Quell.

The problem

People with chronic GERD get partial relief from a PPI prescription and then hit a wall. Root-cause guidance exists — functional medicine — but it costs $250–750 per visit with no insurance, so most users turn to Reddit, YouTube, and Google, where the information is overwhelming and contradictory.

Existing apps like Cara Care are passive loggers: they record what happened but never tell you what to do. There's no continuity — every practitioner encounter starts from scratch — and no structured, personalized protocol. Users are left confused about which of 20+ commonly cited supplements are right for them, and identifying personal triggers is slow and unstructured.

The solution

Quell is an AI assistant for chronic GERD that combines intake, a post-form consult, an evolving action plan, monthly check-ins, and an on-demand chatbot. It uses the user's own health record for context and aims to help them understand triggers and root causes over time, rather than relying on generalized apps or indefinite medication.

After a structured intake form, the AI asks a few targeted follow-ups, runs a testing bridge suggesting 0–2 relevant tests, then generates a plan across six sections — Your situation, Diet, Lifestyle, Supplements, Worth testing, and The path forward — with the reasoning behind each recommendation visible and tied to what the user shared. The design emphasizes tailored guidance while avoiding unsafe medical advice and escalating to doctors when appropriate.

How it works

Quell uses GPT-5, chosen for strong multi-turn instruction following (critical for the form → follow-up → plan sequence), a low hallucination rate, native PDF and image reading for lab uploads, and a large context window that holds full intake and check-in history. All calls run server-side via Next.js server actions, behind a provider abstraction layer that allows swapping models without touching feature code.

The GERD functional-medicine framework — root causes, dietary interventions, evidence-supported supplements, and red flags — is baked directly into the system prompts rather than retrieved via RAG, which adds complexity without benefit at MVP scale. Safety guardrails are non-negotiable: qualifying language throughout, no prescription-change instructions, and immediate doctor referral on any red-flag symptom. Evaluation combines human review, an LLM grader, and deterministic scripts, run before every prompt change.

Who it's for

Quell is B2C, for people with chronic GERD seeking a root-cause or holistic approach — typically 28–55, health-aware, willing to make lifestyle changes, and frustrated that conventional care has only suppressed their symptoms.

The intended experience supports users regardless of the direction they want to try, accumulating context across every interaction — intake, protocol, and check-ins — in a way no individual practitioner can replicate affordably.

Why it matters

The tailwinds are real: growing interest in root-cause health, mainstream gut-microbiome awareness, and LLM capability enabling personalized guidance at scale. The gut health market is projected to grow from $71.2B to $105.7B by 2029, though the GERD therapeutics segment itself grows slowly and remains pharma-dominated, with its digital layer largely uncaptured.

Quell is a pre-revenue startup planning a ~$20/month subscription, later layering in affiliate revenue on lab tests and supplements. Its defining risk is staying in the medical-education lane rather than the medical-advice lane — which is exactly why careful prompting and evaluation are central. The launch plan is to share it free in GERD-related Reddit communities to gather early feedback.

At a glance

Project

Quell

Built by

Sam Holdahl

One-liner

Quell is an AI assistant for people with chronic GERD that combines intake, consultation, action plans, monthly check-ins, and an on-demand chatbot.