AI Healthcare Companion

Noodle AI (Co-founder), 2023 · Case study by Will Dzierson

Tags: TypeScript, UX, Prototyping, LLMs, AI, Software Development

Project link: https://www.noodleai.app/videos/noodle_walkthrough_2.mp4

My contribution

I co-founded Noodle and led the end-to-end design and co-lead engineering. I designed the app and co-built the platform using Next.js (TypeScript), Tailwind, and Supabase/Postgres with PGVector for RAG, along wtih contract engineers.

For AI, we integrated multiple LLM engines — OpenAI, Hugging Face (Meditron-7B/Mistral), and Claude — depending on the task. Added Twilio for WhatsApp-based capture, Deepgram for voice transcription, and RapidAPI for image tagging, OCR, and recognition. The multimodal voice experience was built in Swift.

The work

Founded in 2023, Noodle started as a RAG-based note-taking app and evolved into something more ambitious: a platform designed to give patients real ownership of their health information. The focus shifted to people managing complex, multi-specialist conditions — the kind that generate scattered records, forgotten instructions, and fragmented data across providers.

The core insight was that health record balkanization is the root problem. Noodle addresses it by letting people capture and consolidate health events through whatever channel is easiest — web app, WhatsApp, voice, or images — and then surfaces that information through a conversational UI, making it genuinely useful rather than just stored.

Working with my co-founder, Julz Bautista, we raised an angel round and generated significant interest from partners and members of the healthcare community. The platform leverages LLMs, vector search (RAG), personal health journaling, health record consolidation, and self-sampling to help surface actionable insights and enable more meaningful interactions between patients and their physicians.

Noodle has since dissolved. This is historical work.

Images and video

• The Noodle marketing site and mobile experience — designed to communicate the core value proposition to patients managing complex, ongoing health conditions.
• [VIDEO] A full walkthrough of the Noodle app — demonstrating the end-to-end experience from logging a health event to asking the assistant a follow-up question and getting a context-aware response. Built in Cursor + Swift for iPhone.
• [VIDEO] An example use case, where the user is able to easily summon the piece of information they're interested in by asking Noodle to review their after visit summary and share the doctor's name.
• The RAG-powered health assistant at work — generating a structured summary of a patient’s pain history and pulling relevant context from their logged records to inform the response.
• From the investor pitch deck — introducing Noodle’s mission to empower patients to centralize, better interpret, and derive value from their health information.
• A research slide from our pitch deck framing the core problem — patients routinely deal with too much information that’s rarely centralized, often poorly understood, and too easily forgotten.
• The reality Noodle was built to solve: patient health information is paper-based or scattered across multiple apps, making it nearly impossible for patients to recall, share, or act on their own data
• Market research backing the problem space — 83% of patients forget critical health information after appointments, with $236B in costs tied to patients unable to process their own information and $100B lost annually to non-adherence.
• A technical architecture diagram showing how Noodle uses NER tokenization to extract and tag structured entities from unstructured patient input — enabling more precise RAG retrieval and clinical context-building.
• User discovery work mapping a pregnancy persona — one of several complex condition scenarios we used to define what "managing your own health knowledge" actually looks like in practice.