I'm building an AI financial assistant — here's how it's architected (would love your input!)

A few months ago, I got laid off and did the most janky thing ever: pasted my bank statements into ChatGPT to figure out if we could afford for me to take a break.

It kinda worked… but it also felt sketchy. And slow.
That got me thinking:

What if GPT could actually see your real finances — securely — and answer real questions about your money?

So I started building Ask Linc — a privacy-first AI assistant that connects to your accounts (via Plaid), pulls in live economic + market data, and lets you ask questions like:

“Are we spending more this month than last?”
“How long could we cover expenses if one of us lost income?”
“Are my CDs earning enough compared to bond yields?”

I’ve got a working beta now, and I’m here to sanity-check my architecture and learn from anyone who's been down a similar path.

🧱 Stack Overview

Frontend:

Next.js 15 (App Router)
TypeScript
Tailwind CSS
Deployed via Vercel

Backend:

Node.js + Express
Prisma + PostgreSQL
Hosted on Render

AI + Data:

GPT-4 (OpenAI)
Plaid API for bank/transaction data
FRED API for economic indicators
Alpha Vantage for live market + yield data

Security:

JWT auth, bcrypt, HTTPS
No sensitive data stored
GDPR-compliant delete + audit support

CI/CD & Dev:

GitHub Actions
Hot reloading, ESLint, Prettier
Automated deployments on Vercel + Render

🔐 Design Priorities

Token-based, read-only access via Plaid
All financial data encrypted in transit
Redis-style caching for rate-limited APIs
No user data used for training or stored unnecessarily
Privacy-first analytics (Plausible only)

👇 Where I’d love input

Prisma + Render: too many moving parts? Worth simplifying?
Alpha Vantage: anyone using better market/yield data sources?
Caching/syncing: how do you handle rate limits + stale data in multi-user apps?
Infra: stay with Express + cron jobs or move to serverless?
Security: any red flags from a compliance or risk standpoint?

Trying to keep things simple and scalable without overengineering.
Would love to hear how you’d approach this — especially if you’ve built fintech tools, GPT wrappers, or anything API-heavy.

If you’re working on anything similar (AI + real data), drop a link too — I’d love to check it out.