AWS S3 and Gmail integration

Generate SEO-Optimized PWA Website with AI and Deploy to S3 Who's it for This workflow is designed for agencies, freelancers, and businesses who want to generate production-ready static websites with built-in SEO optimization and PWA (Progressive Web App) capabilities — all without manual coding. It is best suited for users who need landing pages, portfolios, event pages, or client microsites that are mobile-friendly, SEO-optimized, and installable as apps on any device. What it does This workflow collects website requirements via an n8n form, uses Google Gemini AI to generate a complete HTML page with SEO metadata and PWA components (service worker, manifest, offline support), assembles all files, uploads them to AWS S3, and sends the published URL via email. Unlike basic AI website generators, this workflow produces three separate AI-generated outputs that are assembled into a complete, deployable package: ✅ SEO-optimized meta tags, Open Graph, and structured data (Schema.org) ✅ PWA manifest + service worker for offline support and "Add to Home Screen" ✅ Responsive, single-page website with embedded CSS and JavaScript ✅ All files deployed as a cohesive package to S3 How it works Website Request Form — User fills out requirements (name, purpose, colors, content, keywords). Process Form Data — Workflow structures the input for AI processing. Generate SEO Metadata (Gemini AI) — Creates meta tags, Open Graph tags, Twitter cards, and JSON-LD structured data based on the site's purpose and keywords. Generate Website HTML (Gemini AI) — Produces a complete, responsive HTML/CSS/JS page incorporating the SEO metadata. Generate PWA Components — Creates manifest.json and service-worker.js for offline capability and app-like behavior. Assemble All Files — Merges HTML, manifest, and service worker into a deployment-ready package. Convert to Binary — Prepares all files for S3 upload. Upload to S3 — Deploys all files (index.html, manifest.json, sw.js) with proper content types. Build Response — Constructs the live URL and deployment summary. Send Confirmation Email — Delivers the live URL, SEO report, and PWA installation instructions to the user. Requirements To use this workflow, you will need: A Google Gemini API key (Gemini 1.5 Flash or Pro recommended) An AWS account with S3 access An S3 bucket configured for static website hosting A Gmail account for sending confirmation emails (or replace with another email service) AWS Setup Guide Step 1: Create an IAM User for n8n Go to AWS Console → IAM → Users → Create user User name: n8n-s3-uploader Attach the following custom policy: { "Version": "2012-10-17", "Statement": [ { "Sid": "S3WebsiteUpload", "Effect": "Allow", "Action": [ "s3:PutObject", "s3:PutObjectAcl", "s3:GetObject", "s3:ListBucket" ], "Resource": [ "arn:aws:s3:::YOUR_BUCKET_NAME", "arn:aws:s3:::YOUR_BUCKET_NAME/*" ] } ] } Create access key → Select "Application running outside AWS" Save the Access Key ID and Secret Access Key for n8n credential setup Step 2: Create an S3 Bucket Go to AWS Console → S3 → Create bucket Bucket name: Choose a globally unique name (e.g., my-ai-websites-12345) Region: Select your preferred region Object Ownership: Select "ACLs enabled" → "Bucket owner preferred" Block Public Access: Uncheck "Block all public access" and acknowledge the warning Create bucket Step 3: Enable Static Website Hosting Go to your bucket → Properties tab Scroll to "Static website hosting" → Edit Enable static website hosting Index document: index.html Error document: index.html (for PWA routing) Save changes Note the bucket website endpoint URL (e.g., http://YOUR_BUCKET_NAME.s3-website-REGION.amazonaws.com) Step 4: Add Bucket Policy for Public Access Go to your bucket → Permissions tab Scroll to "Bucket policy" → Edit Paste the following policy: { "Version": "2012-10-17", "Statement": [ { "Sid": "PublicReadGetObject", "Effect": "Allow", "Principal": "*", "Action": "s3:GetObject", "Resource": "arn:aws:s3:::YOUR_BUCKET_NAME/*" } ] } Replace YOUR_BUCKET_NAME with your actual bucket name Save changes Step 5: Configure n8n Credentials In n8n, go to Credentials → Add credential → AWS Enter the Access Key ID and Secret Access Key from Step 1 Set the region to match your S3 bucket region Save the credential Important limitations Generated websites are single-page only (no multi-page navigation). The AI may occasionally produce varying results depending on prompt complexity. S3 bucket must have public access enabled for the websites to be viewable. PWA "Add to Home Screen" requires HTTPS — use CloudFront for production deployments. No custom domain support out of the box (requires additional CloudFront/Route53 setup). Service worker caching is basic (cache-first strategy); for advanced caching, customize the generated sw.js. AWS charges may apply based on S3 storage and data transfer usage. How to set up Complete the AWS Setup Guide above. Add your Google Gemini API credential in n8n. Add your AWS credential in n8n (from Step 5 above). Update the S3 bucket name in the "Upload to S3" node. Update the bucket URL in the "Build Response" node. Configure Gmail OAuth2 credential (or replace with your email service). Activate the workflow and share the form URL. How to customize AI Model**: Swap Google Gemini for OpenAI, Anthropic, or any LLM supported by n8n. Form fields**: Add fields for target audience, language preference, or industry-specific requirements. SEO depth**: Extend the SEO prompt to generate sitemaps, robots.txt, or additional structured data types. PWA features**: Customize the service worker for push notifications, background sync, or advanced caching strategies. Notifications**: Replace Gmail with Slack, Discord, or webhook notifications. Storage**: Add a database node to track generated websites with analytics. Domain**: Integrate with CloudFront + Route53 for custom domains with HTTPS. Error handling**: Add error handling nodes and retry logic for production use. What makes this different Most AI website generators create a basic HTML file. This workflow goes further: | Feature | Basic Generator | This Workflow | |---------|----------------|---------------| | HTML/CSS/JS | ✅ | ✅ | | SEO Meta Tags | ❌ | ✅ (AI-generated) | | Open Graph / Twitter Cards | ❌ | ✅ | | Schema.org Structured Data | ❌ | ✅ (JSON-LD) | | PWA Support | ❌ | ✅ (manifest + service worker) | | Offline Capability | ❌ | ✅ | | "Add to Home Screen" | ❌ | ✅ | | Multiple AI Calls | 1 | 2 (specialized prompts) | | Deployment Files | 1 (index.html) | 3+ (html + manifest + sw.js) | Security Considerations The generated websites are publicly accessible. Do not use this for sensitive content. Consider adding authentication if you want to restrict who can generate websites. Review AWS costs regularly to avoid unexpected charges. For production use, set up CloudFront with HTTPS (required for full PWA functionality). Service workers require HTTPS in production; localhost is exempt for testing. Note: This workflow was built using Google Gemini AI and AWS S3 static website hosting. For production deployments, we recommend adding CloudFront for HTTPS, custom domains, and global CDN distribution.

Automatically extract structured information from emails using AI-powered document analysis. This workflow processes emails from specified domains, classifies them by type, and extracts structured data from various attachment formats. Who is this for Operations teams, coordinators, and business professionals who receive proposals or reports from multiple sources via email and need to consolidate the information into a structured database. What this workflow does Monitors Gmail every 30 minutes for emails from specified domains Classifies emails into three categories based on customizable keywords Processes attachments intelligently based on file type and email classification Extracts structured data: dates, times, names, amounts, and other fields Saves to Google Sheets with full metadata and classification Labels processed emails in Gmail for tracking Setup requirements Gmail OAuth2 credentials OpenAI API key (GPT-4 Vision) Google Sheets OAuth2 credentials AWS S3 bucket for temporary image storage ConvertAPI account for PPTX/PDF conversion How to customize Edit the domain list and classification keywords in the code nodes to adapt for your specific use case.

Inspiration & Notes This workflow was born out of a very real problem. While writing a book, I found the process of discovering suitable literary agents and managing outreach to be manual, and surprisingly difficult to scale. Researching agents, checking submission rules, personalizing emails, tracking submissions, and staying organized quickly became a full-time job on its own. So instead of doing it manually, I automated it. I built this entire workflow in 3 days — and the goal of publishing it is to show that you can do the same. With the right structure and intent, complex sales and marketing workflows don’t have to take months to build. Contact & Collaboration If you have questions, business inquiries, or would like help setting up automation workflows, feel free to reach out: 📩 [email protected] I genuinely enjoy designing workflows and automation systems, especially when they support meaningful projects. I work primarily from interest and impact rather than purely financial motivation. Whether I take on a project for FREE or paid for the following reasons: I LOVE setting up workflows and automation. I work for meaningfulness, not for money. I may do the work for free**, depending on how meaningful the project is. If the problem statement matters, the motivation follows. It also depends on the value I bring to the table** -- If I can contribute significant value through system design, I’m more inclined to get involved. If you’re building something thoughtful and need help automating it, I’m always happy to have a conversation. Enjoy~! Overview Automates the end-to-end literary agent outreach pipeline, from data ingestion and eligibility filtering to deep agent research, personalized email generation, submission tracking, and analytics. Architecture The system is organized into four logical domains: The system is modular and is divided into four domains: --> Data Engineering --> Marketing & Research --> Sales (Outreach) --> Data Analysis Each domain operates independently and passes structured data downstream. Data Engineering Purpose: Ingest and normalize agent data from multiple sources into a single source of truth. Inputs Google BigQuery Azure Blob Storage AWS S3 Google Sheets (Optional) HTTP sources Key Steps Scheduled ingestion trigger Merge and normalize heterogeneous data formats (CSV, tables) Deduplication and validation AI-assisted enrichment for missing metadata Append-only writes to a central Google Sheet Output Clean, normalized agent records ready for eligibility evaluation Marketing & Research Purpose: Decide who to contact and how to personalize outreach. Eligibility Evaluation An AI agent evaluates each record against strict rules: Email submissions enabled Not QueryTracker-only or QueryManager-only Genre fit (e.g. Memoir, Spiritual, Self-help, Psychology, Relationships, Family) Outputs send_email (boolean) reason (auditable explanation) Deep Research For eligible agents only: Public research from agency sites, interviews, Manuscript Wish List, and LinkedIn (if public) Extracts: Professional background Editorial interests Genres represented Notable clients/books (if publicly listed) Public statements Source-backed personalization angles Strict Rule: All claims must be explicitly cited; no inference or hallucination is allowed. Sales (Outreach) Purpose: Execute personalized email outreach and maintain clean submission tracking. Steps AI generates agent-specific email copy Copy is normalized for tone and clarity Email is sent (e.g. Gmail) Submission metadata is logged: Submission Completed Submission Timestamp Channel used Result Consistent, traceable outreach with CRM-style hygiene Data Analysis Purpose: Measure pipeline health and outreach effectiveness. Features Append-only decision and submission logs QuickChart visualizations for fast validation (e.g. TRUE vs FALSE completion rates) Optional integration with: Power BI Google Analytics 4 Supports Completion rate analysis Funnel tracking Source/platform performance Decision auditing Design Principles Separation of concerns** (ingestion ≠ decision ≠ outreach ≠ analytics) AI with hard guardrails** (strict schemas, source-only facts) Append-only logging** (analytics-safe, debuggable) Modular & extensible** (plug-and-play data sources) Human-readable + machine-usable outputs** Constraints & Notes Only public, professional information is used No private or speculative data HTTP scraping avoided unless necessary Power BI Embedded is not required Workflow designed and implemented end-to-end in ~3 days Use Cases Marketing Audience discovery Agent segmentation Personalization at scale Campaign readiness Funnel automation Sales Lead qualification Deduplication Outreach execution Status tracking Pipeline hygiene Tech Stack Automation:** n8n AI:** OpenAI (GPT) Scripting:** JavaScript Data Stores:** Google Sheets Email:** Gmail Visualization:** QuickChart BI (optional):** Power BI, Google Analytics 4 Cloud Sources:** AWS S3, Azure Blob, BigQuery Status This workflow is production-ready, modular, and designed for extension into other sales or marketing domains beyond literary outreach.

How it works User Signup & Verification: The workflow starts when a user signs up. It generates a verification code and sends it via SMS using Twilio. Code Validation: The user replies with the code. The workflow checks the code and, if valid, creates a session for the user. Conversational AI: Incoming SMS messages are analyzed by Chat GPT AI for sentiment, intent, and urgency. The workflow stores the conversation context and generates smart, AI-powered replies. Escalation Handling: If the AI detects urgency or frustration, the workflow escalates the session—alerting your team and sending a supportive SMS to the user. Set up steps Estimated setup time:** 10–20 minutes for most users. What you’ll need:** A free n8n account (self-hosted or cloud) Free Twilio account (for SMS) OpenAI API key (for AI) A PostgreSQL database (Supabase, Neon, or local) Setup process:** Import this workflow into n8n. Add your Twilio and OpenAI credentials as environment variables or n8n credentials. Update webhook URLs in your Twilio console (for incoming SMS). (Optional) Adjust sticky notes in the workflow for detailed, step-by-step guidance.