AI SaaS: tenancy, metering, and Stripe around your model
The model is the easy part. Isolation, usage billing, and a dashboard your customers can log into - that is the product. I ship that stack.
From demo to something you can charge for
A chat window on localhost is not a company. US buyers will ask who else can see their data, how you bill, and what happens when a job fails at 2am. I have already built this shape: Klean Data (connect a database, ask in English, approve the query) and the billing patterns in my writing on multi-tenant AI SaaS.
You stay the founder. I am the engineer who wires tenancy, Stripe, and the app so you can onboard the next customer without a custom deploy.
What “production” means here
Every model call is attributed to a tenant. Caps exist before the invoice surprises anyone. Secrets never sit in the browser. Background jobs retry. That is boring on purpose - it is why the product survives the first paying user.
What you get
- Tenant isolation so customer data never leaks across accounts
- Stripe Checkout, subscriptions, and metered billing for tokens or seats
- Postgres + Redis for durable state and rate limits
- Admin and customer dashboards in Next.js
- Auth, roles, and an audit trail on expensive model calls
How we work
01
Scope
We freeze the first paid workflow: who logs in, what they can spend, what you can see as the operator.
02
Build
Auth, tenancy, Stripe, and the AI path in one vertical. You can take a test payment before we polish.
03
Launch
Webhooks, dunning, usage caps, and a deploy you can run without me in the loop.
