were optimized, dynamic, and fully aligned with training logic.
The idea wasn’t to replace human planners, but to give them superpowers. Let the engine compute the most efficient path, then let planners make the fine-tuned decisions only humans can make. Automation and control, instead of one at the expense of the other.
By the end of that hour, I realized the vision was not only possible, but necessary.
From Notebook Sketches to a Working Engine
Turning a concept into a platform required a transformation of its own.
Early on, we discovered that most legacy systems used by academies lacked even basic APIs. To power true scheduling intelligence, we had to build everything from the ground up: the database, the onboarding flows, the maintenance profiles, the qualification tracking, the curriculum management. Every part of the system needed to reflect real operational complexity or the engine would produce elegant answers to the wrong questions.
This is where our partner academies became invaluable. They showed us details no spreadsheet could reveal: the ripple effects of late cancellations, the way linked events shape multi-day schedules, how seasonal weather reduces flight availability, how individual syllabi need custom pacing, how aircraft age changes maintenance reality, how instructors gain or lose qualifications day-to-day. Their insight wasn’t “feedback.” It was raw operational truth.
Together, we built a platform that could hold it all.
The Team That Turned Vision Into Reality
And while the spark may have come from a skipped lunch and a notebook full of sketches, the realization of Flight Optimal required a coordinated, multidisciplinary team.
Engineers architected the cloud-native, multi-tenant infrastructure that could scale with training demand.
Operations-research specialists modeled the dynamics of flight operations, translating constraints and resource interactions into optimization logic.
Our designers shaped an interface that felt simple on the surface but could reveal deep operational insight with a single click.
Our product team ensured every feature aligned with the realities of modern training environments.
Our partner institutions have been more than early adopters. They truly have been co-designers. They provided operational data, surfaced the nuances of real schedules, and helped refine workflows long before code ever reached production. Their fingerprints are evident across the entire platform.
Collectively, our team brings more than 40 years of experience across operations research, web development, database management, user-experience design, and aviation-training technology. When institutions adopt Flight Optimal, they’re not leaning on one person’s idea. They’re partnering with a dedicated organization prepared to support, evolve, and sustain the system for decades.
Flight Optimal is the product of a robust team committed to building the backbone of modern aviation training.
What Flight Optimal Has Become
Today, Flight Optimal is far more than the engine I first sketched over a skipped lunch. It’s a full training-management system built on a modern, cloud-native, multi-tenant architecture, and it’s capable of supporting the most demanding pilot-training environments in the world.
It can model the next 24 hours or the next 12 months.
It can show how adding or losing an aircraft affects graduation timelines.
It can capture student progress with precision, track instructor qualifications automatically, and project capacity across seasons.
It can handle daily dispatch realities and long-term resource negotiations with equal clarity.
But the goal hasn’t changed.
It’s still about democratizing the kind of operational intelligence airlines take for granted and bringing it to the academies that need it most at a fraction of the cost and with none of the engineering overhead.
Why This Work Matters
Every aviation academy shares the same essential mission: graduate pilots on time, safely, and at scale. But they haven’t had the tools to plan confidently. Schedulers were left to fight entropy by hand. Leaders were forced to make critical decisions with incomplete data. Students bore the consequences of delays that weren’t their fault.
Flight Optimal returns something precious to these organizations: the ability to see clearly.
Clarity in the schedule.
Clarity in the constraints.
Clarity in the pathway from today to graduation.
Everything changes when you replace guesswork with insight: training quality, operational efficiency, financial stability, and ultimately, readiness.
The Work Ahead
Our product roadmap is ambitious. We’re expanding deeper into recurrent training, type-rating centers, simulator-only operations, and military pipelines. We're building out documentation workflows, compliance support, and broader dispatch tools. We’re committed to being not just a scheduling solution but the backbone of modern aviation-training operations.
But even as the platform grows, I still think back to that notebook.
Because the heart of Flight Optimal hasn’t changed since the moment I realized what was possible:
This industry deserves tools built for the scale of its responsibility.
We’re here to build them. And we’re just getting started.