MAIA

In the spring of my senior year at UCF, I took an engineering entrepreneurship class that had one premise: take a real problem, talk to real people, and figure out whether a business could exist around your solution. The class focused entirely on pre-seed work — no building, no code, just discovery. Over the semester, my team of five designed a product concept, validated it through dozens of interviews, and presented to experienced entrepreneurs every single week.

The class

The structure was intense. Every week we stood up in front of the class and pitched — not to other students playing along, but to people who had actually done it. Our professor had founded and sold two companies for over $10 million each. Guest panelists included a CEO who had secured investment on Shark Tank, an executive at a hedge fund focused on technology investments, and other successful founders and operators. They didn't give polite feedback. They pressure-tested our assumptions, challenged our market sizing, and picked apart our business model in real time.

The goal was never to build the product. It was to learn the disciplines that come before building: how to identify a real problem, how to perform user interviews that surface honest pain points instead of polite agreement, how to iterate on a business model, and how to pitch investors convincingly.

The problem

We zeroed in on private medical practices. Through our research and interviews, a consistent theme emerged: increasing administrative burden is making it harder and more expensive to privately practice medicine. Physicians in private practice spend roughly 40% of their work time on administrative tasks. Prior authorizations alone require around 20 hours per week outside of clinic hours. Over half of physicians report burnout driven primarily by bureaucratic work, and that burnout costs the healthcare system an estimated $4.6 billion annually.

Private practices get hit the hardest because they lack the corporate infrastructure that large hospital systems use to absorb this overhead. The result is less time with patients, higher costs, and practices that struggle to stay independent.

37 interviews

We conducted 37 interviews with medical practices across multiple specialties — internal medicine, family medicine, oncology, hematology, and nephrology. These weren't surveys or cold emails. We sat down (or got on calls) with physicians, office managers, and administrative staff to understand their day-to-day workflows in detail.

What we heard consistently: the administrative workload is unsustainable. Practices that should be focused on patient care are instead drowning in medical coding, prior authorizations, clinical documentation, fax management, and patient communication overhead. One oncology-focused finding stood out — up to 97% of their services require prior authorization, with a single academic medical center spending nearly $500,000 annually just on the prior authorization process.

These interviews shaped every aspect of our solution and business model. Each week we refined our understanding, adjusted our value proposition, and brought sharper questions to the next round of conversations.

The solution: MAIA

We designed MAIA — Medical Administrative Intelligence Assistant — an AI automation system that would integrate directly with electronic health records (EHRs) to handle the administrative workflows that consume so much physician and staff time.

MAIA was designed around five core capabilities:

• Medical Coding — Review clinician notes, generate accurate medical codes, and submit for payment
• Prior Authorizations — Draft prior authorizations using context pulled directly from the EHR
• Clinical Note Drafting — Automatically draft and submit clinician notes upon approval
• Fax Automation — Manage inbound and outbound faxes and organize documents for accurate record keeping
• Patient Communication — Keep patients informed with updates on their care plans

The business model

We developed a subscription-based credit economy. Practices would subscribe at tiers ranging from $1,500 to $6,000 per month, each including a pool of credits. Different tasks consumed different credit amounts — a prior authorization cost 1.25 credits, medical coding cost 0.75 credits per document, and clinical documentation cost 0.075 credits per note. The model was designed for recurring revenue with low friction to expanding usage.

Our market analysis sized the opportunity at $73 billion across our target customer archetypes within private practice, with a path to $40 million ARR at just 3% market capture. The value proposition was concrete: reduce a practice's administrative staffing needs by roughly 66%, translating to hundreds of thousands of dollars in annual savings per practice.

What I took away

This class taught me things that writing code never could. Learning how to interview users without leading them, how to separate what people say they want from what they actually need, and how to stand in front of experienced operators and defend your thinking under pressure — those are skills that have shaped how I approach product work ever since. The weekly pitch sessions with successful entrepreneurs forced rapid iteration and eliminated the comfortable ambiguity that early-stage ideas tend to hide behind.