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    • Get Qualified Leads in One Click from Apollo to Airtable

      ## You Don't Need More Tools. You Just Need the Right Leads. Why spend $1,000s on lead gen when your perfect leads are already waiting in Apollo? You've already filtered the ideal prospects. You know who they are, where they work, and what they do. Now **imagine turning that list into enriched, ready-to-contact leads—without paying pricey Apollo's recurring subscription** (spoiler: you will pay only $0.60 per 500 leads). ## From Filter to Outreach-Ready in Seconds With the Lead Generation System, you just drop your Apollo search URL. **The workflow does the rest:** - Scrapes all matching contacts from your Apollo filter - Enriches and organizes the data (names, roles, emails, LinkedIns, companies, etc.) - Delivers the final lead list to Airtable—or your CRM of choice No more manual exports. No CSV mess. No VA needed. Just qualified leads, cleaned and ready to go. ## Perfect For - Founders doing DIY outbound - Growth marketers scaling cold email - Agencies running lead-gen for clients - Anyone tired of paying too much for messy, outdated lists ## Setup Guide I built a step-by-step guide to set up this workflow in 5 to 10 minutes, available here: [https://notanothermarketer.gitbook.io/home/templates/lead-generation](https://notanothermarketer.gitbook.io/home/templates/lead-generation) This template is free. Enjoy!

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    • Automate Agile Project Setup in ClickUp with AI and Forms

      Streamline your Agile project management by automating project setup and task creation in ClickUp using AI-driven insights and form submissions.

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  1. AI Proposal Generator

    ## Overview Stop spending hours formatting proposals. This workflow turns a short post-call form into a high-converting, fully-personalized PandaDoc proposal—plus updates your CRM and drafts the follow-up email for you. After a sales call, just fill out a 3-minute form summarizing key pain points, solutions pitched, and the price. The workflow uses AI to generate polished proposal copy, then builds a PandaDoc draft using dynamic data mapped into the JSON body (which you can fully customize per business). It also updates the lead record in ClickUp with the proposal link, company name, and quote—then creates an email draft in Gmail, ready to send. ### Who's it for - Freelancers and consultants sending service proposals - Agencies closing deals over sales calls - Sales reps who want to automate proposal follow-up - Teams using ClickUp as their lightweight CRM ### How it works - After a call, fill out a short form with client details, pitch notes, and price - AI generates professional proposal copy based on form input - Proposal is formatted and sent to PandaDoc via HTTP request - ClickUp lead is updated with: - Company Name - Proposal URL - Quote/price - A Gmail draft is created using the proposal link and a thank-you message ### Example use case > You hop off a call, fill out: > - Prospect: Shopify agency > - Pain: No lead gen system > - Solution: Automated cold outreach > - Price: $2,500/month > > 3 minutes later: PandaDoc proposal is ready, CRM is updated, and your email draft is waiting to be sent. ### How to set up 1. Replace the form with your preferred tool (e.g., Tally, Typeform) 2. Connect PandaDoc API and structure your proposal template 3. Customize the JSON body inside the HTTP request to match your business 4. Link your ClickUp space and custom fields 5. Connect Gmail (or other email tool) for final follow-up draft ### Requirements - Form tool for capturing sales call notes - OpenAI or LLM key for generating proposal copy - PandaDoc API access - ClickUp custom fields set up for lead tracking - Gmail integration ### How to customize - Customize your PandaDoc proposal fields in the JSON body of the HTTP node - Replace ClickUp with another CRM like HubSpot or Notion - Adjust AI tone (casual, premium, corporate) for proposal writing - Add Slack or Telegram alerts when the draft is ready - Add PDF generation or auto-send email step

    n8nFree

  2. Estimate Construction Costs from Revit/IFC Models with GP-4 and Cloud

    Estimate **material price** and **total cost** for grouped BIM/CAD elements using an **LLM-driven** analysis. The workflow accepts an existing **XLSX** (from your model) or, if missing, can trigger a local **RvtExporter.exe** to generate one. It enriches each element group with quantities, pricing, confidence, and produces a **multi-sheet Excel** report plus a polished **HTML executive report**. ## What it does - **Reads grouped element data** (from XLSX or extracted via `RvtExporter.exe`). - Builds **enhanced prompts** with clear rules (volumes/areas are already aggregated per group). - Calls your selected **LLM** (OpenAI/Anthropic/etc.) to identify materials, pick the pricing unit, and estimate **price per unit** and **total cost**. - **Parses AI output**, adds per-group KPIs (cost %, rank), and aggregates **project totals** (by material, by category). - Exports a **multi-sheet XLSX** and an **HTML executive report** (charts, KPIs, top groups). ## Prerequisites - **LLM credentials** for your chosen provider (e.g., OpenAI, Anthropic). Enable exactly one chat node and connect credentials. - **Windows host** only if you want to auto-extract from `.rvt/.ifc` via `RvtExporter.exe`. If you already have an XLSX, Windows is **not required**. - Optional: Internet access on the LLM side for price lookups (model/tooling dependent). ## How to use 1. **Import** this JSON into n8n. 2. Open the **Setup** node(s) and set: - `project_file` - path to your `.rvt/.ifc` or to an existing grouped `*_rvt.xlsx` - `path_to_converter` - `C:\\DDC_Converter_Revit\\datadrivenlibs\\RvtExporter.exe` (optional) - `country` - used to guide price sources/standards (e.g., `Germany`) 3. In the canvas, **enable one LLM node** (e.g., OpenAI or Anthropic) and connect credentials; keep others disabled. 4. **Execute workflow** (Manual trigger). It will detect/build the XLSX, run analysis, then write the **Excel** and open the **HTML** report. ## Outputs - **Excel**: `Price_Estimation_Report_YYYY-MM-DD.xlsx` with sheets: - `Summary`, `Detailed Elements`, `Material Summary`, `Top 10 Groups` - **HTML**: executive report with charts (project totals, top materials, top groups). - Per-group fields include: *Material (EU/DE/US), Quantity & Unit, Price per Unit (EUR), Total Cost (EUR), Assumptions, Confidence*. ## Notes & tips - Quantities in the input are **already aggregated per group** - do **not** multiply by element count. - If you prefer XLSX-only extraction, run your converter with a `-no-collada` flag upstream. - Keep ASCII-safe paths and ensure write permissions to the output folder. ## Categories Data Extraction Files & Storage AI CAD/BIM Cost Estimation ## Tags `cad-bim`, `price-estimation`, `cost`, `revit`, `ifc`, `xlsx`, `html-report`, `llm`, `materials`, `qto` ## Author [DataDrivenConstruction.io](https://DataDrivenConstruction.io) [info@datadrivenconstruction.io](mailto:info@datadrivenconstruction.io) ## Consulting and Training We work with leading construction, engineering, consulting agencies, and technology firms around the world to help them implement open data principles, automate CAD/BIM processing, and build robust AI pipelines. If you would like to test this solution with your own data, or are interested in adapting the workflow to real project tasks, feel free to contact us. **Docs & Issues:** [Full Readme on GitHub](https://github.com/datadrivenconstruction/cad2data-Revit-IFC-DWG-DGN-pipeline-with-conversion-validation-qto)

    n8nFree

  3. Automate Business Lead Extraction from Google Maps to Google Sheets

    This n8n workflow automates the extraction of business leads from Google Maps using RapidAPI and stores the data in Google Sheets. It is ideal for lead generation, market research, and competitive analysis, ensuring efficient data collection with duplicate prevention.

    n8nFree

  4. Automate LinkedIn Outreach with AI-Personalized Connection Requests

    Streamline your LinkedIn outreach by generating targeted lead lists, creating AI-personalized icebreakers, and sending automated connection requests using Apollo, OpenAI, Apify, and PhantomBuster.

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  5. Automate AI-Driven Proposal Generation with OpenAI, Google Slides, and PandaDoc

    This workflow automates the creation of professional, personalized proposals using AI, Google Slides, and PandaDoc, enabling instant proposal generation during live sales calls.

    n8nFree

  6. Instant Multi-Channel Error Alerts for n8n Workflows

    Automatically receive real-time notifications of workflow errors via Telegram, Gmail, and other messaging platforms to ensure quick response and resolution.

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  7. Generate Multiple Language Blog Posts with OpenAI, Supporting Yoast & Polylang

    The **blogblitz: polylang** workflow streamlines the creation and publication of high-quality blog content using powerful automation with n8n, OpenAI's GPT and the WordPress API. It enables effortlessly generating SEO-friendly articles complete with metadata and optimized featured images, improving content freshness and search engine visibility. ![Screenshot 20250625 at 15.16.45.png](fileId:1580) ### Why Use blogblitz? - **Automate content creation** to keep your blog fresh and engaging - **Generate SEO-optimized posts** with expert-crafted titles, meta descriptions, and focus keyphrases - **Save hours** of manual writing, image sourcing, and SEO configuration - **Leverage AI** for topic ideation and high-quality writing tailored to international student audiences - **Seamlessly publish and manage drafts** directly on your WordPress site via API - **Produce captivating, relevant featured images** without external tools - **Support multilingual content creation** with randomized language selection for diversity ### Who Is This For? - Content strategists managing WordPress blogs needing efficient topic generation - SEO specialists wanting automated post creation with optimized metadata - Website owners aiming to maintain active, multilingual content - Marketers who want to leverage AI for high-quality, consistent article production ### What Problem Does It Solve? This workflow automates the entire editorial cycle—from generating engaging topics with AI, drafting full-length articles, producing featured images automatically, to posting drafts configured for SEO on WordPress—dramatically reducing editor workload and improving content output. ### What This Workflow Does 1. **Trigger** - Runs on manual trigger or a weekly schedule to ensure consistent content flow 2. **Fetch Site Context** - Retrieves recent posts, taxonomies, and WordPress API schema to understand site structure 3. **Generate Topic** - Uses OpenAI GPT-4.1-mini to roll a random language and craft a targeted blog post topic + SEO metadata 4. **Draft Article** - Composes a comprehensive, SEO-friendly article tailored to the generated topic 5. **Create Draft** - Posts the draft on WordPress with Yoast SEO fields populated 6. **Generate Image** - Creates a high-quality, cinematic featured image via AI 7. **Upload & Attach** - Uploads the image to the WordPress media library and sets it as the post's featured image --- ### Setup Instructions 1. **Import** the workflow file into n8n: 2. **Add credentials:** - WordPress API (with create-post & media permissions) - OpenAI API key (for GPT and image models) 3. **Customize** categories, languages, and schedule in the relevant nodes 4. **Adjust** the Schedule Trigger timing as desired (e.g., every Monday at 9 AM) 5. **Test** end-to-end on a staging WordPress site to verify drafts and images publish correctly ### Pre-Requirements - An operational **[n8n instance](https://n8n.partnerlinks.io/khaisastudio)** (Cloud or self-hosted) - WordPress site with REST API access & proper authentication - OpenAI account with API access for both language and image models - (Optional) Yoast SEO plugin installed for metadata recognition ### Customize It Further - Tweak OpenAI prompts for niche topics or additional languages - Add social-media nodes to auto-share new posts - Insert an editorial review step before publishing - Refine image prompts for different visual styles (e.g., "modern infographic" vs. "cinematic portrait") --- ### Nodes Used - **Manual Trigger** - **Schedule Trigger** (weekly) - **HTTP Request** (fetch posts, taxonomies, schema; upload media) - **Code** (JavaScript analyzers for API schema & taxonomy parsing) - **OpenAI Chat** (GPT-4.1-mini for topics & articles) - **OpenAI Image Generation** (for featured images) - **WordPress** (create draft post) - **Sticky Notes** (in-flow documentation) --- ### Support **Built by:** [Khaisa Studio](https://khaisa.studio) **Tags:** wordpress, marketing, polylang **Category:** Content Creation **Need a custom?** Contact me on **[LinkedIn](https://www.linkedin.com/in/khmuhtadin/)** or **[Web](https://khmuhtadin.com)**

    n8nFree

  8. EL: Extract and Parse Revit Model Data to Structured Excel

    Convert a **Revit model** to **Excel** and parse it into structured items ready for downstream EL. This minimal template runs a local `RvtExporter.exe`, checks success, derives the expected `*_rvt.xlsx` filename, reads it from disk, and parses it to data items in n8n. ## What it does 1. **Setup**: define `path_to_revit_converter` and `revit_file`. 2. **Run converter**: execute `RvtExporter.exe <converter> <revit_file>` (writes `*_rvt.xlsx` next to the RV). 3. **Check success**: branch on converter error output. 4. **Read Excel**: compute `<revit_file> *_rvt.xlsx` and read it from disk. 5. **Parse**: convert the workbook into structured items (rows → items). ## Prerequisites - **Windows** host (local executable and filesystem paths). - DDC Revit toolkit installed: `C:\\DDC_Converter_Revit\\datadrivenlibs\\RvtExporter.exe`. - A local `.rvt` you can read; the converter will write `*_rvt.xlsx` next to it. ## How to use 1. **Import** this JSON into n8n. 2. Open **“Setup - Define file paths”** and set: - `path_to_revit_converter`: `C:\\DDC_Converter_Revit\\datadrivenlibs\\RvtExporter.exe` - `revit_file`: e.g., `C:\\Sample_Projects\\your_project.rvt` 3. Run **Manual trigger**. 4. On success, the flow will read `*_rvt.xlsx` and emit parsed items. ## Outputs - On disk: `<YourProject>_rvt.xlsx` (created by the converter). - In n8n: parsed rows as items, ready for **Transform**/**Load** phases. ## Notes & tips - If your converter writes the Excel to a **different folder/file name**, update the “**Success - Create Excel filename**” node to point to the actual path. - Ensure write permissions in the project folder and avoid non-ASCII characters in paths when possible. - This template is purposefully minimal (Extract-only). Chain it with your own **Transform**/**Load** steps. ## Categories Data Extraction Files & Storage EL CAD/BIM ## Tags `cad-bim`, `revit`, `ifc`, `dwg`, `extract`, `xlsx`, `etl` ## Author [DataDrivenConstruction.io](https://DataDrivenConstruction.io) [info@datadrivenconstruction.io](mailto:info@datadrivenconstruction.io) ## Consulting and Training We work with leading construction, engineering, consulting agencies, and technology firms around the world to help them implement open data principles, automate CAD/BIM processing, and build robust EL pipelines. If you would like to test this solution with your own data, or are interested in adapting the workflow to real project tasks, feel free to contact us. **Docs & Issues:** [Full Readme on GitHub](https://github.com/datadrivenconstruction/cad2data-Revit-IFC-DWG-DGN-pipeline-with-conversion-validation-qto)

    n8nFree

  9. Automated Lead Capture and Scheduling via Conversational AI

    This workflow uses conversational AI to capture leads, check for duplicates in Salesforce, and schedule demos, enhancing lead management efficiency.

    n8nFree

  10. Batch Convert CAD/BIM Files to XLSX/DAE with Validation and Reporting

    # CAD2DAA: Batch Converter (Revit/IFC/DWG/DGN → XLSX/DAE) Batch-convert CAD/BIM files to analysis-ready **XLSX** and optional **DAE** with automatic verification and a clean HTML report. Runs locally via `RvtExporter.exe` and PowerShell on Windows. Supports configurable export modes - **basic (~309 categories)**, **standard (~724)**, and **complete (~1209)** - plus optional outputs such as **bounding boxes**, **Revit schedules**, and **PDF drawings**. ## What it does - Scans a **source folder** (optionally including subfolders) for `.rvt`, `.ifc`, `.dwg`, or `.dgn`. - For each file, runs: `RvtExporter.exe [input] [output.xlsx] [output.dae] [options]`. - Verifies outputs (existence + size) and aggregates results. - Generates a **summary HTML report** and opens it automatically on completion. ## Converter options - **Export modes:** `basic` | `standard` | `complete` | `custom` - **Flags:** `bbox` (BoundingBox to XLSX), `schedule` (Revit schedules), `sheets2pdf` (Sheets → PDF) - **Disable:** `-no-xlsx`, `-no-collada` - **Custom files:** `[<output file>]` and `[<category file>]` (used with `custom`) **Examples** - `basic bbox` - minimal export + BoundingBox - `complete schedule sheets2pdf` - full export + schedules + PDFs - `standard -no-collada` - XLSX only (skip DAE) ## Prerequisites - **Windows** host (PowerShell + local executable). - DDC Revit toolkit installed: `C:\DDC_Converter_Revit\datadrivenlibs\RvtExporter.exe` - Read access to the source folder and write access to the output folder. ## How to use 1. **Import** this JSON workflow into n8n. 2. Open **Set Configuration Parameters** and set: - `converter_path`: `C:\DDC_Converter_Revit\datadrivenlibs\RvtExporter.exe` - `source_folder`: folder with your projects - `output_folder`: folder for results - `include_subfolders`: `true` / `false` - `file_extension`: `.rvt` | `.ifc` | `.dwg` | `.dgn` - `options`: see **Converter options** 3. Run **Manual trigger**. 4. The workflow discovers files → runs conversions → verifies outputs → writes and opens the HTML report. ## Outputs - `*_ext.xlsx` - tabular data per input file. - `*_ext.dae` - lightweight 3D (if not disabled with `-no-collada`). - `CAD_Conversion_Report_YYYY-MM-DD_HH-MM-SS.html` - summary with: - success rate and progress - per-file and total processing time - input/output sizes and file paths ## Notes & tips - Uses PowerShell `Get-ChildItem` for discovery and `cmd /c start` to open the report. - With `-no-collada`, success/verification is XLSX-only (DAE is skipped). - Prefer ASCII paths and ensure write permissions in the output folder. ## Categories Data Extraction Files & Storage EL CAD/BIM ## Tags `cad-bim`, `revit`, `ifc`, `dwg`, `dgn`, `converter`, `batch`, `xlsx`, `dae`, `qto` ## Author DataDrivenConstruction.io ## Author [DataDrivenConstruction.io](https://DataDrivenConstruction.io) [info@datadrivenconstruction.io](mailto:info@datadrivenconstruction.io) ## Consulting and Training We work with leading construction, engineering, consulting agencies, and technology firms around the world to help them implement open data principles, automate CAD/BIM processing, and build robust EL pipelines. If you would like to test this solution with your own data, or are interested in adapting the workflow to real project tasks, feel free to contact us. **Docs & Issues:** [Full Readme on GitHub](https://github.com/datadrivenconstruction/cad2data-Revit-IFC-DWG-DGN-pipeline-with-conversion-validation-qto)

    n8nFree

  11. Automate Lead Engagement with AI-Driven WhatsApp Messages and Google Sheets

    This workflow captures leads from an inquiry form, crafts personalized WhatsApp messages using AI, and logs interactions in Google Sheets. It enhances lead engagement by automating initial outreach and tracking message success or failure.

    n8nFree

  12. Manage GoHighLevel CRM with Conversational AI Assistant and GPT-4

    # Your Conversational GoHighLevel CRM Assistant: Instantly manage contacts, deals, and tasks in GoHighLevel using simple chat commands. ![Screenshot 20250621 at 19.12.26.png](fileId:1560) --- ## Overview This automation sets up an intelligent AI assistant directly connected to your GoHighLevel CRM. Instead of clicking through menus and forms, you can now manage your entire sales pipeline through a simple chat conversation. It's like having a dedicated, 24/7 sales operations expert on your team, ready to act on your commands instantly. ## The Problem Managing a powerful CRM like GoHighLevel is essential, but it can be incredibly time-consuming. You're constantly jumping between screens to add a new contact after a call, update a deal's status, create a follow-up task, or check calendar availability. Each small action requires navigating different menus, filling out multiple fields, and saving your work. This constant context-switching kills productivity, creates opportunities for human error, and slows down your entire sales cycle. ## The Solution This workflow acts as your personal automated employee, transforming your GoHighLevel experience by giving you an AI-powered conversational assistant. Now, you can simply tell the AI what you need in plain English, and it gets done. When you send a message like, **Create a new contact for John Doe at john@email.com**, the automation instantly captures the information and creates the contact. Ask it to **Find all open deals for ABC Corp** and it will search your pipeline. Need to schedule a follow-up? Just say **Create a task to call John Doe next Tuesday.** This assistant handles everything from contact creation and opportunity management to task setting and appointment booking, turning tedious CRM admin into a fast and simple conversation. ## Simple Setup This workflow is a pre-built blueprint, designed to be up and running in minutes! - **1. Upload:** Simply upload the provided JSON file into your n8n instance. - **2. Connect:** Connect your app credentials (e.g., your GoHighLevel and OpenAI accounts). The workflow will show you exactly where. - **3. Activate:** Turn the workflow on, and it's ready to go! Let your new automated employee get to work. --- Explore more workflows Buy more workflows at: [adamcrafts](https://adamcrafts.cloudysoftwares.com) Custom workflows at: [adamcrafts@cloudysoftwares.com](mailto:adamcrafts@cloudysoftwares.com) [adamaicrafts@gmail.com](mailto:adamaicrafts@gmail.com) > Build once, customize endlessly, and scale your video content like never before.

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  13. Enhance HighLevel CRM with Intelligent Automation and Contextual AI

    Integrate advanced AI capabilities into HighLevel CRM to automate contact management, opportunity tracking, and task scheduling using contextual data retrieval and natural language processing.

    n8nFree

  14. Qualify Meta Ads Leads with WhatsApp Verification, Gemini AI, & Zoho CRM

    ## What Problem Does It Solve? Meta ads forms often generate unqualified leads from casual scrollers. This workflow uses WhatsApp and AI to automatically verify, qualify, and prioritize real leads - saving time and boosting sales efficiency. ## Description This workflow automates lead qualification for businesses using Meta Ads (Facebook/Instagram Lead Ads) to filter out irrelevant leads. It ensures only confirmed prospects enter your CRM by: - Collecting new Facebook leads - Verifying via WhatsApp confirmation - Classifying responses with AI - Updating CRM status based on intent When a new Facebook lead arrives: - Lead details are extracted (name/phone/email) - Zoho CRM is checked for existing contacts - WhatsApp confirmation request is sent - AI classifies the response (confirmed/declined/human/invalid) - CRM status is updated automatically - Sales team receives only verified leads ## Key Advantages for Meta Ads - Blocks 60%+ irrelevant leads based on WhatsApp non-response - Reduces fake submissions by requiring active confirmation - Prevents CRM bloat through duplicate checking - Identifies hot leads via instant human-requested escalation - Saves sales team hours by auto-declining no responses ## Features - Facebook Lead Ads integration via Graph API - WhatsApp messaging via Twilio - AI response classification (Gemini) - Zoho CRM synchronization - Duplicate lead prevention - Customizable confirmation flow - Error-resistant JSON parsing - CRM owner assignment - Status-based routing ## Requirements - Facebook Access Token with ads_management & leads_retrieval permissions - Twilio Account with WhatsApp-enabled number - Zoho CRM with custom Status field - Gemini API Key (or alternative LLM) - n8n credentials configured for: - Twilio (API SID/token) - Zoho CRM (OAuth2) - Google Gemini (or alternative LLM) ## Customization Tips 1. Adjust Classification Criteria - Modify the AI prompt in Classify Response (AI) node 2. Customize CRM Status Values - Update field IDs in Zoho nodes 3. Modify Messaging - Edit WhatsApp templates in Send WhatsApp Confirmation 4. Set Owner Assignment - Replace owner ID in Prepare Owner ID node ## Use Case Examples - Real Estate Agencies: Filter speculative inquiries from serious buyers - Medical Clinics: Verify appointment requests before scheduling - SAAS Companies: Qualify free trial sign-ups - Education Providers: Confirm course interest before counselor assignment - Auto Dealerships: Screen test drive requests from tire-kickers If you need help, get in touch on [Linkedin](https://www.linkedin.com/in/abdallaelshikh0/).

    n8nFree

  15. Automate WhatsApp Welcome Messages for New Vtiger CRM Leads

    Automatically send personalized WhatsApp welcome messages to new leads in Vtiger CRM using Evolution API, ensuring efficient lead engagement and reducing manual tasks.

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  16. Interactive Q&A on Pipedrive Leads with OpenAI Integration

    Leverage OpenAI to ask natural-language questions about your Pipedrive leads. This workflow retrieves live lead data from Pipedrive and uses OpenAI to provide insightful answers, ensuring responses are based solely on your Pipedrive data.

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  17. Calculate Embodied Carbon (CO2) for Revit/IFC Models Using AI Classification

    Estimate **embodied carbon (CO2e)** for grouped BIM/CAD elements. The workflow accepts an existing **XLSX** (grouped element data) or, if missing, can trigger a local **RvtExporter.exe** to generate one. It detects category fields, filters out non-building elements, infers **aggregation rules** with AI, computes **CO2** using densities & emission factors, and exports a **multi-sheet Excel** plus a clean **HTML** report. ## What it does - **Reads or builds XLSX** (from your model via `RvtExporter.exe` when needed). - **Finds category/volumetric fields**; separates building vs. annotation elements. - Uses AI to **infer aggregation rules** (sum/mean/first) per header. - **Groups** rows by your `group_by` field and aggregates totals. - Prepares **enhanced prompts** and calls your LLM to classify materials and estimate CO2 (A1-A3 minimum). - **Computes project totals** and generates a **multi-sheet XLSX** + **HTML** report with charts and hotspots. ## Prerequisites - **LLM credentials** for one provider (e.g., OpenAI, Anthropic, Gemini, Grok/OpenRouter). Enable one chat node and connect credentials. - **Windows host** only if you want to auto-extract from `.rvt/.ifc` via `RvtExporter.exe`. If you already have an XLSX, Windows is **not required**. - Optional: mapping/classifier files (XLSX/CSV/PDF) to improve material classification. ## How to use 1. **Import** this JSON into n8n. 2. Open the **Setup/Parameters** node(s) and set: - `project_file` - path to your `.rvt/.ifc` **or** to an existing grouped `*_rvt.xlsx` - `path_to_converter` - `C:\\DDC_Converter_Revit\\datadrivenlibs\\RvtExporter.exe` (optional) - `group_by` - e.g., `Type Name` / `Category` / `IfcType` - `sheet_name` - default `Summary` (if reading from XLSX) 3. **Enable one LLM node** and attach credentials; keep others disabled. 4. **Execute** (Manual trigger). The workflow detects/builds the XLSX, analyzes, classifies, estimates CO2, then writes **Excel** and opens the **HTML** report. ## Outputs - **Excel** (`CO2_Analysis_Report_YYYY-MM-DD.xlsx`, ~8 sheets): Executive Summary, All Elements, Material Summary, Category Analysis, Impact Analysis, Top 20 Hotspots, Data Quality, Recommendations. - **HTML**: executive report with key KPIs and charts. - Per-group fields include: Material (EU/DE/US), Quantity & Unit, Density, Mass, CO2 Factor, Total CO2 (kg/tonnes), CO2 %, Confidence, Assumptions. ## Notes & tips - Input quantities (volumes/areas) are **already aggregated per group** - do **not** multiply by element count. - Use `-no-collada` upstream if you only need XLSX in extraction. - Prefer ASCII-safe paths and ensure write permissions to output folder. ## Categories Data Extraction | Files & Storage | AI | CAD/BIM | Carbon/ESG ## Tags `cad-bim`, `co2`, `carbon`, `embodied-carbon`, `lca`, `revit`, `ifc`, `xlsx`, `html-report`, `llm` ## Author [DataDrivenConstruction.io](https://DataDrivenConstruction.io) [info@datadrivenconstruction.io](mailto:info@datadrivenconstruction.io) ## Consulting and Training We work with leading construction, engineering, consulting agencies, and technology firms around the world to help them implement open data principles, automate CAD/BIM processing, and build robust AI pipelines. If you would like to test this solution with your own data, or are interested in adapting the workflow to real project tasks, feel free to contact us. **Docs & Issues:** [Full Readme on GitHub](https://github.com/datadrivenconstruction/cad2data-Revit-IFC-DWG-DGN-pipeline-with-conversion-validation-qto)

    n8nFree

  18. Automate LinkedIn Company Search and CRM Integration with Airtable

    Streamline your prospecting process by automatically searching LinkedIn for companies and adding them to your Airtable CRM. This workflow saves time and reduces errors by automating data retrieval and entry.

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