AI Automation
923 results — all source-linked n8n references
CWMulti-Platform Social Media Publisher with Blotato, GPT-4 Mini & Airtable
How it works • Automates multi-platform social media posting (Instagram, YouTube, TikTok, etc.) using AI-generated content • Integrates Airtable, n8n, and Blotato for full content scheduling and publishing • Supports both image and video uploads with dynamic text and account routing Set up steps • Takes ~15–30 minutes to set up depending on how many platforms you connect • Requires Airtable personal access token and Blotato API key • Uses sticky notes throughout the workflow to explain config, tokens, and troubleshooting clearly
WAutomated PR Code Reviews with GitHub, GPT-4, and Google Sheets Best Practices
AI-Agent Code Review for GitHub Pull Requests Description: This n8n workflow automates the process of reviewing code changes in GitHub pull requests using an OpenAI-powered agent. It connects your GitHub repo, extracts modified files, analyzes diffs, and uses an AI agent to generate a code review based on your internal code best practices (fed from a Google Sheet). It ends by posting the review as a comment on the PR and tagging it with a visual label like ✅ Reviewed by AI. 🔧 What It Does Triggered on PR creation Extracts code diffs from the PR Formats and feeds them into an OpenAI prompt Enriches the prompt using a Google Sheet of Swift best practices Posts an AI-generated review as a comment on the PR Applies a PR label to visually mark reviewed PRs ✅ Prerequisites Before deploying this workflow, ensure you have the following: n8n Instance (Self-hosted or Cloud) GitHub Repository with PR activity OpenAI API Key** for GPT-4o, GPT-4-turbo, or GPT-3.5 GitHub OAuth App** (or PAT) connected to n8n to post comments and access PR diffs (Optional) Google Sheets API credentials if using the code best practices lookup node. ⚙️ Setup Instructions 1. Import the Workflow in n8n, click on Wor
Create a Session-Based Telegram Chatbot with GPT-4o-mini and Google Sheets
How It Works This workflow creates an AI-powered Telegram chatbot with session management, allowing users to: Start new conversations** (/new). Check current sessions** (/current). Resume past sessions** (/resume). Get summaries** (/summary). Ask questions** (/question). Key Components: Session Management**: Uses Google Sheets to track active/expired sessions (storing SESSION IDs and STATE). /new creates a session; /resume reactivates past ones. AI Processing**: OpenAI GPT-4 generates responses with contextual memory (via Simple Memory node). Summarization: Condenses past conversations when requested. Data Logging**: All interactions (prompts/responses) are saved to Google Sheets for audit and retrieval. User Interaction**: Telegram commands trigger specific actions (e.g., /question [query] fetches answers from session history). Main Advantages 1. Multi-session Handling Each user can create, manage, and switch between multiple sessions independently, perfect for organizing different conversations without confusion. 2. Persistent Memory Conversations are stored in Google Sheets, ensuring that chat history and session states are preserved even if the server or n8n instance restarts.
Optimize Amazon Ads with GPT-4o for Bid, Budget & Keyword Recommendations
Overview This template is designed for Amazon sellers and advertisers who want to automate their campaign performance analysis and bidding strategy. It solves the common challenge of manually reviewing Sponsored Products reports and guessing how to adjust keywords, placements, and budgets. By combining Amazon Advertising reports with OpenAI's GPT-4o, this workflow delivers real-time, personalized optimization instructions — automatically. Features 📥 Automatically downloads Sponsored Products reports from Google Drive 🧠 Uses AI to analyze campaign, keyword, placement, targeting, and budget performance 📊 Supports both .csv and .xlsx report formats 🔁 Handles multiple ASINs and scales easily across ad accounts 📧 Sends structured optimization recommendations to your inbox via Gmail 🗂 Built-in logic to normalize filenames and correctly map reports 🧹 Includes error handling and formatting cleanup for AI-ready input Requirements To use this workflow, you’ll need: An Amazon Ads account with access to Sponsored Products reports A Google Drive folder where Amazon Ads reports are delivered (manually or via Gmail automation) A Gmail account (for sending summaries) An OpenAI API key with
WGenerate & Enrich LinkedIn Leads with Apollo.io, LinkedIn API, Mail.so & GPT-3.5
Note: Now includes an Apify alternative for Rapid API (Some users can't create new accounts on Rapid API, so I have added an alternative for you. But immediately you are able to get access to Rapid API, please use that option, it returns more detailed data). *Scroll to bottom for APify setup guide* This n8n workflow automates LinkedIn lead generation, enrichment, and activity analysis using Apollo.io, RapidAPI, Google Sheets and Mail.so. Perfect for sales teams, founders, B2B marketers, and cold outreach pros who want personalized lead insights to drive better conversion rates. ⚙️ How This Workflow Works The workflow is broken down into several key steps, each designed to help you build and enrich a valuable list of LinkedIn leads: 1. 🔑 Lead Discovery (Keyword Search via Apollo) Pulls leads using Apollo.io's API based on keywords, industries, or job titles. Saves lead name, title, company, and LinkedIn URL to your Google Sheet. You can replace the trigger node from the form node to a webhook, whatsapp, telegram, etc, any way for you to send over your query variables over to initiate the workflow. 2. 🧠 Username Extraction (from LinkedIn URL) Extracts the LinkedIn username from pro
C
Automated Stock Analysis Reports with Technical & News Sentiment using GPT-4o
Stock Analysis Agent (Hebrew, RTL, GPT-4o) Overview Get comprehensive stock analysis with this AI-powered workflow that provides actionable insights for your investment decisions. On a weekly basis, this workflow: Analyzes stock data from multiple sources (Chart-img, Twelve Data API, Alphavantage) Performs technical analysis using advanced indicators (RSI, MACD, Bollinger Bands, Resistance and Support Levels) Scans financial news from Alpha Vantage to capture market sentiment Uses OpenAI's GPT-4o to identify patterns, trends, and trading opportunities Generates a fully styled, responsive HTML email (with proper RTL layout) in Hebrew Sends detailed recommendations directly to your inbox Perfect for investors, traders, and financial analysts who want data-driven stock insights - combining technical indicators with news sentiment for more informed decisions. Setup Instructions Estimated setup time: 15 minutes Required credentials: OpenAI API Key Chart-img API Key (free tier) Twelve Data API Key (free tier) Alpha Vantage API Key (free tier) SMTP credentials (for email delivery) Steps: Import this template into your n8n instance. Add your API keys under credentials. Configure the SMTP E
Assign Requests Using AI and Send Reminders Based On NocoDB Kanban Board Status
Who is it for? This is automation for support project manager, which helps not only to keep developres informed but also automatically keep clients in the loop - especially useful if you are managing SLA-like agreement. It is actually simple incident management board using free Kanban board, that is extended in functionality via N8N. How It Works? Script has two entry points. The first one is incident form. When incident details are provided, automation gets incident definitions from database and pushes both information to AI. AI comparse definitions with client request, refines incident priority and pushed it in NocoDB database. Second is schedule trigger, which is responsible for regular notificaitons on task status. If task is not picked up or delivered in proper time, then emails or slack messages are being sent both to client and responsible developer. How to set up? Clone automation Create (samples below) two NocoDB tables: one with definitions and second that servers as Kanban board (mind column naming!) Set up email and slack connection You should be ready to go Different incident naming If your incident level naming is different, you need to update few nodes and few column
SEnhance Chat Responses with Real-Time Search via Bright Data MCP & Gemini AI
Disclaimer This template is only available on n8n self-hosted as it's making use of the community node for MCP Client. Who this is for? The Chat Conversations with Bright Data MCP Search Engines & Google Gemini workflow is designed for users who need real-time, AI-enhanced conversations powered by live search engine results. This workflow is tailored for: Data Analysts - Who want live, search-based data fused with AI reasoning. Marketing Researchers - Seeking up-to-the-minute market or competitor insights via conversational AI. Product Managers - Exploring user needs, market trends, and competitor analysis in real time. AI Developers - Building dynamic applications that combine live search data with intelligent conversation agents. Growth Hackers - Who need fast, conversational research tools for campaign ideation, outreach, or content creation. What problem is this workflow solving? Traditional chatbots and AI systems often rely on static, outdated data. This workflow enables AI agents to fetch live search engine data and converse intelligently about it, making interactions dynamic, accurate, and highly contextual. This workflow solves the major gaps of: Outdated Knowledge: Regul
Scrape Web Data with Bright Data, Google Gemini and MCP Automated AI Agent
Disclaimer This template is only available on n8n self-hosted as it's making use of the community node for MCP Client. Who this is for? The Scrape Web Data with Bright Data and MCP Automated AI Agent workflow is built for professionals who need to automate large-scale, intelligent data extraction by utilizing the Bright Data MCP Server and Google Gemini. This solution is ideal for: Data Analysts - Who require structured, enriched datasets for analysis and reporting. Marketing Researchers - Seeking fresh market intelligence from dynamic web sources. Product Managers - Who want competitive product and feature insights from various websites. AI Developers - Aiming to feed web data into downstream machine learning models. Growth Hackers - Looking for high-quality data to fuel campaigns, research, or strategic targeting. What problem is this workflow solving? Manually scraping websites, cleaning raw HTML data, and generating useful insights from it can be slow, error-prone, and non-scalable. This workflow solves these problems by: Automating complex web data extraction through Bright Data’s MCP Server. Reducing the human effort needed for cleaning, parsing, and analyzing unstructured we
Extract, Transform LinkedIn Data with Bright Data MCP Server & Google Gemini
Disclaimer This template is only available on n8n self-hosted as it's making use of the community node for MCP Client. Who this is for? The Extract, Transform LinkedIn Data with Bright Data MCP Server & Google Gemini workflow is an automated solution that scrapes LinkedIn content via Bright Data MCP Server then transforms the response using a Gemini LLM. The final output is sent via webhook notification and also persisted on disk. This workflow is tailored for: Data Analysts : Who require structured LinkedIn datasets for analytics and reporting. Marketing and Sales Teams : Looking to enrich lead databases, track company updates, and identify market trends. Recruiters and Talent Acquisition Specialists : Who want to automate candidate sourcing and company research. AI Developers : Integrating real-time professional data into intelligent applications. Business Intelligence Teams : Needing current and comprehensive LinkedIn data to drive strategic decisions. What problem is this workflow solving? Gathering structured and meaningful information from the web is traditionally slow, manual, and error-prone. This workflow solves: Reliable web scraping using Bright Data MCP Server LinkedIn
Automatically Classify and Label Gmail Emails with Google Gemini AI
Description Quickly organize your inbox with AI! This simple workflow automatically classifies incoming emails into different categories — like High Priority, Work Related, or Promotions — and applies Gmail labels accordingly. Setup takes less than 2 minutes, and it runs 24/7, helping you stay focused on what matters most without manual sorting. Tools/Services Needed Gmail: To trigger the workflow and label emails. Google Gemini (or any LLM Model): To intelligently classify email content. How It Works Gmail Trigger: Detects every new incoming email. Text Classifier Node: Classifies the email content into predefined categories. Google Gemini Chat Model: Provides the AI-powered understanding behind the classification. Conditional Labeling: If the email is High Priority, label it accordingly. If it’s Work Related (e.g., internal emails), apply the work label. If it’s a Promotion, sort it into the promotions label. Gmail Labeling: Automatically adds the correct label to the email. Setup Instructions Connect your Gmail account to n8n. Connect your Google Gemini (or other LLM) credentials. Customize the categories and labels if needed. Activate the workflow — and that's it! Notes You can
Build your own N8N Workflows MCP Server
This n8n template shows you how to create an MCP server out of your existing n8n workflows. With this, any MCP client connected can get more done with powerful end-to-end workflows rather than just simple tools. Designing agent tools for outcome rather than utility has been a long recommended practice of mine and it applies well when it comes to building MCP servers; In gist, agents to be making the least amount of calls possible to complete a task. This is why n8n can be a great fit for MCP servers! This template connects your agent/MCP client (like Claude Desktop) to your existing workflows by allowing the AI to discover, manage and run these workflows indirectly. How it works An MCP trigger is used and attaches 4 custom workflow tools to discover and manage existing workflows to use and 1 custom workflow tool to execute them. We'll introduce an idea of "available" workflows which the agent is allowed to use. This will help limit and avoid some issues when trying to use every workflow such as clashes or non-production. The n8n node is a core node which taps into your n8n instance API and is able to retrieve all workflows or filter by tag. For our example, we've tagged the workflo
Perform SEO Keyword Research & Insights with Ahrefs API and Gemini 1.5 Flash
This n8n workflow automates SEO keyword research by querying the Ahrefs API for keyword data and related keyword insights. The enriched data is then processed by an AI agent to format a response and provide valuable SEO recommendations. Perfect for SEO specialists, content marketers, digital agencies, and anyone looking to gain valuable insights into keyword opportunities to boost their rankings. ⚙️ How This Workflow Works This workflow guides you through the entire SEO keyword research process, from entering the initial keyword to receiving detailed insights and related keyword suggestions. 1. 🗣️ User Input (Keyword Query) The user enters a keyword they want to research. This input is captured by the Chat Input Node, ready for analysis. 2. 🤖 AI Agent (Input Verification) The AI Agent reviews the keyword input for any grammatical errors or extra commentary. If necessary, it cleans the input to ensure a seamless query to the API. 3. 🔑 Ahrefs API (Keyword Data Retrieval) The cleaned keyword is sent to the Ahrefs Keyword Tool API. This retrieves a detailed report including metrics like search volume, keyword difficulty, and CPC. 4. 💡 Related Keywords Extraction (Using JavaScript F
Update Hubspot engagement by parsing inbox mail with AI
Who is this for? This workflow is designed for Customer Success Managers (CSM), sales, support, or marketing teams using HubSpot CRM who want to automate customer engagement tracking when new emails arrive. It’s ideal for businesses looking to streamline CRM updates without manual data entry. Problem Solved / Use Case Manually logging email interactions in HubSpot is time-consuming. This workflow automatically parses incoming emails, checks if the sender exists in HubSpot, and either: Creates a new contact + logs the email as an engagement (if the sender is new). Logs the email as an engagement for an existing contact. What This Workflow Does Triggers when a new email arrives in a connected IMAP inbox. Parses the email using AI (OpenAI) to extract structured data. Searches HubSpot for the sender’s email address. Updates HubSpot: Creates a contact (if missing) and logs the email as an engagement. Or logs the engagement for an existing contact. Setup Configure Email Account: Replace the default IMAP node with your email provider HubSpot Credentials: Add your HubSpot API key in the HubSpot nodes. OpenAI Integration: Ensure your OpenAI API key is set for email parsing. Customization Ti
Resume Screening & Behavioral Interviews with Gemini, Elevenlabs, & Notion ATS
Description Candidate Engagement | Resume Screening | AI Voice Interviews | Applicant Insights This intelligent n8n workflow automates the process of extracting and scoring resumes received through a company career page, populating a Notion database with AI insights where the recruiter or hiring manager can automatically invite the applicant to an instant interview with an Elevenlabs AI voice agent. After the agent conducts the behavior-based interview, the workflow scores the overall interview against customizable evaluation criteria and updates the Notion database with AI insights about the applicant. AI Powered Resume Screening & Voice AI that interviews like a Recruiter! AI Insights in Notion dashboard Who is this for? HR teams, recruiters, and talent acquisition professionals This workflow is ideal for HR teams, recruiters, and talent acquisition professionals looking for a foundational, extensible framework to automate early stage recruiting. Whether you're exploring AI for the first time or scaling automation across your hiring process, this template provides a base for screening, interviewing, and tracking candidates—powered entirely by n8n, Elevenlabs, Notion, and LLM inte
C
Chat with Your Email History using Telegram, Mistral and Pgvector for RAG
Who is this for? Everyone! Did you dream of asking an AI "what hotel did I stay in for holidays last summer?" or "what were my marks last semester like?". Dream no more, as vector similarity searches and this workflow are the foundations to make it possible (as long as the information appears in your e-mails 😅). 100% Local and Open Source! This workflow is designed to use locally-hosted open source. Ollama as LLM provider, nomic-embed-text as the embeddings model, and pgvector as the vector database engine, on top of Postgres. Structured AND Vectorized This workflow combines structured and semantic search on your e-mail. No need for enterprise setups! Leverage the convenience of n8n and open source to get a bleeding edge solution. Setup You will need a PGVector database with embeddings for all your email. Use my other template Gmail to Vector Embeddings with PGVector and Ollama to set it up in a breeze! Make a copy of my Email Assistant: Convert Natural Language to SQL Queries with Phi4-mini and PostgreSQL, you will need it for structured searches. Install this template and modify the Call the SQL composer Workflow step, to point at your copy of the SQL workflow. Adjust the rest o
Gmail to Vector Embeddings with PGVector and Ollama
Gmail to Vector Embeddings with PGVector and Ollama Who is this for? Everyone! Did you dream of asking an AI "what hotel did I stay in for holidays last summer?" or "what were my marks last semester like?". Dream no more, as vector similarity searches and this workflow are the foundations to make it possible (as long as the information appears in your e-mails 😅). 100% local This workflow is designed to use locally-hosted open source. Ollama as LLM provider, nomic-embed-text as the embeddings model, and pgvector as the vector database engine, on top of Postgres. But.. how?! Firstly, specify the date you created your Gmail account on, then manually run the workflow in order to bulk read all your e-mail in monthly batches. Your database is now populated! Now it's the task for other workflows to query the vector database. Activate the workflow so that new e-mail is continuously added by the Gmail Trigger upon receiving it. Structured AND Vectorized This workflow stores your e-mail activity in two ways: In a structured table In a vector embeddings table And the information in both of them can be correlated by Gmail's messages id, which is stored in the vectors table as metadata propert
Email Assistant: Convert Natural Language to SQL Queries with Phi4-mini and PostgreSQL
Who is this for? 🧑🏻🫱🏻🫲🏻🤖 Humans and Robots alike. This workflow can be used as a Chat Trigger, as well as a Workflow Trigger. It will take a natural language request, and then generate a SQL query. The resulting query parameter will contain the query, and a sqloutput parameter will contain the results of executing such query. What's the use case? This template is most useful paired with other workflows that extract e-mail information and store it in a structured Postgres table, and use LLMs to understand inquiries about information contained in an e-mail inbox and formulate questions that needs answering. Plus, the prompt can be easily adapted to formulate SQL queries over any kind of structured database. Privacy and Economics As LLM provider I'm using Ollama locally, as I consider my e-mail extremely sensitive information. As model, phi4-mini does an excellent job balancing quality and efficiency. Setup Upon running for the first time, this workflow will automatically trigger a sub-section to read all tables and extract their schema into a local file. Then, either by chatting with the workflow in n8n's interface or by using it as a sub-workflow, you will get a query and a
Real-time Crypto News & Sentiment Analysis via Telegram with GPT-4o
Stay on top of the latest crypto news and market sentiment instantly, all inside Telegram! This workflow aggregates articles from the top crypto news sources, filters for your topic of interest, and summarizes key news and market sentiment using GPT-4o AI. Ideal for crypto traders, investors, analysts, and market watchers needing fast, intelligent news briefings. > 💬 Just type a coin name (e.g., "Bitcoin", "Solana", "DeFi") into your Telegram AI Agent—and get a smart news digest. How It Works Telegram Bot Trigger User sends a keyword (e.g., "Ethereum") of questions to the Telegram AI Agent. Keyword Extraction (AI-Powered) An AI agent identifies the main topic for better targeting. News Aggregation Pulls articles from 9 major crypto news RSS feeds: Cointelegraph Bitcoin Magazine CoinDesk Bitcoinist NewsBTC CryptoPotato 99Bitcoins CryptoBriefing Crypto.news Filtering Finds and merges articles relevant to the user's keyword. AI Summarization GPT-4o generates a 3-part summary: News Summary Market Sentiment Analysis List of Article Links Telegram Response Sends a structured, easy-to-read digest back to the user. 🔍 What You Can Do with This Workflow 🔹 Summarize breaking news for an
Extract & Classify Invoices & Receipts with Gmail, OpenAI and Google Drive
Who is it for? Anyone who wants to automatically aggregate their invoices or receipts. Main beneficiaries: small business owners and freelancers. How it works Creates a folder in Google Drive for uploading invoices and receipts. Responds (Webhook response) with URL to the created folder. Gets all emails with attachments from a Gmail mailbox. (Optional) Filters emails, e.g. exclude emails sent to specific address. Filters only PDF attachments. Classifies all PDF attachment contents with an AI model (is it a receipt or an invoice?). Uploads receipts and invoices to the created Google Drive folder and optionally sends an email with the attachments to, e.g., your accountant. Pre-conditions/Requirements Gmail and Google Drive accounts A Google Cloud OAuth 2.0 Client ID or a service account with Google Drive and Gmail APIs enabled OpenAI API account and API key Set up steps Provide credentials for the nodes: Gmail, Google Drive, OpenAI. Configure parameters in the "Configure" node. Most importantly: "sendInvoicesTo" for the email address where invoices/receipts should be sent. It uses a Webhook node trigger. It expects a body with a schema such as: { "name": "getInvoicesAndReceiptsFromEm
Automated Instagram Comment Replies using Gemini AI with Context-Aware Responses
Instagram Auto-Comment Responder with AI Agent Integration Version: 1.1.0 ‧ n8n Version: 1.88.0+ ‧ License: MIT A fully automated workflow for managing and responding to Instagram comments using AI agents. Designed to improve engagement and save time, this system listens for new Instagram comments, verifies and filters them, fetches relevant post data, processes valid messages with a natural language AI, and posts context-aware replies directly on the original post. Key Features 💬 AI-Driven Engagement: Intelligent responses to comments via a GPT-powered agent. ✅ Webhook Verification: Handles Instagram webhook handshake to ensure secure integration. 📦 Data Extraction: Maps incoming payload fields (user ID, username, message text, media ID) for processing. 🚫 Self-Comment Filtering: Automatically skips comments made by the account owner to prevent loops. 📡 Post Data Retrieval: Fetches the media’s id and caption from the Graph API (v22.0) before generating a reply. 🧠 Natural Language Processing: Uses a custom system prompt to maintain brand tone and context. 🔁 Automated Replies: Posts the AI-generated message back to the comment thread using Instagram’s API. 🧩 Modular Architectu
Compare Different LLM Responses Side-by-Side with Google Sheets
This workflow allows you to easily evaluate and compare the outputs of two language models (LLMs) before choosing one for production. In the chat interface, both model outputs are shown side by side. Their responses are also logged into a Google Sheet, where they can be evaluated manually or automatically using a more advanced model. Use Case You're developing an AI agent, and since LLMs are non-deterministic, you want to determine which one performs best for your specific use case. This template is designed to help you compare them effectively. How It Works The user sends a message to the chat interface. The input is duplicated and sent to two different LLMs. Each model processes the same prompt independently, using its own memory context. Their answers, along with the user input and previous context, are logged to Google Sheets. You can review, compare, and evaluate the model outputs manually (or automate it later). In the chat, both responses are also shown one after the other for direct comparison. How To Use It Copy this Google Sheets template (File > Make a Copy). Set up your System Prompt and Tools in the AI Agent node to suit your use case. Start chatting! Each message w
Analyze Client Transcripts & Route Feedback with GPT-4o Mini, HubSpot, and Gmail
Who is this for? This workflow is designed for Customer Satisfaction Managers (CSM), sales professionals, and operations managers who need to automate the analysis of client transcripts, save summarized notes to HubSpot, and route relevant feedback to the appropriate departments via email. What problem is this workflow solving? / Use Case Manually processing client conversations, extracting key insights, and distributing them to the right teams is time-consuming and error-prone. This workflow automates: Transcript analysis** using AI (OpenAI) to identify relevant content. HubSpot integration** to log meeting notes against client records. Email routing** to ensure feedback reaches the correct departments (e.g., support, sales, product, admin). What this workflow does Input Transcript: Accepts a client conversation transcript (e.g., from emails, calls, or chats). HubSpot Sync: Searches for the client’s HubSpot ID using their email. Uploads a summarized version of the conversation as meeting notes. AI-Powered Routing: Uses an OpenAI model to analyze the transcript and categorize content by department. Triggers emails (via Gmail) to route feedback to the relevant teams. Form Completion
BIndeed Data Scraper & Summarization with Airtable, Bright Data & Google Gemini
Who this is for? Indeed Data Scraper & Summarization with Airtable, Bright Data and Google Gemini is an automated workflow that extracts company profile information from Indeed using Bright Data Web Unlocker, transforms the data using Google Gemini's LLM, and forward the transformed response with the summary to a specified webhook for downstream use. This workflow is tailored for: Recruiters and HR teams who want quick summaries of companies listed on Indeed. Market researchers and analysts needing structured insights into businesses. Founders, investors, and consultants scouting potential competitors, partners, or clients. No-code enthusiasts looking to automate data extraction and enrichment pipelines without manual scraping or parsing. What problem is this workflow solving? Manually gathering structured information about companies on Indeed is time-consuming and inconsistent. Pages vary in structure, and extracting clean, digestible summaries can require technical scraping expertise. This workflow automates: Extracting company data from Indeed reliably using Bright Data Web Unlocker. Cleaning and summarizing the extracted content using Google Gemini LLM. Storing structured insig