AWS S3 and Google Drive integration

Monthly AI SEO Content Engine: 34 Assets to WordPress, LinkedIn & Socials Summary This workflow is an end-to-end, enterprise-grade content engine. It automates the entire lifecycle of a brand's content marketing: capturing business context via an n8n Form Trigger to generate a master strategy document, using real-time analytics to write 34 targeted assets, packaging them into a styled .docx file for review, and automatically generating images to publish the content across WordPress, LinkedIn, Facebook, and Instagram. Key features Automated Brand Strategy:** Uses an n8n Form Trigger to capture business details and generates a 16-section master Markdown strategy document saved to Google Drive. Data-Driven Content Planning:** Integrates Google Analytics 4 (GA4) and localized Google Trends to identify content gaps (high-bounce pages) and rising topics to inform the content plan. High-Volume AI Generation:** Leverages native n8n Google Gemini nodes to write 34 distinct assets per run: 6 SEO blogs, 12 LinkedIn posts, 8 educational social posts, 4 newsletters, and 4 long-form guides. Native Document Assembly:** Bypasses basic text outputs by dynamically assembling the generated content into a professionally styled, downloadable Microsoft Word (.docx) package with a generated table of contents. AI Image Generation:** Uses Google Gemini 2.5 Flash Image to generate custom, photorealistic featured images and social media graphics for every post natively within the flow. Omnichannel Publishing:** Parses the finalized .docx file, extracts the targeted content, and schedules it automatically to WordPress, LinkedIn, Facebook Pages, and Instagram Business with clamped timestamp validation. Automated Error Logging & Alerts:** Built-in error trapping that sends a detailed summary to your Gmail if any API fails, or if prerequisite files are missing before publishing begins. How it works This template is divided into three distinct pipelines that run sequentially: Pipeline A: Strategy Generation Trigger:** An n8n Form Trigger collects the company name, mission, audience, and core services. Process:** The native Google Gemini node generates a strict JSON strategy object, which a Code node formats into a comprehensive Markdown document. Storage:** The Google Drive node saves this context document directly to the root of your Google Drive. Pipeline B: Content Generation & Assembly Trigger:** Triggered manually via the Pipeline B trigger, or swap in a Schedule Trigger to run monthly. Context Gathering:** Fetches the Markdown strategy from Drive, pulls the last 30 days of GA4 data, and fetches current Google Trends via RSS. Generation:** Google Gemini is prompted in stages: first to build a Content Plan JSON, then to write the batches of blogs, social posts, and guides. Assembly:** A robust Code node compiles the raw text into a valid, styled .zip/.docx file and uploads it to the root of your Google Drive. Notification:** A Gmail node sends the team an email notification with a direct link to the finalized .docx package. Pipeline C: Multi-Platform Publishing Trigger:** Schedule Trigger set to run on the 1st of each month — adjust the time to run after Pipeline B completes. Extraction:** Searches Google Drive for the latest .docx package, unzips it, and extracts the raw XML text. (If missing, it safely aborts and alerts you). Processing:** Code nodes split the text into individual arrays for Blogs, LinkedIn, and Social posts, safely clamping publish dates to prevent API scheduling errors. Media & Publishing:** * Generates an image for each asset using Gemini 2.5 Flash Image. Uploads blog images to WordPress Media and creates a future-dated WordPress post. Publishes text and images natively to LinkedIn, Facebook, and Instagram (via AWS S3 temporary hosting). Nodes used n8n Form Trigger Schedule Trigger Code (Heavy JavaScript for data merging, XML parsing, and DOCX assembly) Google Gemini (Langchain Native Nodes for Text and Image) Google Drive Google Analytics Gmail LinkedIn Facebook Graph API AWS S3 (Temporary public storage for Instagram image ingestion) Compression, Set, If, Merge, HTTP Request (WordPress API) Setup instructions Credentials Setup: You will need active credentials for Google Drive, Google Analytics (OAuth2), Gmail, LinkedIn, Facebook Graph API, AWS S3, and a Google Gemini API key. Your LinkedIn credential must have the openid scope enabled to fetch the user URN dynamically. Run Pipeline A: Run the n8n Form Trigger manually, fill out your company details, and let it generate your initial Markdown strategy file in the root of your Google Drive. Configure Pipeline B: Open the Config: Pipeline B node and enter your GA4 Property ID, notification email address, the direct Drive link to the generated Markdown file, and your preferred Google Trends geographic/language codes. Configure Pipeline C: Open the Config: Pipeline C node and enter your WordPress domain, Facebook Page ID, Instagram Business ID, your S3 bucket details (used to temporarily host images for Instagram), and a notification email address. WordPress Auth: Ensure your WordPress site has Application Passwords enabled to use Basic Auth for the Upload to WP Media node. Activate: Turn the workflow on. Pipeline B and C will run automatically on their schedules. Requirements n8n version 1.60+** (Required for the node types and versions used in this template). AWS S3 bucket with public-read access** (Required to host image URLs temporarily so Instagram's Graph API can fetch them). Google Gemini API credentials** (Budget for ~100k-150k output tokens per monthly run). Google Workspace (Analytics, Drive, Gmail). WordPress site with Basic Auth enabled. LinkedIn account, Facebook Page, and Instagram Business account. Customization ideas Adjust Output Volume:** Modify the JSON prompt in the Build Content Plan Prompt node to generate weekly content (e.g., 2 blogs, 4 social posts) instead of massive monthly batches. Change the Tone:** Update the "Brand Voice" restrictions in the n8n Form Trigger or tweak the system prompts in the Code nodes to match a specific industry style (e.g., highly technical vs. casual). Add Human-in-the-Loop:** Replace the direct link between Pipeline B and C with a Wait node that pauses publishing until a manager clicks an approval webhook link sent via email. Use cases Marketing Agencies:** Scaling monthly content deliverables for multiple clients while ensuring the AI strictly adheres to different brand guidelines. SEO Consultants:** Automating high-volume, keyword-targeted blog clusters backed by Google Analytics gap data. Lean Startups:** Maintaining a massive omnichannel social media and blog presence without hiring a dedicated content team.

Blockify® Technical Manual Data Optimization Workflow Blockify Optimizes Data for Technical Manual RAG and Agents - Giving Structure to Unstructured Data for ~78X Accuracy, when pairing Blockify Ingest and Blockify Distill Learn more at https://iternal.ai/blockify Get Free Demo API Access here: https://console.blockify.ai/signup Read the Technical Whitepaper here: https://iternal.ai/blockify-results See example Accuracy Comparison here: https://iternal.ai/case-studies/medical-accuracy/ Blockify is a data optimization tool that takes messy, unstructured text, like hundreds of sales‑meeting transcripts or long proposals, and intelligently optimizes the data into small, easy‑to‑understand "IdeaBlocks." Each IdeaBlock is just a couple of sentences in length that capture one clear idea, plus a built‑in contextualized question and answer. With this approach, Blockify improves accuracy of LLMs (Large Language Models) by an average aggregate 78X, while shrinking the original mountain of text to about 2.5% of its size while keeping (and even improving) the important information. When Blockify's IdeaBlocks are compared with the usual method of breaking text into equal‑sized chunks, the results are dramatic. Answers pulled from the distilled IdeaBlocks are roughly 40X more accurate, and user searches return the right information about 52% more accurate. In short, Blockify lets you store less data, spend less on computing, and still get better answers- turning huge documents into a concise, high‑quality knowledge base that anyone can search quickly. Blockify works by processing chunks of text to create structured data from an unstructured data source. Blockify® replaces the traditional "dump‑and‑chunk" approach with an end‑to‑end pipeline that cleans and organizes content before it ever hits a vector store. Admins first define who should see what, then the system ingests any file type—Word, PDF, slides, images—inside public cloud, private cloud, or on‑prem. A ​context‑aware splitter finds natural breaks, and a series of specially developed Blockify LLM model turns each segment into a draft IdeaBlock. GenAI systems fed with this curated data return sharper answers, hallucinate far less, and comply with security policies out of the box. The result: higher trust, lower operating cost, and a clear path to enterprise‑scale RAG without the cleanup headaches that stall most AI rollouts.

Multi-Agent Book Creation Workflow with AI Tool Node and GPT-4, DALL-E Who’s it for This workflow is designed for: Content creators** who want to generate books or structured documents automatically. Educators and trainers** who need quick course materials, eBooks, or study guides. Automation enthusiasts* exploring multi-agent systems using the newly released AI Tool Node* in n8n. Developers* looking for a reference template to understand orchestration of multiple AI agents* with structured output. How it works / What it does This template demonstrates a multi-agent orchestration system powered by AI Tool Nodes: Trigger: Workflow starts when a chat message is received. Book Brief Agent: Generates the initial book concept (title, subtitle, and outline). Book Writer Agent: Expands the outline into full content by collaborating with two sub-agents: Designer Agent → Provides layout/design suggestions. Content Writer Agent → Drafts and refines chapters. Generate Cover Image: AI generates a custom book cover image. Upload to AWS S3: Stores the cover image securely. Configure Metadata: Adds metadata for title, author, and description. Build Book HTML: Converts markdown-based content into HTML format. Upload to Google Drive: Saves the HTML content for processing. Convert to PDF: Transforms the book into a professional PDF. Archive to Google Drive: Final version is archived for safe storage. This workflow showcases multi-agent coordination, structured parsing, and seamless integration with cloud storage services. How to set up Import the workflow into n8n. Configure the following connections: OpenAI (for Book Brief, Book Writer, Designer, and Content Writer Agents). AWS S3 (for image storage). Google Drive (for document storage & archiving). Add your API keys and credentials in n8n credentials manager. Test the workflow by sending a sample chat message (e.g., “Write a book about AI in education”). Verify outputs in Google Drive (HTML + PDF) and AWS S3 (cover image). Requirements n8n* (latest version with AI Tool Node* support). OpenAI API key** (to power multi-agent models). AWS account** (with S3 bucket for storing images). Google Drive integration** (for document storage and archiving). Basic familiarity with workflow setup in n8n. How to customize the workflow Switch Models**: Replace gpt-4.1-mini with other models (faster, cheaper, or more powerful). Add More Agents: Introduce agents for **editing, fact-checking, or translation. Change Output Format: Export to **EPUB, DOCX, or Markdown instead of PDF. Branding Options: Modify the **cover generation prompt to include company logos or specific style. Extend Storage: Add **Dropbox, OneDrive, or Notion integration for additional archiving. Trigger Alternatives: Replace chat trigger with **form submission, webhook, or schedule-based runs. ✅ This workflow acts as a free, plug-and-play template to showcase how multi-agents + AI Tool Node can work together to automate complex content creation pipelines.

This workflow synchronizes files one-way from Google Drive to AWS S3. Google Drive Trigger node** triggers the workflow when a new file is added to the drive. AWS S3 node** gets all files stored in an S3 bucket. Merge node** merges the files from Google Drive and AWS S3 by key (file name) and keeps only the new file. AWS S3 node** uploads the new file in the S3 bucket.

This workflow transcribes audio files stored in AWS S3 and stores the information in Google Sheets. Google Drive Trigger node** triggers the workflow when a new file is uploaded in Google Drive. AWS S3 1 node** uploads the new file to an S3 bucket. AWS S3 2 node** gets the file from the S3 bucket. AWS Transcribe 1 node** creates a transciption job for the respective audio file. Wait node** waits for the transcription job from the previous node to be complete before proceeding with the workflow (necessary in case the service is busy or the file to be transcribed is large, delaying the workflow). AWS Transcribe 2 node** gets the information of the transcription job. Set node** sets the necessary values to be included in the data set. Google Sheets node** adds the transcription information to a sheet that serves as data set.