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Selected Work 04

AI Chatbot and Training CMS

ChatSquare

Helping SMEs train and manage AI without technical complexity.

Product StrategyEnd-to-end UX/UI DesignPrototypingProduct Website
Role
Product Strategy / UX/UI Design / Prototyping / Product Website
Platforms
Website Chatbot / CMS Platform / Responsive Product Website
Target users
SMEs / Non-technical users unfamiliar with AI training
Outcome
One coherent journey for setup, training, review and product communication.

01

Project snapshot

The product, people and scope—at a glance.

Project
ChatSquare
Product Type
AI Chatbot and Training CMS
Target Users
SMEs / Non-technical users / Teams unfamiliar with AI training
Platforms
Website Chatbot / CMS Platform / Responsive Product Website
My Role
Product StrategyEnd-to-end UX/UI DesignPrototypingProduct Website

02

Overview

A manageable way to work with AI.

ChatSquare helps SMEs create, train and manage an AI chatbot without requiring technical knowledge.

03

The challenge

Make complex training feel clear.

AI training can feel complex and inaccessible to non-technical users. The challenge was to turn chatbot setup, knowledge management and response refinement into a clear, manageable workflow.

04

My role & process

One continuous product-design journey.

I defined the product direction and connected the chatbot, training CMS and product website from system flow through developer handoff.

Product Strategy + System Flow + Information Architecture + UX/UI Design + Prototyping

01Product Strategy
02System Flow
03Information Architecture
04Wireframes
05UI Design
06Interactive Prototype
07Developer Handoff

05

Product strategy

Clarity, control and a lower barrier to entry.

Three principles kept the experience focused on what non-technical teams need to understand and do.

01

Simplify Setup

Guide users without technical language.

02

Centralise Training

Use the CMS as the main knowledge-management workspace.

03

Keep Users in Control

Make content, training status and responses easy to review and refine.

06

Product flow

From business content to continuous improvement.

The loop keeps knowledge, publishing and response refinement connected instead of treating AI training as a one-off setup task.

01Add Business Content
02Organise Knowledge
03Train Chatbot
04Publish Website Widget
05Review Conversations
06Refine Responses
Update Business Content

Refined responses feed back into the source knowledge.

07

Promotion website & chatbot demo

ChatSquare Promotion Website & Chatbot Demo

The promotional website introduces ChatSquare’s core features and includes an interactive chatbot demo, helping prospective users understand the product through direct experience.

No conversation data is collected or stored by this portfolio page.

Official experience provided by chatsquare.aiOpen Official ChatSquare Demo

08

CMS user flow

A clear path from review to chatbot training.

The CMS connects chat review, Q&A training, reporting and settings from one dashboard, with the main training journey highlighted throughout the map.

Rectangle: ScreenRounded rectangle: ActionDark node: Status outcomeBlue route: Primary training journey

Focused CMS map

Review, train and resolve.

The primary route connects conversation review to Q&A training, while reporting and settings remain available from Home.

  1. The primary journey moves from login and Home through chat records, conversation review, Q&A creation and training status.
  2. Custom Q&A offers a direct route to create or edit a training record.
  3. Reports lead to report details and export, while Settings controls email notice frequency.

09

CMS UI showcase

The operational centre of the product.

The CMS turns AI training into familiar workspace tasks: organise knowledge, check progress and improve responses from real conversations.

10

Outcome & reflection

Make AI feel like a manageable product task.

Outcome

The final experience connects chatbot setup, knowledge training, response review and product communication into one coherent journey, helping SMEs manage AI without understanding the underlying technology.

Reflection

The project reinforced the importance of translating AI concepts into familiar tasks, visible feedback and clear user control.