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Wire AI docs

How Wire AI works

Wire AI is an activation loop, not a single screen. A new user walks into a personalized onboarding, the AI adapts to what they tell you, and everything after that (the value bridge, the app features walkthrough, the reviews, the learning reports, the experiments) works to turn that first session into a user who sticks.

Activation is when a user reaches the moment your app pays off, and comes back. That is the number the whole loop moves.

The short version
Keep your base questions. Wire AI adds AI-tailored follow-ups per user, renders them as native cards, and then keeps improving the flow from the funnel it collects. It runs on the open-source Wire RN SDK and talks to a multi-tenant backend.
Inputs
What they answer
Onboarding questions
How they behave
In-app events
Where they came from
Acquisition source
Wire AI decides the next step
Weighs every signal, per user
Value bridge
You define the slides. The AI picks which each user sees.
App features walkthrough
You author the steps. The walkthrough plays the ones that fit their answers.
Reviews and feedback
Asks at a moment of value, routes unhappy users to a private channel.
The learning loop
A week of funnel becomes an analysis and a paste-ready update to the questions.
Feeds back into the next flow
Every finished flow feeds the funnel, and the funnel sharpens the next one.
01

Onboarding questionnaire

The flow opens with your base questions, rendered as themed native cards inside your app. Nothing looks bolted on. It is the first screen a new user sees, and it reads like part of your product.

02

The AI decides the next step

Every answer is sent to the Wire AI backend, which decides what to ask next for this specific user. A runner keeps a static plan; Wire AI tailors the follow-ups so a fitness user and a finance user do not walk the same path. Per-step validation keeps answers usable.

03

Value bridge

Mid-flow, a value screen reflects what the user just told you back at them, so the questions feel like they are already paying off. You define the slides once, roughly six of them, and Wire AI picks which ones this user sees from their answers. So the screen reads as personal without you writing a version per persona. This is the screen that turns a form into a reason to keep going.

04

App features walkthrough

Once the user lands in the app, an app features walkthrough points at the features that matter for the profile they just described. You author the steps once, each with its anchor, its copy, and the gesture it teaches, and the walkthrough plays the ones that fit. They fire at the point of need, not as an intro carousel nobody reads. Today you pass that selection yourself; as the server learns from the funnel, it returns the order straight from the onboarding answers.

05

In-app reviews and feedback

When a user hits a moment of value, Wire AI can prompt for an in-app review or a quick piece of feedback. You collect the sentiment while the good feeling is still fresh, and you route unhappy users to a private channel instead of the store.

06

The learning loop

Every finished onboarding feeds a funnel you can read. Wire AI turns a week of that funnel into an aggregate analysis of who your users are and where they drop, plus a paste-ready update to the questions themselves. The flow gets sharper the more it runs.

07

A/B/C testing

Run variants of the copy, the order, or the value screen against each other. Wire AI assigns users to arms server-side and tracks a per-arm goal, so you can see which version actually activates more people, not which one you liked writing.

What you actually see

The funnel and the experiments are not a mockup. Here is the console reading a live app that runs its activation on Wire AI.

console / funnel
Wire AI console funnel showing each onboarding screen, how many users reached it and dropped off, with AI-picked questions marked.
Every screen's drop-off, per user. The questions the AI picked are marked.
console / overview
Wire AI console showing the A/B/C experiments table and a Download insights.md export button.
The console: A/B/C experiments and a one-click insights.md export you paste into your AI.