WISP GUIDE · FLAGSHIP CASE STUDY · 2026

Wisp

Building a bilingual psychology product from behavioral logic to a measurable, deployable system.

ROLE Product owner · Product analytics · UX · Systems · Build
23 QUESTIONS · 2 LANGUAGES
FUNNEL SNAPSHOT · AUGUST 2026 · HISTORICAL, NOT REAL-TIME
101RECORDED STARTS
70COMPLETIONS
69.3%COMPLETION RATE
8PURCHASE REQUESTS

From structured answers to useful guidance.

This interactive system view uses the existing product flow to show the input, deterministic logic, and controlled output without inventing product screenshots.

WISP / PRODUCT MOTION23 QUESTIONS · 2 LANGUAGES
Structured responses captured
INPUT · 23 RESPONSES

Structured responses captured.

Wisp collects 23 answers about connection, conflict, trust, closeness, and emotional safety. The assessment works in both English and Burmese.

CONNECTIONCONFLICTTRUSTEN / MY
AUTO LOOP · PAUSES ON HOVER
01

Overview

Wisp Guide is a bilingual relationship self-insight product for Myanmar users. I owned the product flow, behavioral logic, UX writing, analytics, authentication, paid-session operations, AI-personalization architecture, and production delivery.

02

The problem

Relationship advice is often generic, while clinical language can feel distant. The experience needed to make a sensitive subject approachable and private without presenting a result as diagnosis or therapy.

03

The product

A guided 23-question assessment turns structured responses about connection, conflict, trust, closeness, and emotional safety into an understandable relationship-pattern result and practical next steps.

04

Assessment flow

The flow reduces a complex topic into one decision at a time: answer the assessment, classify the primary and secondary patterns, explain the result, then offer a clear next action.

05 · SYSTEM ARCHITECTURE

A product chain with explicit responsibilities.

Classification stays deterministic.

Structured psychology rules compare answer signals to identify the primary pattern, secondary tendencies, triggers, and emotional needs. The core classification is reproducible and does not depend on generative output.

AI works inside a controlled boundary.

AI supports explanation and tone after the structured result is known. Approved wording, explicit product limits, and fallback content keep personalization from becoming diagnosis or uncontrolled classification.

PRODUCT ANALYTICS · AUGUST 2026 SNAPSHOT

The funnel shows where users progressed.

These verified historical counts provide iteration evidence. They are presented as a dated snapshot and are not implied to be live metrics.

07

Admin & operations

The product includes the operational path around paid sessions, purchase requests, administration, release workflow, and cost controls—not only the user-facing assessment.

08

Authentication & ownership

Google authentication and SQLite-backed ownership connect a result to the right user while keeping access and operational data within the product system.

09

Localization

English and Burmese are treated as product states rather than an afterthought. Assessment content, result wording, and guidance are designed to remain understandable across both languages.

10

Production delivery

React interfaces, a Python/FastAPI service, SQLite data, Cloudflare delivery, and a secured VPS release workflow form one deployable product chain.

11 · RESULTS

A working product with evidence for the next iteration.

Wisp moved beyond a concept into a bilingual, authenticated product with a measurable assessment funnel and an operational path around paid guidance.

  • 01 Live English and Burmese product flow
  • 02 Verified 101-start / 70-completion snapshot
  • 03 Deterministic classification with controlled AI support
  • 04 Authentication, ownership, analytics, and operations

The product is the whole chain.

The strongest product work is not a screen. It is the connection between user need, decision logic, careful wording, operations, measurement, and sustainable delivery.

See the analytics workflow.

Personal Intelligence Lab documents how raw datasets move through profiling, cleaning, analysis, KPI framing, and decision-ready reporting.