Cheng Siong Chin
Dr. Cheng Siong CHIN is an n8n workflow creator specializing in AI-powered automation, agent orchestration, and intelligent system integrations. He designs and builds end-to-end workflows that combine LLMs, APIs, and data pipelines to streamline complex processes and deliver production-ready automation solutions. Contact me to discuss custom AI workflows and agent architectures.
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Templates by Cheng Siong Chin
Stock market analysis & prediction with GPT, Claude & Gemini via Telegram
Introduction Automates stock market analysis using multiple AI models to predict trends, analyze sentiment, and generate consensus-based investment insights. For traders and analysts seeking data-driven forecasts by eliminating manual research and combining AI perspectives for accurate predictions. How It Works Daily trigger fetches stock data, news, ratings, and sentiment → AI models analyze each source → OpenAI generates report → Three AI validators (OpenAI, Anthropic, Gemini) cross-verify → Consensus evaluation → Telegram alert with insights. Workflow Template Schedule → Fetch Stock Data → Fetch News → Fetch Ratings → Fetch Sentiment → AI Analysis → Combine → Generate Report (GPT) → Validate (3 AIs) → Evaluate Consensus → Send Telegram Workflow Steps Data Collection: Scheduled trigger fetches prices, news, analyst ratings, and social trends AI Analysis: Separate models analyze stocks, news sentiment, ratings, and social discussions Report Generation: OpenAI GPT combines analyses into comprehensive market report Multi-AI Validation: Three AI models independently validate predictions for accuracy Consensus Building: Evaluates AI agreement to determine confidence levels Alert Delivery: Sends Telegram alerts with buy/sell/hold recommendations Setup Instructions Schedule: Configure daily trigger time Data Sources: Add API keys for stock data, news APIs, and social platforms AI Models: Configure OpenAI, Anthropic, and Google Gemini credentials Telegram: Create bot and add token Thresholds: Define consensus requirements for recommendations Prerequisites Stock data API (Alpha Vantage, Yahoo Finance) News API key Social media API OpenAI API key Anthropic API key Google Gemini API key Telegram bot token Use Cases Day Trading: Real-time volatile stock analysis with multiple AI perspectives. Portfolio Management: Daily consensus reports for rebalancing. Customization Add technical indicators (RSI, MACD). Include crypto analysis. Integrate portfolio tracking. Add email/Slack notifications. Configure sector-specific analysis. Benefits Eliminates hours of daily research. Reduces AI hallucination through multi-model validation. Provides 24/7 monitoring. Combines multiple data sources.
By Cheng Siong ChinSmart travel package finder: Search flights & hotels with Skyscanner-Booking.com
Introduction Automates travel itinerary creation by searching flights and hotels via APIs, then uses AI to generate personalized recommendations delivered as HTML emails through Gmail. How It Works Webhook receives travel requests, searches Skyscanner and Booking.com APIs in parallel, merges results, uses AI to create optimized itineraries, formats as HTML email, sends via Gmail. Workflow Template Webhook → Parse & Validate → Parallel Searches (Flights: Skyscanner | Hotels: Booking.com) → Merge Data → AI Generate Itinerary → Format HTML Email → Send Gmail → Webhook Response Workflow Steps Trigger & Validate: Webhook receives request, extracts destination/dates/budget/preferences, validates data, converts to API parameters. Parallel Search: Skyscanner fetches flights with price/duration/airline. Booking.com retrieves hotels with ratings/pricing. Merge combines both into single JSON object. AI Generation: AI analyzes merged data, evaluates by price/duration/rating, creates itinerary with daily schedule, pairings, costs, and rankings. Delivery: Converts JSON to HTML email with tables and booking links. Gmail sends email. Webhook confirms success. Setup Instructions API Configuration: Add Skyscanner and Booking.com API credentials in n8n. Gmail Setup: Configure OAuth2 authentication. Customization: Copy webhook URL, adjust validation rules, modify AI prompts and HTML template. Prerequisites Skyscanner API key Booking.com API credentials Gmail with OAuth2 n8n instance Use Cases Personal vacation planning Business travel arrangements Customization Add APIs (Kiwi, Expedia) Filter by budget, Modify email design Benefits Saves 2-3 hours per trip Real-time pricing comparison
By Cheng Siong ChinAi-optimized travel itinerary generator with Skyscanner, Booking.com and Gmail
Introduction Automates travel planning by aggregating flights, hotels, activities, and weather via APIs, then uses AI to generate professional itineraries delivered through Gmail and Slack. How It Works Webhook receives requests, searches APIs (Skyscanner, Booking.com, Kiwi, Viator, weather), merges data, AI builds itineraries, scores options, generates HTML emails, delivers via Gmail/Slack. Workflow Template Webhook → Extract → Parallel Searches (Flights/Hotels/Activities/Weather) → Merge → Build Itinerary → AI Processing → Score → Generate HTML → Gmail → Slack → Response Workflow Steps Trigger & Extract: Receives destination, dates, preferences, extracts parameters. Data Gathering: Parallel APIs fetch flights, hotels, activities, weather, merges responses. AI Processing: Analyzes data, creates itinerary, ranks recommendations. Delivery: Generates HTML email, sends via Gmail/Slack, confirms completion. Setup Instructions API Configuration: Add keys for Skyscanner, Booking.com, Kiwi, Viator, OpenWeatherMap, OpenRouter. Communication: Connect Gmail OAuth2, Slack webhook. Customization: Adjust endpoints, AI prompts, HTML template, scoring criteria. Prerequisites API keys: Skyscanner, Booking.com, Kiwi, Viator, OpenWeatherMap, OpenRouter Gmail account Slack workspace n8n instance Use Cases Corporate travel planning Vacation itinerary generation Group trip coordination Customization Add sources (Airbnb, TripAdvisor) Filter by budget preferences Add PDF generation Customize Slack format Benefits Saves 3-5 hours per trip Real-time pricing aggregation AI-powered personalization Automated multi-channel delivery
By Cheng Siong ChinGold market prediction system with Perplexity Sonar-Pro, FRED data, and WordPress reporting
Introduction Automates gold market tracking using AI forecasting by collecting live prices, financial news, and macro indicators (inflation, interest rates, employment) to produce real-time insights and trend predictions for analysts and investors. How It Works Every 6 hours, the system fetches market data and news → runs AI sentiment and trend analysis → generates a concise forecast report → publishes it to WordPress → and alerts users via Slack or email. Workflow Template Trigger → Fetch → Format → Merge → AI Analyze → Report → Publish → Notify Workflow Steps Schedule: Executes automatically every 6 hours using a Cron trigger. Fetch: Retrieves live gold prices (MetalPriceAPI), financial headlines (NewsAPI), and macroeconomic indicators (FRED). Format & Merge: Cleans, normalizes, and merges all data into a single structured dataset for AI analysis. AI Analyze (OpenAI): Performs sentiment, trend, and correlation analysis to forecast short-term gold price movements. Report Generation: Creates a concise summary report with forecasts, insights, and confidence metrics. Publish & Notify: Automatically posts to WordPress and sends alerts via Slack and Email to keep analysts updated. Setup Add API keys: MetalPrice, NewsAPI, FRED, OpenAI, WordPress, Slack, Gmail. Configure scheduling interval, API endpoints, and authentication in n8n. Predefine WordPress post format and Slack message templates for smooth automation. Prerequisites n8n v1.0+, API keys, OAuth credentials, and internet access. Use Cases Investment forecasting, financial newsletter automation, or market monitoring dashboards. Customization Add cryptocurrency or stock tracking, modify AI prompts, or route summaries to Telegram, Notion, or Google Sheets. Benefits Saves analyst time, ensures consistent insights, enhances accuracy, and delivers timely, AI-driven financial intelligence.
By Cheng Siong ChinQwen-Max: journal paper generation from title/abstract
Introduction Generates complete scientific papers from title and abstract using AI. Designed for researchers, automating literature search, content generation, and citation formatting. How It Works Extracts input, searches academic databases (CrossRef, Semantic Scholar, OpenAlex), merges sources, processes citations, generates AI sections (Introduction, Literature Review, Methodology, Results, Discussion, Conclusion), compiles document. Workflow Template Webhook → Extract Data → Search (CrossRef + Semantic Scholar + OpenAlex) → Merge Sources → Process References → Prepare Context → AI Generate (Introduction + Literature Review + Methodology + Results + Discussion + Conclusion via OpenAI) → Merge Sections → Compile Document Workflow Steps Input & Search: Webhook receives title/abstract; searches CrossRef, Semantic Scholar, OpenAlex; merges and processes references AI Generation: OpenAI generates six sections with in-text citations using retrieved references Assembly: Merges sections; compiles formatted document with reference list Setup Instructions Trigger & APIs: Configure webhook URL; add OpenAI API key; customize prompts Databases: Set up CrossRef, Semantic Scholar, OpenAlex API access; configure search parameters Prerequisites OpenAI API, CrossRef API, Semantic Scholar API, OpenAlex API, webhook platform, n8n instance Customization Adjust reference limits, modify prompts for research fields, add citation styles (APA/IEEE), integrate databases (PubMed, arXiv), customize outputs (DOCX/LaTeX/PDF) Benefits Automates paper drafting, comprehensive literature integration, proper citations
By Cheng Siong ChinIntelligent project delivery and task management system
How It Works Automates daily project monitoring by fetching project data, analyzing tasks and team capacity with anthropic models, and generating resource optimization recommendations. Target audience: project managers, engineering leads, and resource planners managing complex team assignments. Problem solved: manual capacity planning misses bottlenecks; AI analysis identifies effort mismatches and delays proactively. Workflow runs daily checks, merges project and team profiles, analyzes tasks via multiple anthropic agents (breakdown, estimation, assignment), calculates effort allocation, detects delays, generates rebalancing recommendations, notifies stakeholders, and tracks milestones. Setup Steps Configure daily trigger schedule. Connect project management system APIs. Set anthropic API keys with task analysis prompts. Enable email notifications for managers. Connect reporting database for tracking. Prerequisites Anthropic API access, project management tool credentials, team capacity database Use Cases SaaS teams managing feature backlogs, consulting firms balancing client projects Customization Adjust effort estimation models. Add Slack notifications for urgency. Benefits Detects delays 2-3 weeks early, improves team utilization by 25%
By Cheng Siong ChinExtract PDF itineraries to Google Sheets with GPT-4.1-Mini & Gmail notifications
Extract PDF Itineraries to Google Sheets with GPT-4.1-Mini & Gmail Notifications Overview Automates PDF data extraction using OpenAI GPT, saves to Google Sheets, sends email confirmations. Reduces manual entry by 90%. How It Works Receives PDF uploads via form Splits & loops through files AI extracts structured data Appends to Sheets with timestamps Sends confirmation email Prerequisites OpenAI API key (platform.openai.com) Google Workspace (Sheets & Gmail) n8n v1.0.0+ Setup Add OpenAI API key to n8n credentials Create Google Sheet with extraction columns, authorize OAuth2 Configure Gmail OAuth2 Import workflow JSON Edit AI prompt for your fields Activate & share form URL Customization Modify extraction prompts Adjust Sheets mapping Customize email templates Add error handling/validation Extend to Word/Excel files Use Cases Invoices, expense reports, resumes, contracts, forms, legal docs
By Cheng Siong ChinPredictive health monitoring & alert system with GPT-4o-mini
How It Works The system collects real-time wearable health data, normalizes it, and uses AI to analyze trends and risk scores. It detects anomalies by comparing with historical patterns and automatically triggers alerts and follow-up actions when thresholds are exceeded. Setup Steps Configure Webhook Endpoint - Set up webhook to receive data from wearable devices Connect Database - Initialize storage for health metrics and historical data Set Normalization Rules - Define data standardization parameters for different devices Configure AI Model - Set up health score calculation and risk prediction algorithms Define Thresholds - Establish alert triggers for critical health metrics Connect Notification Channels - Configure email and Slack integrations Set Up Reporting - Create automated report templates and schedules Test Workflow - Run end-to-end tests with sample health data Workflow Template Webhook → Store Database → Normalize Data → Calculate Health Score → Analyze Metrics → Compare Previous → Check Threshold → Generate Reports/Alerts → Email/Slack → Schedule Follow-up Workflow Steps Ingest real-time wearable data via webhook, store and standardize it, and use GPT-4 for trend analysis and risk scoring. Monitor metrics against thresholds, trigger SMS, email, or Slack alerts, generate reports, and schedule follow-ups. Setup Instructions Configure webhook, database, GPT-4 API, notifications, calendar integration, and customize alert thresholds. Prerequisites Wearable API, patient database, GPT-4 key, email SMTP, optional Slack/Twilio, calendar integration. Use Cases Monitor glucose for diabetics, track elderly vitals/fall risk, assess corporate wellness, and post-surgery recovery alerts. Customization Adjust risk algorithms, add metrics, integrate telemedicine. Benefits Early intervention reduces readmissions and automates 80% of monitoring tasks.
By Cheng Siong ChinIntelligent legal document review and compliance automation
How It Works This template automates legal document review by extracting text, analyzing clauses with OpenAI, checking compliance standards, and generating alternative wordings. Target audience: legal teams, contract managers, and compliance officers seeking efficient document processing. Problem solved: manual clause extraction and compliance review is time-consuming and error-prone. Workflow extracts document text, performs parallel AI-powered clause analysis and compliance verification via OpenAI, consolidates findings, generates alternative wordings for non-compliant clauses, creates summary reports, stores results in databases, and notifies stakeholders via email. Setup Steps Configure OpenAI API with clause analysis and compliance prompts. Connect Google Sheets for database staging. Set Gmail for notifications. Input document source (upload node). Test with sample contracts. Prerequisites OpenAI API key, Gmail account, Google Sheets access, document upload capability. Use Cases Legal teams reviewing SaaS contracts, compliance departments auditing vendor agreements Customization Modify OpenAI prompts for industry-specific clauses. Swap Google Sheets for your database. Benefits Reduces manual review time by 80%, ensures consistent clause standardization
By Cheng Siong ChinTelegram bot: analyze images with GPT-4o-Mini/NVIDIA Vila & generate images with Stable Diffusion 3
Introduction Transform your Telegram bot into an AI vision system using GPT-4o-Mini and NVIDIA Stable Diffusion 3. Perfect for content moderators, researchers, and developers. Workflow Explanatory At start: Processes Telegram messages: images→analysis, text→image generation At Router: Routes by content type Upper path: Analyzes images using Nvidia Vila + GPT-4o-Mini Lower path: Generates images from text via Stable Diffusion 3 At Merge: Combines AI results At Gmail: Emails processed results How It Works Telegram Trigger listens for messages (images, text, documents) Content Router directs images → AI analysis, text → image generation Image Analysis: Downloads image → GPT-4o-Mini vision analysis → Email results Image Generation: Text prompt → Stable Diffusion 3 → Email generated image Gmail Notifications send formatted reports Prerequisites Telegram Bot token (via @BotFather) OpenAI API key (GPT-4 Vision) NVIDIA API key (free tier available) Gmail OAuth2 credentials Setup Steps Setup Steps Create Telegram Bot - Create Telegram bot and obtain token Configure API Credentials - Configure API credentials in HTTP Request nodes Set Up Gmail OAuth2 - Set up Gmail OAuth2 Import and Activate Workflow - Import workflow, update credentials, and activate Customization Options Add more AI models (Anthropic, Gemini) Route audio/documents to transcription/OCR Replace Gmail with Slack or Discord Connect to databases for storage Benefits Speed: Seconds per analysis vs. hours manually Accuracy: AI-powered visual understanding Intelligence: Historical tracking enables trend analysis
By Cheng Siong ChinCoordinate patient care and alerts with EHR/FHIR, GPT-4, Twilio, Gmail and Slack
How It Works This workflow automates end-to-end patient care coordination by monitoring appointment schedules, clinical events, and care milestones while orchestrating personalized communications across multiple channels. Designed for healthcare operations teams, care coordinators, and patient engagement specialists, it solves the challenge of manual patient follow-up, missed appointments, and fragmented communication across care teams. The system triggers on scheduled intervals and real-time clinical events, ingesting data from EHR systems, appointment schedulers, and lab result feeds. Patient records flow through validation and risk stratification layers using AI models that identify high-risk patients, predict no-show probability, and recommend intervention timing. The workflow applies clinical protocols for appointment reminders, medication adherence checks, and post-discharge follow-ups. Critical cases automatically route to care coordinators via Slack alerts, while routine communications deploy via SMS, email, and patient portal notifications. All interactions log to secure databases for compliance documentation. This eliminates manual outreach coordination, reduces no-shows by 40%, and ensures HIPAA-compliant patient engagement at scale. Setup Steps Configure EHR/FHIR API credentialsfor patient data access Set up webhook endpoints for real-time clinical event notifications Add OpenAI API key for patient risk stratification and communication personalization Configure Twilio credentials for SMS and voice call delivery Set Gmail OAuth or SMTP credentials for email appointment reminders Connect Slack workspace and define care coordination alert channels Prerequisites Active EHR system with FHIR API access or HL7 integration capability. Use Cases Automated appointment reminder campaigns reducing no-shows. Customization Modify risk scoring models for specialty-specific patient populations. Benefits Reduces patient no-show rates by 40% through timely, personalized reminders.
By Cheng Siong ChinMarket intelligence engine with AI sentiment detection & competitor analysis
How It Works A scheduled process aggregates content from eight distinct data sources and standardizes all inputs into a unified format. AI models perform sentiment scoring, detect conspiracy or misinformation signals, and generate trend analyses across domains. An MCDN routing model prioritizes and channels insights to the appropriate workflows. Dashboards visualize real-time analytics, trigger KPIs based on thresholds, and compile comprehensive market-intelligence reports for stakeholders. Setup Steps Data Sources: Connect news APIs, social media platforms, academic databases, code repositories, and documentation feeds. AI Analysis: Configure OpenAI models for sentiment analysis, conspiracy detection, and trend scoring. Dashboards: Integrate analytics platforms and enable automated email or reporting outputs. Storage: Configure a database for historical records, trend archives, and competitive-intelligence storage. Prerequisites Multi-source API credentials; OpenAI API key; dashboard platform access; email service; code repository access; academic database credentials Use Cases Competitive intelligence monitoring; market trend analysis; technology landscape tracking; product strategy research; misinformation filtering Customization Adjust sentiment thresholds; add/remove data sources; modify analysis rules; extend AI models Benefits Reduces research time 80%; consolidates market intelligence; improves decision accuracy
By Cheng Siong Chin