(03 / 08) — Full Case Study
Final Year Project — Master's (Software Engineering)

Psychology AI Platform

Designed and built a modern web platform with integrated LLMs for an AI chat assistant, real-time appointment tracking, pathology search, gender distributions, regional statistics, and visual insights.

Next.jsTypeScriptLLMsMongoDBNode.js
Cover — WebShot 01
Psychology AI Platform
Fact Sheet
Role
Product Engineer
Year
2024
Client
Health Startup
Platform
Web
Degree
Final Year Project — Master's (Software Engineering)
Stack
Next.js · TypeScript · LLMs · MongoDB · Node.js
The Showcase

A visual journey through the screens.

8 frames, capture by capture — how Psychology AI Platform actually flows, from first launch to final booking.

One dashboard for clinicians
Frame 01 / 08Web · browser
Frame 01Web View

One dashboard for clinicians

At a glance: today's appointments, pending diagnostics and flagged cases — arranged so the entire day reads left to right without scrolling for answers.

Ask the AI assistant
Frame 02 / 08Web · browser
Frame 02Web View

Ask the AI assistant

A clinical copilot that answers natural-language questions about patients, diagnostics and literature — grounded in the data the platform already holds.

Search the pathology library
Frame 03 / 08Web · browser
Frame 03Web View

Search the pathology library

A searchable repository of pathologies with prevalence, symptoms and linked cases, built for fast retrieval rather than archive dust.

Appointments & regions
Frame 04 / 08Web · browser
Frame 04Web View

Appointments & regions

Appointment pressure and regional distribution render as live charts, so capacity problems surface before the waiting room does.

Gender & outcome analytics
Frame 05 / 08Web · browser
Frame 05Web View

Gender & outcome analytics

Gender distributions and treatment outcomes are sliced visually — trends that would take hours of spreadsheets become a single glance.

Visual insights
Frame 06 / 08Web · browser
Frame 06Web View

Visual insights

Every dataset decays into a chart a clinician trusts — incidence, progression and comparisons in consistent, readable tokens.

Patient-level detail
Frame 07 / 08Web · browser
Frame 07Web View

Patient-level detail

Drilling into a single case keeps the context tight — history, status and actions on one focused surface.

Reports at a glance
Frame 08 / 08Web · browser
Frame 08Web View

Reports at a glance

Clear summaries rendered for review — the same data a poll of doctors would ask for, already shaped into a decision.

Overview

Mental health professionals needed a unified dashboard combining patient diagnostics, AI-powered analysis, and appointment management.

Next.jsTypeScriptLLMsMongoDBNode.js