Go ahead and try it. No sign-up.

These three run the same way the AI features I build for clients do — same limits, same transparency.

Problem → product outline

Describe one business problem in your own words. What comes back is an outline of a first version: who it's for, the core flow, what's in and deliberately out, the technical approach, a time estimate, and the risks worth watching.

A real result: a warehouse stock problem in a spreadsheet, answered with a first-version design. This is the opening; the full answer runs twice as long.

Ask about those 86 projects

Ask anything about what I've built. Answers are assembled from the same catalogue the Catalogue page uses — so if I haven't built something, it will say so rather than invent it.

A real result: asked about payments, answered with the projects that exist and their stacks, then honest about what has not been built.

Raw data → dashboard

Paste any table — a copy straight out of a spreadsheet is fine. What comes back is a dashboard you can click, with chart choices that suit the shape of the data.

A real result: six rows of revenue and transactions pasted as they were, turned into a dashboard you can read.

Transparency

How this lab works

If you're from the IT team, this is what you usually want to know before typing anything into someone else's box.

API key: held on the server, never sent to the browser
Backend: bound to 127.0.0.1, reachable only through Caddy
Usage limits: rate-limited per IP address, plus a global daily ceiling
Storage: request contents aren't stored; only usage counts are recorded
Dashboard: your data is processed in the browser — only the column structure is sent
Models: chosen per case among providers such as Anthropic and DeepSeek

If the daily ceiling is reached, the box will say so plainly rather than failing quietly.