Chongsun Yu | Portfolio

💬

cs-ai-chatbot

ArchivedAI PythonFastAPI

AI-powered CS chatbot prototype — evolved into cs-ai-dashboard (above). Claude API + RAG, 10 markets, fraud detection, smart escalation. Prototyping role completed.

cs-ai-chatbot/
├── app/
│ ├── main.py
│ ├── routers/
│ │ ├── chat.py
│ │ ├── escalation.py
│ │ └── metrics.py
│ ├── services/
│ │ ├── language_detector.py
│ │ ├── intent_classifier.py
│ │ ├── fraud_detector.py
│ │ └── response_generator.py
│ ├── rag/
│ │ ├── knowledge_base.py
│ │ └── template_store.py
│ └── models/
│ └── schemas.py
├── tests/ ← 161 tests
├── Dockerfile
└── .github/workflows/
└── ci-cd.yml

Key Features

🎯

Intent Classification

7 categories × 32 sub-intents, 90/10 hybrid

🛡️

Fraud Detection

9 Red Flag scoring (0~100) + Minna/Ethoca block

⚡

3-tier Smart Routing

L1 Escalate / L2 Draft / L3 Self-service (38%)

🌍

Multilingual Templates

30 templates × 10 languages, quality scoring

PythonFastAPIClaude APIChromaDBDockerPydantic v2GitHub Actions

🔴 PROBLEM

1,600+ monthly tickets across 10 markets in 10 languages handled manually

Inconsistent response quality — no fraud detection at intake

🟠 STRATEGY

Designed hybrid AI chatbot — 90% template consistency + 10% Claude AI flexibility

3-tier routing with RAG knowledge base and real-time fraud scoring

Full CI/CD: 161 tests → Docker build → staging deploy

🟢 RESULT

38% self-service target (~630 tickets/month automated)

9 Red Flag fraud detection operational with quality scoring (0.0~1.0)

Message Processing Pipeline

🖥️

cs-ai-dashboard

AIProduction PythonFastAPILive

Production AI-powered CS operations dashboard. FastAPI + Vanilla JS SPA integrated with Zendesk API. AI draft generation with Claude SDK, 9-market multilingual RAG, 12-pattern spam detection, 6-dimension quality scoring. Phase 1 Draft+Review operational.

toomics-ai-agent/dashboard/
├── main.py ← FastAPI app
├── routers/
│ ├── tickets.py
│ ├── actions.py
│ ├── drafts.py
│ ├── auth.py
│ └── auto_response.py
├── services/
│ ├── zendesk_client.py
│ ├── draft_generator.py
│ ├── claude_service.py
│ ├── rag_service.py
│ ├── spam_detector.py
│ ├── category_classifier.py
│ ├── language_detector.py
│ ├── quality_scorer.py
│ ├── killswitch.py
│ └── auto_responder.py
├── knowledge/ ← 9 lang RAG
├── static/ ← SPA (JS+CSS)
└── tests/ ← 1422 tests

Key Features

🤖

AI Draft Generation

95/5 rule — 95% source-based + 5% format only. Claude SDK/Proxy dual mode

🌍

9-Market Multilingual RAG

EN + FR/DE/ES/JP/PT/TH/CN/IT keyword-based section routing, EN fallback

🛡️

Spam Detection P1~P12

Phishing, legal impersonation, social media scam, security/sales spam

📊

4-Stage Category Pipeline

Intent → Content Scoring → Consensus → Post-correction (B2B detect)

🤖

🤖 L3 Auto-Response

Phase 1: 60s polling → 8-gate filter → AI Draft → Approve/Edit/Reject

PythonFastAPIClaude APIZendesk APIRAGJWTVanilla JSSPA

🔴 PROBLEM

1,600+ monthly tickets manually handled across 10 markets, 10 languages

No AI assistance — agents write every response from scratch

🟠 STRATEGY

Built production AI dashboard — agents review AI drafts, not write from zero

Invisible AI: customers never know AI exists. Zendesk UX unchanged

Phase 1 (Draft+Review ✅) → Phase 2 (Auto Send) → Phase 3 (Advanced)

🟢 RESULT

Phase 1 live in production — 1422 tests, Phase 1 Draft+Review operational

6-dimension quality scoring (Template/Safety/Action/Relevance/Complete/Length)

Live Dashboard Screenshots

Dashboard — Ticket List + KPI Cards + Charts

🤖 AI Draft Ready — Approve / Edit / Reject

L3 Settings — Master Control + Category & Market

🌐

ai-translate

AIProduction PythonFastAPILive

Air-gapped AI translation system for internal use. No external API calls — runs entirely on local SQLite vocab.db. Full-text search (FTS5) across 25,070 terms in 10 languages, 12 source integrations, 17-tier priority system. Changelog tracking for every edit.

ai-translate/
├── app.py ← FastAPI server (1,477 lines)
├── vocab.db ← 25,070 terms · 13.0MB
├── changelog.db ← full edit history
├── static/
│ ├── css/
│ │ └── style.css ← 473 lines
│ └── js/
│ └── app.js ← 855 lines SPA
└── templates/
└── index.html ← SPA shell

Key Features

🔍

FTS5 Full-Text Search

SQLite FTS5 index — partial matching, multilingual morpheme search across 10 languages

📦

12 Source Integration

Translation compilations, product glossaries, Confluence, app language packs — 17-tier priority

📋

Batch Translation

1~20 texts per batch, vocab.db pattern matching, auto language detection

📜

Changelog Tracking

Every add/edit/delete recorded in changelog.db — full audit trail

PythonFastAPISQLiteFTS5Vanilla JSSPAREST API

🔴 PROBLEM

10 language translations scattered across 12+ Excel sheets, Confluence pages, and PDFs

No centralized search — operators manually grep through files to find official terms

🟠 STRATEGY

Built air-gapped translation DB — no external API, no data leaves the server

Consolidated 12 sources with priority-based deduplication (37,839 → 25,070 terms)

SQLite FTS5 for instant search — no external search engine needed

🟢 RESULT

25,070 terms across 10 languages, 10 categories — single source of truth

CS Manual docs + FAQ 101 articles searchable in-app — no login required

Live Screenshots

Term Lookup — FTS5 search with autocomplete

Batch Translation — Auto detect → Target language

Docs — CS Manual + FAQ 101 articles, 10 languages

📈

global-cs-analytics

ANALYTICSMIT Jupyter

CS data analytics & interactive dashboards for multi-market operations. Ticket volume trends, SLA benchmarking, category analysis, and revenue save tracking.

global-cs-analytics/
├── notebooks/
│ ├── 01_ticket_volume_analysis.ipynb
│ ├── 02_response_time_benchmark.ipynb
│ ├── 03_category_deep_dive.ipynb
│ └── 04_revenue_save_tracking.ipynb
├── dashboards/
│ └── cs_dashboard.html
├── data/
│ └── synthetic_tickets_10k.csv
└── scripts/
├── data_generator.py
└── kpi_calculator.py

Key Features

🌍

Multi-market Volume Trends

10 markets, 11 languages, weekly WoW comparison

⏱️

SLA Benchmarking

FRT, resolution time, agent performance

🔬

9-stage Noise Filtering

82% noise removal → clean data pipeline

💰

Interactive Dashboard

Chart.js + Plotly KPI visualization

PythonJupyterpandasPlotlyChart.jsZendesk API

🔴 PROBLEM

Raw Zendesk data was 82% noise — no structured analysis possible

13K+ tickets across 10 markets with no cross-market pattern visibility

🟠 STRATEGY

Built 9-stage filtering pipeline with 4-tier category classification engine

Created interactive Plotly/Chart.js dashboards for KPI visualization

🟢 RESULT

82% noise eliminated — clean data pipeline established

13,400+ tickets across 7 months analyzed with proactive insights

📊 Data Pipeline

Raw Input

12,920

Noise (-82%)

-9,693

Clean Data

3,227

Total Analyzed

13,400+

🔧

bizops-automation-toolkit

EXECUTION MIT Python

Business process automation tools for global operations teams. Automates Zendesk reporting, chargeback tracking, Slack team digests, and Confluence documentation.

bizops-automation-toolkit/
├── zendesk-reporting/
│ ├── weekly_report_generator.py
│ ├── cs_kpi_analyzer.py
│ ├── template_manager.py
│ └── sample_data/
├── chargeback-tracker/
│ ├── sheets_sync.py
│ ├── alert_generator.py
│ └── sample_data/
├── slack-team-digest/
│ ├── collect_updates.py
│ ├── digest_generator.py
│ └── slack_webhook_sender.py
└── confluence-docs-sync/
├── manual_updater.py
└── template_generator.py

Key Features

📊

Weekly HTML Report Auto-gen

Zendesk API → Chart.js dashboard + KPI cards

🔄

Chargeback Real-time Sync

Google Sheets API → 30-column CSV/JSON

📱

Slack Team Digest

Weekly updates collection + webhook delivery

📝

Confluence Auto-updater

CS manual + category template generator

PythonZendesk APIGoogle Sheets APISlack WebhookConfluence APIpandas

🔴 PROBLEM

Manual reporting consumed 2 days/week — repetitive data collection across 4 platforms

Chargeback data siloed in Google Sheets with no automated tracking

🟠 STRATEGY

Built modular Python toolkit connecting 4 platform APIs independently

Each module runs standalone with auto-commit and sample data for portability

🟢 RESULT

Report generation 2 days → 1 hour (95% reduction)

Chargeback data real-time synced, team digest & docs fully automated

Automation Pipeline

🤖

CS_claw

AIProduction PythonTelegram Bot

Telegram-based AI operations assistant for server monitoring, Zendesk ticket lookup, audit execution, and deployment — all from a single chat interface. Claude Opus conversational AI with vision, SQLite session persistence, real-time health monitoring, and 15-pattern natural language command routing.

CS_claw/
├── bot.py ← single-file bot (1,342 lines)
├── config.py ← env + multi-project routing
├── session_store.py ← SQLite session persistence
├── doc_indexer.py ← document RAG indexer
├── episode_store.py ← conversation episodes
├── health.py ← PID lock + health check
├── data/ ← SQLite DBs
└── tests/

Key Features

💬

Claude Opus AI + Vision

Conversational AI with image analysis, streaming responses, auto-summarization at 20-turn threshold

🎯

Natural Language Routing

15 patterns — "차지백 현황", "티켓 131234" auto-routed without slash commands

🖥️

Server Operations

/health, /services, /logs, /deploy, /audit run — full ops from chat

🛡️

Resilience & Safety

fcntl.flock dedup, 409 backoff, 600s watchdog, rate limiting 10 req/min, confirmation for destructive ops

PythonTelegram APIClaude APISQLiteZendesk APIsystemdhttpx

🔴 PROBLEM

Server monitoring, ticket checks, audit runs require SSH + multiple CLI tools

No mobile-friendly interface — ops tasks blocked when away from desktop

🟠 STRATEGY

Unified Telegram bot — AI chat + server ops + Zendesk + reports in one interface

Natural language routing — no need to memorize commands

5-min health polling with auto-alerting on service down

🟢 RESULT

All ops from phone — ticket lookup, audit execution, deployment, log review

6 slash commands + 15 natural language patterns, Claude Opus AI with vision analysis

Processing Pipeline

🗂️

bizops-artifacts-portal

OUTPUTLive58 docs

Public documentation portal hosting 58 operational artifacts across 9 categories. CS manuals (EN/KO), FAQ (10 languages), ToS (10 languages), chargeback templates, AI dashboard docs, analysis reports, and weekly archives.

bizops-artifacts-portal/
├── index.html
├── cs-operations/ ← 10 docs
│ ├── cs_manual_EN.html
│ ├── cs_manual_KO.html
│ ├── fraud_analysis.html
│ ├── cs_infographic.html
│ ├── cs_flow_diagram.html
│ └── weekly-reports/ ← W1~W4
├── chargeback/ ← 3 docs
│ ├── operation_manual.html
│ ├── template.xlsx
│ └── flow_diagram.html
├── ai-dashboard/ ← 6 docs
│ ├── policy.html
│ ├── quickstart.html
│ └── l3_engine.html
├── ip-protection/ ← 1 doc
│ └── ip_manual.html
└── dashboards/ ← 2 docs
├── ticket_dashboard.html
└── dashboard_manual.html

Categories

📞

CS Operations (10 docs)

EN/KO manuals, fraud report, flow diagrams, weekly reports

🖥️

AI Dashboard (6 docs)

Policy, quickstart, L3 engine, roadmap, settings

💳

Chargeback (3 docs)

8 PG dispute manual + evidence form V5 + template v2

📊

Dashboards & IP (3 docs)

Ticket dashboard, manual, IP protection guide

GitHub PagesHTML/CSSGitHub ActionsClaude AI@media printConfluence

🔴 PROBLEM

Operational docs scattered across Confluence, Sheets, and local files

No single source of truth for 10 global markets' operations

🟠 STRATEGY

Built centralized GitHub Pages portal with CI/CD auto-deployment

5 categories, EN/KO bilingual, print-optimized for PDF export

🟢 RESULT

58 documents publicly accessible — all authored solo

Single source of truth for 10 global markets with auto-deploy on push

📁 Documents by Category

AI Dashboard

6

CS Ops

10

Chargeback

3

Dashboard

2

IP Protection

1

Portal Screenshot

BizOPS Artifacts Portal — 58 docs, 9 categories

⚡

nexus-dashboard

DevOpsProduction TypeScriptNext.jsLive

Claude Code workspace management dashboard. Next.js 16 + shadcn/ui — manages agents, skills, hooks, and project instructions across multiple repositories. JWT auth, CRUD operations, audit logging, real-time monitoring, and export/import for configuration portability.

nexus-dashboard/
├── app/ ← Next.js 16 App Router
│ ├── overview/ ← KPI cards + project list
│ ├── agents/ ← agent CRUD + routing
│ ├── skills/ ← skill registry + hot reload
│ ├── hooks/ ← hook toggle + event config
│ ├── instructions/ ← CLAUDE.md editor
│ ├── projects/ ← multi-repo management
│ ├── monitor/ ← real-time monitoring
│ └── settings/ ← config + export/import
├── components/ ← shadcn/ui components
├── lib/ ← auth + API utilities
└── pm2.config.js ← PM2 deployment

Key Features

🧩

8-Page Management Console

Overview, Agents, Skills, Hooks, Instructions, Projects, Monitor, Settings

🔐

JWT Auth + Audit Log

Secure authentication with full audit trail — every create/update/delete logged

🔍

Search + Highlighting

Global search across agents, skills, hooks — keyword highlighting in results

📦

Export / Import

Full configuration portability — export as JSON, import to new workspace instantly

TypeScriptNext.js 16shadcn/uiTailwind CSSJWTPM2REST API

🔴 PROBLEM

Claude Code configuration scattered across CLAUDE.md, agents.yaml, hooks — no unified view

Managing 7+ projects × dozens of agents/skills requires manual file editing

🟠 STRATEGY

Built visual management dashboard — CRUD for all Claude Code primitives

Project-scoped filtering — switch context without navigating file trees

shadcn/ui component library — consistent, accessible, responsive UI

🟢 RESULT

8-page dashboard managing 7 projects, 40+ agents, 60+ skills from a single UI

Full audit log + export/import for configuration portability across environments

Live Dashboard Screenshots

Overview — KPI cards, project list, quick actions

📖

payment-ops-playbook

EXPERTISECC BY 4.0Docs

Open knowledge base for payment gateway operations. Covers PG fundamentals, cross-border settlements, fraud & chargeback management, and market localization from hands-on experience.

payment-ops-playbook/
├── 01-pg-fundamentals/
│ ├── payment-flow-overview.md
│ ├── 3-party-vs-4-party-system.md
│ └── card-brand-acquiring.md
├── 02-cross-border-payments/
│ ├── cross-border-settlement.md
│ ├── fx-risk-management.md
│ └── aml-kyc-compliance.md
├── 03-fraud-and-chargeback/
│ ├── fds-rule-design.md
│ ├── chargeback-dispute-process.md
│ └── fraud-pattern-analysis.md
├── 04-localization/
│ ├── thailand-pg-setup.md
│ └── multi-market-operations.md
└── diagrams/
├── payment-flow.mermaid
└── settlement-cycle.mermaid

Chapters

💳

PG Fundamentals

Payment flow, 3-party vs 4-party, card brand acquiring

🌏

Cross-border Payments

Settlement, FX risk, AML/KYC compliance

🛡️

Fraud & Chargeback

FDS rule design, dispute process, pattern analysis

🇹🇭

Market Localization

Thailand PG setup, multi-market playbook

Visa / MastercardNHN KCPCross-borderFDSAML/KYCMermaid

🔴 PROBLEM

PG operations knowledge siloed in individuals — no structured handoff

No onboarding guide for cross-border settlement or fraud operations

🟠 STRATEGY

Documented 10+ years of PG experience into 4 structured chapters

Added Mermaid diagrams for visual payment & settlement flows

🟢 RESULT

Comprehensive playbook covering 4 core domains with visual flows

Reusable reference for PG partnerships, FDS design, multi-market expansion

🎭

avatara-nft-platform

BLOCKCHAINNX3 Games Web3

Blockchain-based digital avatar NFT platform designed at NX3 Games (NEXON). Led end-to-end service design — NFT minting pipeline, marketplace trading, tokenomics, and GameFi integration on Polygon network.

avatara-nft-platform/
├── contracts/
│ ├── AvataraNFT.sol
│ ├── Marketplace.sol
│ └── TokenRewards.sol
├── avatar-builder/
│ ├── trait_generator.py
│ ├── metadata_engine.py
│ └── rarity_calculator.py
├── marketplace/
│ ├── listing_service.ts
│ ├── auction_engine.ts
│ └── royalty_splitter.ts
├── gamefi-integration/
│ ├── staking_module.sol
│ └── play_to_earn.sol
└── docs/
├── tokenomics.md
└── whitepaper.md

Key Features

🎨

Generative Avatar Minting

Trait-based generative system with rarity tiers

🏪

NFT Marketplace

Listing, auction, royalty split on Polygon

🎮

GameFi Integration

Staking rewards + Play-to-Earn mechanics

📊

Tokenomics Design

Supply control, burn mechanics, reward distribution

SolidityPolygonNFTWeb3.jsIPFSReactTypeScriptHardhat

🔴 PROBLEM

Game assets locked in centralized servers — no true player ownership or cross-game portability

No secondary market for in-game items — zero residual value for players

🟠 STRATEGY

Designed NFT-based avatar system on Polygon — low gas, high throughput for game assets

Built marketplace with royalty splits (creator + platform) and P2E staking mechanics

Managed tokenomics — supply, burn, reward cycles aligned with game economy

🟢 RESULT

End-to-end NFT platform designed — minting → marketplace → GameFi full lifecycle

Web3 partnership ecosystem established with multiple blockchain partners

NFT Lifecycle Architecture

💱

global-mass-remittance

NEW BIZNHN KCP Fintech

Designed and launched a cross-border multi-currency mass remittance platform for global partners. Developed KRW-KRW and USD-USD localized bulk transfer services for Payoneer, Uber, and Airbnb — enabling mass bank transfers to sub-merchants without a Korean PG license. Generated ₩200M+ monthly fixed revenue.

Monthly Fixed Revenue

₩200M+

Minimum guaranteed / month

Revenue Model

Fixed + %

Fixed KRW per transfer + commission rate

Transfer Frequency

Daily

Daily & weekly cross-border USD settlement

global-mass-remittance/
├── 01-cross-border-usd/
│ ├── usd-virtual-account-design.md
│ ├── bulk-transfer-api-spec.md
│ ├── settlement-cycle-daily.md
│ └── revenue-model-analysis.md
├── 02-localized-remittance/
│ ├── krw-krw-domestic-transfer.md
│ ├── usd-usd-fx-settlement.md
│ └── sub-merchant-onboarding.md
├── 03-partner-integration/
│ ├── payoneer-integration.md
│ ├── uber-settlement-flow.md
│ ├── airbnb-host-payout.md
│ └── partner-compliance-kyc.md
├── 04-van-banking/
│ ├── van-partner-contract.md
│ └── banking-api-integration.md
└── diagrams/
├── remittance-flow.mermaid
└── settlement-cycle.mermaid

Key Deliverables

💵

Cross-border USD Mass Remittance

USD virtual account-based bulk transfer with daily/weekly settlement

🔄

KRW-KRW / USD-USD Services

Bulk bank transfers for partners without Korean PG license

🤝

Global Partner Acquisition

Payoneer · Uber · Airbnb onboarded for Korean market settlement

🏦

VAN Banking Infrastructure

Mass bank transfer execution and reconciliation

🔒

Partner Lock-in & Revenue Defense

Remittance as value-add → partner retention + new acquisition

Cross-borderUSD Virtual AccountMass RemittancePayoneerUberAirbnbVANKRW-KRWUSD-USD

🔴 PROBLEM

Global e-wallet providers (Payoneer, Uber, Airbnb) needed Korean sub-merchant settlement but couldn't obtain PG licenses

NHN KCP revenue relied solely on PG processing fees — no defense against partner churn

No infrastructure for cross-border multi-currency bulk transfers to Korean recipients

🟠 STRATEGY

Designed USD virtual account-based cross-border bulk remittance platform with daily/weekly settlement

Developed KRW-KRW & USD-USD localized mass transfer services for partners without Korean PG licenses

Partnered with domestic VAN providers for banking API integration and automated reconciliation

Positioned remittance as value-add for existing PG partners → lock-in + new acquisition channel

🟢 RESULT

New platform launched — ₩200M+ monthly fixed revenue with per-transaction commission

Onboarded Payoneer, Uber, Airbnb as remittance clients for Korean market settlement

Dual revenue model: fixed KRW fee + % commission on each cross-border remittance

Existing partners locked in; remittance became a new partner acquisition channel

Mass Remittance Platform Architecture

📊 Service Impact Metrics

Monthly Rev.

₩200M+

Global Partners

3+

Transfer Types

KRW+USD

Settlement

Daily

Chongsun Yu
PM who builds × Product Owner

Why I Built Everything Below

See the Pattern

Decide with Evidence

Build, Learn, Harden

Know Where to Stop

Built to Solve Real Problems

12+ Years in Global Operations

Team Lead, BizOps

Part Lead, Blockchain Business

Part Lead, Global Payment Division

IT Director / Team Lead

Account Manager, Global Payment

Australian National University

Tools & Domain Expertise

Domain Expertise

Tech & Tools

Let's Connect

Chongsun Yu PM who builds × Product Owner

Why I Built Everything Below

See the Pattern

Decide with Evidence

Build, Learn, Harden

Know Where to Stop

Built to Solve Real Problems

12+ Years in Global Operations

Team Lead, BizOps

Part Lead, Blockchain Business

Part Lead, Global Payment Division

IT Director / Team Lead

Account Manager, Global Payment

Australian National University

Tools & Domain Expertise

Domain Expertise

Tech & Tools

Let's Connect

Chongsun Yu
PM who builds × Product Owner