We read the premise correctly, including domain knowledge, usage scenes, emotional movement, and operational constraints.
Doui Lab / AI Product Direction
Same engine. Different outcome.
Using the same AI model does not create the same product. The difference comes from assumptions, what gets noticed, and what gets removed. Doui Lab turns those decisions into products people actually use.
Philosophy
Interpretation and judgment create the difference, not the model name.
As models become shared infrastructure, the gap in results is decided before and after the model itself. Doui Lab treats context reading, product judgment, and implementation for launch as one continuous flow.
Instead of adding complexity, we decide what to remove so the core stands out. The difference comes from cuts, not feature count.
We implement beyond the UI, including public pages, policies, measurement, and support paths, so the result reaches users without breaking.
Products
Product List
These are Doui Lab's public and planned products. One is built for ultra-fast spending capture, one preserves live memories, and one captures instant reaction, each shaped by a different set of product decisions.
iPhone Download
An ultra-light expense app built for amount-only entry. The recording step stays short, while the dashboard is designed to reveal patterns worth revisiting later.
iPhone Download
iPhone Download
An anonymous one-button app for releasing emotion. The urge to tap, what you see after tapping, and the path that keeps the experience going are designed as one flow.
The goal is not to repeat the same template. We want to create clearly different products from the same engine through different context and judgment.
Guides
Detailed guides with product scope, usage, and limitations
The site now includes longer pages that explain who each app is for, how it works, and where the boundaries are, instead of relying only on short promotional summaries.
This guide explains show browsing, setlists, attendance logs, stats, the unofficial fan-app position, and how the dataset is maintained.
This guide explains the amount-first workflow, local-first storage, who the app is for, and the current release scope for the planned App Store launch.
This guide explains anonymous one-button use, why region selection is manual, how serious mode and fuel work, and the main questions new users ask.