The story

Building since 13. Working since 14. Choosing the harder path ever since.

The long version. Every chapter here trained a different part of what Rōvn needs from me: code, crews, markets, a locker room after a loss, and three years inside a regulated buyer. Read it top to bottom or jump around.

Beginnings

My path did not begin with a startup title.

I grew up close to entrepreneurship, began teaching myself to build software around 13, and started working formally in my father’s company at 14.

Best SARL showed me the part of business people rarely put in founder stories: people have to show up, customers expect delivery, contracts carry consequences, and somebody has to own the problem when the plan breaks. I eventually led about 22 people inside a 60-plus-person operation connected to work in the United States, France, and Gabon. Landscaping, construction, operational services, and government contract work won on bids, not on relationships.

Since then, I have kept moving through different systems and learning each one from the inside. Markets taught me to think in probabilities and to respect a drawdown. Football taught me to come back after losing. Enterprise healthcare taught me that a technically good product still has to earn trust. Rōvn is where those lessons finally meet.

Age 13

Learning to make ideas real

I started with Roblox games, websites, scripts, and automation. The tools changed, but the impulse did not: understand how a system works, then see what I can build inside it.
Age 14

Responsibility before a founder title

I worked throughout high school inside Best SARL. What began as early exposure became direct responsibility for people and execution across landscaping, construction, and operational services. At 14 nobody cares that you’re 14. The work is done or it isn’t.
Age 15

My own money in the market

Binary options first, then equities, crypto, options, and futures. The market grades you every single day and never rounds up. That is where I learned to think in probabilities instead of stories.
2021

Returning to finish the job

After Collins Hill lost the 2020 Class 7A state championship, I returned at defensive end for the next season. We finished 15-0, won the first state title in school history, and ended No. 3 nationally in multiple polls.

Team roster GHSA champions
2022

Choosing the less conventional path

I graduated Collins Hill with a 3.9 GPA, AP Scholar and National Honor Society recognition, plus work across DECA, FBLA, STEM, and robotics. I was accepted to leading universities across the Southeast and beyond, including Georgia Tech, Duke, Emory, Wake Forest, and UGA.

I began at Georgia Tech, moved closer to home to create more room for ventures already underway, and ultimately left college to build full time. The conventional path was available. I chose execution.
2023

Learning operations wherever the work was real

At Jackson EMC, I worked as an Operational Technology intern around IT and OT systems supporting a regional electric utility. Through Prezi Digital, I worked on reputation, growth, and customer acquisition for metro Atlanta businesses.
2023 to 2026

Three ventures and a day job

Prezi Capital was the vehicle: BOVYN, my own trading, and Prezi Digital. I ran all of it while working full time in cardiovascular-renal sales at Boehringer Ingelheim. In 2024, across everything, I made $810K.

The decision that still explains me

Losing once made finishing matter more.

I had been academically accelerated after skipping sixth grade. When we lost the state championship in 2020, I had a real choice about whether to move on. I came back. The lesson was never that every unfinished thing deserves another year. It was learning to recognize the ones that do, then giving them everything.

Built before Rōvn

BOVYN began with a harder question: could a discretionary market read become a deterministic system?

By the time I was trading NQ, ES, and GC every session, I cared less about any single trade than about whether the read itself could be specified precisely enough to test, and then to run without me.

BOVYN was the answer. I wrote the core in Python around SLAM, my own methodology, and built the rest of the stack around it: the data pipeline, the feature layer, the rule engines, the consensus grader, the risk manager, the execution bridge, and the subscriber product on top.

Market data

Structure and options features

Rule engines

Consensus grade

Risk sizing

Execution

Measurement

Data

Databento futures history for research, roughly fifteen years of it, and a live feed in production. Tick size, tick value, and point value handled per instrument across NQ, ES, YM, RTY, CL, GC, and SI.

Features

Market structure made explicit: fractal pivots, liquidity sweeps above and below prior highs and lows, and session windows from Asia through the New York afternoon. Options-derived context alongside it: dealer gamma-exposure walls and implied-volatility targets that shape where price can and cannot travel.

Engines

ICT concepts I once read by eye, rewritten as deterministic conditions with explicit invalidation. Seventeen independent engines, each one a setup definition that either fires or does not. No indicator soup, no discretion at runtime.

Consensus

Engines vote. A signal ships only when the consensus score clears a threshold, and it carries its grade, entry zone, stop, three targets, and the reasoning behind the grade. Below the bar, the system stays silent.

Risk

Position size is derived from account risk percentage and stop distance in ticks, never from conviction. A guardian tracks the high-water mark, pauses after consecutive losses, and kills the session when a limit is hit.

Execution and measurement

Deployed on a VPS with a broker bridge into funded futures accounts. Every signal is logged with its entry, stop, targets, and outcome, so the system is judged on what it did, not on what it looked like on a chart.

Archived BOVYN signals dashboard showing graded setups with entry, stop, and targets — Archived BOVYN client, 2026. React and TypeScript, public on GitHub. The engines and execution run privately.

Then I sold it

200+

paying customers, acquired organically through TikTok, Instagram, and trading communities. No paid acquisition.

$10K

monthly recurring revenue, $11.5K at peak. Tiered subscriptions from real-time signals to auto-execution. I ran the live reviews, the journal and alert tooling, support, and retention myself, then wound it down to build Rōvn.

BOVYN client repository Prop firm scoring tool How it was built

Learning sales deliberately

I went inside regulated healthcare because building was only half the job.

“I wanted to learn how trust is earned, how sophisticated buyers evaluate a product, and what it takes for a good idea to move through a real institution.”

From August 2023 through March 2026, I worked in cardiovascular-renal sales at Boehringer Ingelheim across a Florida territory. Physicians, clinical detailing, account development, and a market where every word is regulated. I came in through the door most people never take on purpose, because I wanted to be sold to by the best and then learn to do it.

Technical merit is not enough. Adoption depends on evidence, stakeholder alignment, timing, compliance, and the ability to explain complicated value clearly. Those lessons now shape how I build and sell Rōvn.

See my professional history

The work now

Rōvn is not a pivot. It is where the whole path converges.

The nurses in my family gave me personal proximity to healthcare. Boehringer gave me commercial proximity. Then the discovery work behind Rōvn showed me the same structural problem from every side.

Healthcare repeatedly rebuilds the same professional from scratch. Licenses, certifications, work history, permissions, requirements, and readiness live across disconnected systems. Professionals keep resubmitting evidence, while each organization still needs its own rules and decisions.

Rōvn is the AI-operated hiring network and workforce system for healthcare. It is designed around a continuing professional identity and a governed path from opportunity to approved work.

Professionals control the proof.

Evidence can be reusable with consent instead of recreated for every opportunity.

Organizations keep authority.

Every facility retains its own policies, requirements, reviews, and final decisions.

Agents operate authorized work.

Automation should move permitted workflow forward without inventing regulated authority.

Explore Rōvn Read the thesis

Early teens

Quant and systems builder

Python rule engines, backtesting on Databento history, risk and execution systems, a TypeScript and React product, Pine Script, Java, and C++.

Family operations

Best SARL

Started at 14. Later led about 22 people inside a 60-plus-person operation spanning work across three countries.

2023

Jackson EMC

Worked around IT and Operational Technology infrastructure supporting a regional electric utility.

Built and sold

Prezi Digital

Helped metro Atlanta businesses with reputation, growth, social media, and customer acquisition.

2023 to 2026

Boehringer Ingelheim

Nearly three years learning cardiovascular-renal sales, regulated communication, and enterprise adoption.

Follow the work

The best profile should keep getting more convincing when you open the links.

RōvnCurrent company work BOVYNPublic client repository BOVYN ExtractorProp firm scoring tool LinkedInProfessional history Collins HillFootball roster GHSA2021 Class 7A champions

The next chapter

I’m building for people who know trust is operational.

If you are building healthcare, workforce, identity, or other systems where the details carry real consequences, I want to know what you see.

Book a conversation Read the essays