Advoc8

Inspiration

“Your symptoms are probably normal.”

For many women, that sentence can be the end of a conversation they spent months trying to have.

While shadowing a patient appointment, we saw a woman walk in carrying a massive, ChatGPT-generated PDF of her medical history, filled with symptoms, medications, and timelines. She had turned to AI because she needed help organizing her story and making herself heard.

We asked: What if technology could help before the appointment, not just when someone is already overwhelmed?

That question became Advoc8.

What it does

Advoc8 helps women turn scattered health experiences into organized, actionable evidence for medical appointments.

Users can:

Track → Discover → Prepare → Practice → Advocate

They track symptoms over time, discover patterns worth discussing with a provider, and receive personalized questions and talking points.

Advoc8 also includes a chatbot that lets users practice their questions and conversations before an appointment, helping them build confidence and feel more prepared to speak up.

Finally, users can generate a concise Evidence Sheet summarizing their symptoms, patterns, and key concerns to bring to their provider.

Advoc8 isn't designed to diagnose users. It's designed to help them communicate their experiences and advocate for themselves.

How we built it

We built Advoc8 using Next.js, React, JavaScript, and Tailwind CSS.

Our MVP uses locally stored symptom data and a lightweight pattern-analysis layer to identify trends and relationships across entries. For example, if two symptoms repeatedly occur together or severity changes over time, Advoc8 can surface that relationship as something worth discussing.

We also built an interactive chatbot for practicing appointment questions, along with an Evidence Sheet generator that transforms tracking data and insights into a structured, appointment-ready document.

Challenges we ran into

Our biggest challenge was balancing usefulness with responsibility. Healthcare is high-stakes, so we wanted Advoc8 to surface observations and questions without presenting them as diagnoses.

We also had to make complex health information feel simple and actionable while building a complete workflow within a short hackathon timeframe.

Accomplishments that we're proud of

We're proud that Advoc8 goes beyond symptom tracking. A user can go from logging a symptom → discovering a pattern → preparing questions → practicing with a chatbot → generating an Evidence Sheet all in one experience.

We're especially proud of the practice feature because knowing what you want to ask isn't always enough. Advoc8 helps users actually rehearse the conversation and build confidence before walking into the room.

What we learned

Building Advoc8 changed how we think about AI in healthcare.

We initially thought AI's biggest value would be helping someone find an answer. Instead, we found something more powerful:

Helping someone ask a better question.

We learned that good healthcare technology isn't always about making the medical decision. Sometimes it's about helping someone communicate clearly enough to be part of that decision.

What's next for Advoc8

Our next step is moving from local data to a Supabase-backed database, allowing users to securely maintain longer-term health histories.

We also want to incorporate machine learning to identify more nuanced relationships between symptoms over time. Future models could surface potential connections and trends that users may want to discuss with their provider.

These predictions would remain signals, not diagnoses, keeping the provider at the center of decision-making.

Ultimately, we want Advoc8 to help women walk into every appointment prepared, informed, and ready to advocate for themselves.