[ SOFTWARE_DELIVERY ]

AI Requirements Gathering Tool

2024Developer PlatformsCapability

What it is

Interrogates a project idea into a structured requirements document, then generates from it.

Client work is shown without identifying imagery

[ THE_PROBLEM ]

Why this existed

Most project failure traces back to the gap between what the client said and what was buildable. That interrogation happens in someone's head, inconsistently.

[ WHAT_WE_BUILT ]

What we built

A project intake that generates clarifying questions, collects answers, assembles a structured requirements set through a chat interface with editing, and then drives generation from the finished specification — with project management and a full marketing site around it.

Project intake generating clarifying questions
Answer collection against each question
Structured requirements assembled through a chat interface with editing
Generation driven from the finished specification
Project management around the flow

[ HOW_IT_IS_USED ]

How a company uses it

The gap between "the client said they want a portal" and a buildable spec is where most projects go wrong. This makes the interrogation systematic.

Built with

Next.jsPrismaClerkOpenAI

[ COMMON_QUESTIONS ]

Questions clients ask

Can AI really gather requirements?

It can do the systematic part — asking the questions that always need asking, and noticing when an answer is missing or contradicts an earlier one. It cannot do the part that requires knowing the client's business or reading the room. Treating it as a checklist that never forgets is the right expectation.

Why make requirements editable rather than regenerating?

Because the human always knows something the model does not, and regenerating to fix one line loses everything else that was right.

Does the generated output get used directly?

The specification does. The generated code is a starting point — useful for scaffolding and for showing the client that their requirements produce something coherent.

[ RELATED_WORK ]