From a Lovable Prototype to a Production Mental Health Platform in 4 Weeks
A non technical founder had a landing page and a basic product built in Lovable. HouseofMVPs handled the product strategy and the build, and delivered a production platform with therapist matching, booking, chat and video, payments and admin, on TypeScript, AWS and Amazon Bedrock with a HIPAA aware architecture, in 4 weeks for $16,000 fixed. The client is not named at her request.
Client: Client name withheld at the founder's request
The Challenge
An AI app builder gets a founder to something that looks like a product quickly. The distance from there to a product that can responsibly handle mental health conversations is large, and most of it is invisible in a demo: how data is stored and who can reach it, what happens when something fails, and how the AI parts behave when a person in distress is on the other side. A non technical founder cannot easily judge that distance alone. She needed someone to make the product decisions with her, not only to write code to a specification she was not in a position to write.
Our Approach
We started with the product, not the code. Before anything was built we worked through what the first production version needed and what could wait, and wrote it down as a fixed scope with a fixed price. Then we rebuilt the product properly instead of extending the prototype: a Next.js web app and a Fastify API in strict TypeScript, PostgreSQL through Prisma, AWS for hosting, and Amazon Bedrock for the AI features so that model access sits inside the same cloud as the rest of the system. Because this is mental healthcare, the architecture was designed around health information from the start. Retrofitting that later is far more expensive than building it in.
What We Built
Delivery Timeline
Strategy and scope
Worked through the product with the founder and fixed the scope and the price in writing before the build started.
Architecture
Designed the system for health information from the start, on AWS with Amazon Bedrock for AI.
Build
Rebuilt the product as a production TypeScript codebase.
Handover
Delivered the production platform at the end of week 4.
Tech Stack
Architecture
webApp
Next.js with the App Router, Tailwind CSS and TypeScript.
api
Fastify, with Zod validation on every input.
database
PostgreSQL through Prisma, with 44 models and every schema change managed as a migration.
storage
S3 compatible object storage: MinIO in local development, Amazon S3 with KMS encryption in production.
ai
LLM calls go through Amazon Bedrock, inside the same cloud as the rest of the system, with no tracking of the data sent in those calls.
codebase
A Turborepo monorepo with pnpm workspaces and strict TypeScript everywhere.
Security
design
HIPAA aware architecture: decisions about storage, access and data flow were made with health information in mind from the first day of the build.
auth
Sessions are self hosted in PostgreSQL and carried in httpOnly cookies, so session data stays in the platform's own database.
access
Role based access control that denies by default: a role can do only what it has been explicitly granted.
inputs
Every API input is validated with Zod before it reaches business logic.
storage
Files in production are stored in Amazon S3 and encrypted with KMS.
ai
LLM calls run through Amazon Bedrock with no tracking of the data sent.
scope
HIPAA aware describes how the system is designed. Compliance is an ongoing programme that belongs to the organisation operating the product, and a development studio cannot certify it.
Key Takeaways
An AI app builder is a fast way to show an idea. It is not the same as a product that can carry sensitive data.
A non technical founder needs a partner for the product decisions as well as the code.
In healthcare, design for health information on day one. Adding it later costs more than building it in.
A fixed scope and a fixed price let a founder plan around a known number.
Deliverables
FAQ
Frequently Asked Questions
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