Filter cybersecurity news for your tech stack (OpenAI + Pinecone RAG)
What it does: Collects cybersecurity news from trusted RSS feeds and uses OpenAI’s Retrieval-Augmented Generation (RAG) capabilities with Pinecone to filter for content that is directly relevant to your organization’s tech stack. “Relevant” means the AI looks for news items that mention your specific tools, vendors, frameworks, cloud platforms, programming languages, operating systems, or security solutions — as described in your .txt scope documents. By training on these documents, the system understands the environment you operate in and can prioritize news that could affect your security posture, compliance, or operational stability. Once filtered, summaries of the most important items are sent to your work email every day. How it works Pulls in news from multiple cybersecurity-focused RSS feeds: The workflow automatically collects articles from trusted, high-signal security news sources. These feeds cover threat intelligence, vulnerability disclosures, vendor advisories, and industry updates. Filters articles for recency and direct connection to your documented tech stack: Using the publish date, it removes stale or outdated content. Then, leveraging your .txt scope documents stored in Pinecone, it checks each article for references to your technologies, vendors, platforms, or security tools. Uses OpenAI to generate and review concise summaries: For each relevant article, OpenAI creates a short, clear summary of the key points. The AI also evaluates whether the article provides actionable or critical information before passing it through. Trains on your scope using Pinecone Vector Store (free) for context-aware filtering: Your scope documents are embedded into a vector store so the AI can “remember” your environment. This context ensures the filtering process understands indirect or non-obvious connections to your tech stack. Aggregates and sends only the most critical items to your work email: The system compiles the highest-priority news items into one daily digest, so you can review key developments without wading through irrelevant stories. What you need to do: Setup your OpenAI and Pinecone credentials in the workflow Create and configure a Pinecone index (dimension 1536 recommended) Pinecone is free to setup. Setup Pinecone with a single free index. Use a namespace like: scope. Make sure the embedding model is the same for all of your Pinecone references. Submit .txt scope documents listing your technologies, vendors, platforms, frameworks, and security products. .txt does not need to be structured. Add as much detail as possible. Update AI prompts to accurately describe your company’s environment and priorities.
By Will CarlsonExtract marketing insights & generate content from TikTok videos with Dumpling AI & GPT-4
📄 What this workflow does This workflow turns TikTok videos into high-quality marketing insights and social-ready posts using Dumpling AI and GPT-4. It takes a TikTok URL, keyword, and product name, then automatically extracts the video transcript, analyzes the content for key marketing insights (pain points, outcomes, triggers), and rewrites it as a social media post that positions your product as the solution. Everything is logged to Google Sheets for use by your content or product team. --- 👤 Who is this for Product marketers doing UGC research Copywriters repurposing TikTok into content Founders or VAs turning viral clips into assets Agencies building research-based social proof --- ⚙️ How to set up ✅ Requirements Dumpling AI: For TikTok transcript extraction OpenAI GPT-4 or GPT-4o-mini: For analysis and rewriting Google Sheets: To log the results n8n Form Trigger: To input TikTok URL, Keyword, and Product --- 🔧 Setup Instructions Google Sheets Create a sheet with the following columns: Video URL, Original Transcription, Pain points, Desired outcomes, Triggers or motivating events, Interesting direct quotes, New Script Update the sheet ID and tab in the Google Sheets node Credentials Add your Dumpling AI key using HTTP Header Auth Use GPT-4 via OpenAI credentials Connect your Google Sheets using OAuth2 Customization (Optional) You can modify the GPT-4 prompts in the LangChain nodes to change tone, output structure, or content depth --- 🧠 How it works A form is submitted with a TikTok URL, keyword, and product Dumpling AI fetches and returns the TikTok transcript The VTT format is cleaned into plain text GPT-4 (via LangChain agent) extracts: Pain points Desired outcomes Motivating events Direct quotes GPT-4 then rewrites the transcript into a compelling marketing post Results are saved to Google Sheets for further use --- 🛠️ Customization ideas Push insights to Notion or Airtable instead of Sheets Use Claude or Gemini instead of GPT-4 Automatically generate image prompts to pair with the rewritten script Add notification email or Slack post when draft is ready --- This workflow gives marketers and founders a fast way to convert real social content into reusable copy, backed by authentic user voice and GPT-powered insights.
By YangAI-powered code review with linting, red-marked corrections in Google Sheets & Slack
Advanced Code Review Automation (AI + Lint + Slack) Who’s it for For software engineers, QA teams, and tech leads who want to automate intelligent code reviews with both AI-driven suggestions and rule-based linting — all managed in Google Sheets with instant Slack summaries. How it works This workflow performs a two-layer review system: Lint Check: Runs a lightweight static analysis to find common issues (e.g., use of var, console.log, unbalanced braces). AI Review: Sends valid code to Gemini AI, which provides human-like review feedback with severity classification (Critical, Major, Minor) and visual highlights (red/orange tags). Formatter: Combines lint and AI results, calculating an overall score (0–10). Aggregator: Summarizes results for quick comparison. Google Sheets Writer: Appends results to your review log. Slack Notification: Posts a concise summary (e.g., number of issues and average score) to your team’s channel. How to set up Connect Google Sheets and Slack credentials in n8n. Replace placeholders (<YOURSPREADSHEETID>, <YOURSHEETGIDORNAME>, <YOURSLACKCHANNEL_ID>). Adjust the AI review prompt or lint rules as needed. Activate the workflow — reviews will start automatically whenever new code is added to the sheet. Requirements Google Sheets and Slack integrations enabled A configured AI node (Gemini, OpenAI, or compatible) Proper permissions to write to your target Google Sheet How to customize Add more linting rules (naming conventions, spacing, forbidden APIs) Extend the AI prompt for project-specific guidelines Customize the Slack message formatting Export analytics to a dashboard (e.g., Notion or Data Studio) Why it’s valuable This workflow brings realistic, team-oriented AI-assisted code review to n8n — combining the speed of automated linting with the nuance of human-style feedback. It saves time, improves code quality, and keeps your team’s review history transparent and centralized.
By higashiyama Score telematics driving risk with Claude and adjust insurance premiums via HTTP, Gmail, and Slack
How It Works This workflow automates insurance premium adjustments by analyzing telematics data with AI-driven risk assessment and syncing changes across underwriting systems. Designed for carriers, actuaries, and underwriting teams managing usage-based insurance programs, it eliminates manual review of driving patterns, speed, braking, and mileage while ensuring compliance. Scheduled execution fetches telematics data via HTTP from vehicles or mobile apps. Anthropic Claude analyzes behavior with structured output parsing, generating risk scores from acceleration, harsh braking, speeding, and time-of-day driving. Calculator node applies scores to premiums, and HTTP node updates policy systems. High-risk cases trigger Gmail alerts to underwriting managers and Slack notifications to claims teams. Final HTTP sync ensures compliance across all systems. Setup Steps Configure Schedule node for desired analysis frequency Set up HTTP node with telematics platform API Add Anthropic API key to Chat Model node for behavioral risk analysis Connect policy management system API credentials in HTTP nodes Integrate Gmail and Slack with underwriting team addresses Prerequisites Anthropic API key, telematics data platform API access Use Cases Auto insurance carriers implementing usage-based insurance programs Customization Modify AI prompts to incorporate additional risk factors like weather conditions Benefits Reduces premium calculation time from days to minutes
By Cheng Siong Chin