Can AI replace DataFast?

Build me a revenue attribution dashboard for one site, to replace DataFast. Requirements:

- Node + Express + better-sqlite3, one process behind Caddy on my own VPS.
  Server-rendered pages, no frontend framework, no build step.
- A tracker snippet under 2 KB: navigator.sendBeacon sends path, referrer and
  any utm_* params, keyed to a first-party visitor id in localStorage. No
  third-party cookies.
- Attribution is the whole point. Per visitor store first-touch and last-touch
  channel, from utm_source/utm_medium/utm_campaign, else by parsing the
  referrer host into google / x / reddit / hn / direct. Never overwrite
  first-touch.
- An /identify endpoint I call after signup with the user's email, which binds
  the anonymous visitor id to a customer row.
- A Stripe webhook for checkout.session.completed, invoice.paid and
  customer.subscription.deleted: verify the signature, match on email, write
  revenue against that visitor. Webhook secret and API key from .env.
- Dashboard on localhost behind one bearer token from .env: a channel table
  with visitors, signups, customers, MRR and revenue per visitor over 7/30/90
  days. Tables and one inline SVG bar chart, nothing else.
- Drop known bots against a user-agent blocklist before anything is counted. No
  accounts, no telemetry, one SQLite file I can copy off the box.
- Out of scope: cross-device identity stitching, multi-touch models, the live
  visitor feed, purchase-likelihood scoring, team seats and an MCP server. One
  domain, single-touch, single-device.
- README: the script tag, the /identify call, `stripe listen` for testing
  webhooks locally, and an honest paragraph on where the numbers lie · a
  phone-to-laptop journey counts as two visitors, cleared localStorage counts
  as a new one, and a customer who pays from a different address never matches
  at all.