Basic LLM Chain Workflows
205 Ergebnisse — ausschließlich quellenverknüpfte n8n-Referenzen
Save Amazon reviews to Notion with ScraperAPI and OpenAI GPT-5 Mini
Quick Overview This workflow runs every Monday to scrape recent Amazon product reviews via ScraperAPI, uses OpenAI to classify sentiment and feature tags, and then saves each new review into a Notion database with structured properties and a formatted page body. How it works Runs every Monday at 8am and loads a configured watchlist of Amazon ASINs plus Notion and locale settings. Fetches Amazon product data (including recent reviews) for each ASIN using ScraperAPI. Extracts reviews from each response and only forwards reviews that have not been seen in previous runs, capped per ASIN. Sends each new review to OpenAI to return a JSON sentiment label, 1–4 feature tags, and a one-sentence summary. Normalizes the AI output, clips long review text to fit Notion limits, and converts the review date into an ISO date. Creates a new page in the target Notion database for each review, filling properties like Sentiment, Stars, Feature tags, Product, Review date, and metadata. Setup Add ScraperAPI credentials and ensure the ScraperAPI Amazon Product (SDE) endpoint is available for your account. Add Notion API credentials, share the target database with your Notion integration, and copy the data
Validate startup ideas and generate business plans from Telegram with Perplexity and GPT-4o
Quick overview This workflow receives startup ideas via a Telegram bot, uses OpenAI (GPT-4o and GPT-4o mini) plus Perplexity to score, research, and validate them, then generates a full business plan in Google Docs, logs key results to Google Sheets, and returns the plan link in Telegram. How it works Receives a Telegram message containing a raw startup idea. Uses OpenAI (GPT-4o mini) to structure the idea, detect its language, and assign an initial 1–10 idea score with improvement feedback. If the idea score is below the configured threshold, sends the score reasoning back to Telegram and stops. If the score meets the threshold, asks in Telegram for approval to run full research and plan generation. After approval, uses Perplexity to research the target market and competitors and then uses OpenAI (GPT-4o) to structure the findings, score market and competition, and generate differentiation and moat notes. Uses OpenAI (GPT-4o mini) to validate demand, risks, and go-to-market approach, then computes a composite score and recommendation. Uses OpenAI (GPT-4o) to write a full business plan, saves it to a Google Doc, appends a summary row to Google Sheets, and sends the Google Doc link
WMonitor new template releases with OpenAI and log insights to Telegram and Google Sheets
Quick overview This workflow runs daily to check the public n8n Templates API for newly published templates in a chosen category, generates improvement suggestions with OpenAI, logs each new template to Google Sheets, and sends a Telegram digest (with an optional all-clear message when nothing new is found). How it works Runs every day at 9 AM on a schedule. Fetches the latest templates for the configured category from the n8n Templates API. Extracts key metadata for each template and compares template IDs against a stored “seen” list to detect newly published items. For each new template, sends its details to an OpenAI chat model to generate 4–6 business-focused improvement tips. Appends one row per new template (including the AI tips and metadata) to a Google Sheets spreadsheet. Builds a combined digest of all new templates and posts it to a Telegram chat, or sends an optional all-clear message when no new templates are found. Setup Add an OpenAI API credential and select the model to use for the analysis. Add a Google Sheets OAuth credential, then choose the target spreadsheet and sheet tab and ensure the header columns match the fields being appended. Add a Telegram bot credent
Qualify WhatsApp real estate leads with Gemini and Supabase
Quick overview This workflow triggers on incoming WhatsApp messages, uses Google Gemini to extract and score real estate lead details, stores each lead in Supabase, and sends a WhatsApp alert to the agent only for high-intent inquiries based on configurable score thresholds. How it works Triggers when a new WhatsApp message is received via the WhatsApp Business Cloud API. Pulls the sender name, phone number, and message text and applies your configured scoring thresholds and agent contact number. Sends the message to Google Gemini to extract structured lead details (budget range, property type, location preference, timeline, and intent score). Inserts the extracted lead data into a Supabase leads table for tracking. Routes the lead based on the intent score and sends a formatted WhatsApp message to the agent for high-intent leads. Leaves medium- and low-intent leads logged in Supabase without sending an agent alert. Setup Connect WhatsApp Business Cloud API credentials for both the incoming-message trigger and the WhatsApp send action, and activate the workflow to generate the webhook for your WhatsApp app. Add a Google Gemini (PaLM) API credential for the Gemini chat model. Add a
Triage support tickets with OpenRouter (OpenAI o3-mini) and ClickUp
Quick overview This workflow collects support tickets via an n8n form, uses OpenRouter (OpenAI o3-mini) to assess priority, severity, impact, and suggested diagnostics, and then creates a formatted task in ClickUp with the AI-generated incident details. How it works Receives a new ticket submission through an n8n form with subject, description, company, name, and email. Normalizes the submitted fields into a consistent ticket payload (customer name/email, subject, and description). Validates that the ticket has a description and that the email address contains an “@” symbol. Sends the ticket subject and description to OpenRouter (OpenAI o3-mini) to generate incident metadata, priority (1–4), impact, severity, affected service, and recommended diagnostics and next steps in structured JSON. Creates a new task in ClickUp using the ticket subject as the task name and adding the customer details plus the AI assessment and recommendations to the task description. Setup Create or select an n8n Form Trigger and share the form URL with users who should be able to submit tickets (configure any access restrictions as needed). Add an OpenRouter credential to the OpenRouter chat model node and
Track asset warranty deadlines with Google Sheets, Gmail, Todoist, Slack, and OpenAI
Quick overview This workflow runs daily to read an asset register from Google Sheets, calculate warranty expiry dates, and escalate upcoming deadlines via Gmail, Slack, and Todoist, while using OpenAI to draft vendor negotiation emails for high-value assets and updating expired items back in the sheet. How it works Runs every day at 08:30. Reads all assets from a Google Sheets register and calculates each item’s warranty expiry date and days remaining from the purchase date and warranty months. For already-expired assets, updates the Google Sheets register to set the status to “warranty expired.” For assets expiring within 7 days, posts an urgent Slack message and creates a Todoist task due on the warranty expiry date. For assets expiring within 30 days, emails the asset owner via Gmail asking them to choose whether to extend, replace, or let the warranty lapse. For 30-day warnings where the asset value is at least 2000, uses OpenAI to draft a vendor warranty-extension negotiation email and saves it as a Gmail draft for review. Setup Create a Google Sheets asset register with columns for asset, owner_email, purchase_date, warranty_months, vendor, value, and status. Add credentials
Triage Gmail and draft replies with Ollama, Telegram and Google Sheets
Quick Overview This workflow pulls unread Gmail messages, uses a local Ollama Llama 3.1 model to classify and extract action items, drafts a reply, and sends an approval request to Telegram before creating a threaded Gmail draft and logging the decision to Google Sheets. How it works Runs manually and fetches up to 10 unread emails from Gmail. Normalizes each email into a consistent structure (sender, subject, body, message ID, and thread ID) and classifies it with Ollama into urgent, action_needed, fyi, or spam. Continues only for emails classified as urgent or action_needed and marks all other categories as skipped. For actionable emails, uses Ollama to extract a task title and deadline and to draft a short professional reply as structured JSON. Sends the classification, extracted task/deadline, and draft reply to Telegram and waits for you to approve or decline. If approved, creates a Gmail draft reply in the original thread, adds a Gmail label (STARRED), and logs the approval/rejection plus details to Google Sheets. Setup Connect your Gmail OAuth2 credential and ensure it has permission to read messages, create drafts, and add labels. Install and run Ollama, pull the llama3.1:l
Schedule YouTube Shorts to Pinterest with Apify, Gemini, and an OpenAI model
Quick overview This workflow receives YouTube Shorts webhook events, downloads the video via Apify, uses Google Gemini and an OpenAI-compatible chat model to generate Pinterest SEO metadata and choose a board, then schedules a Pinterest video pin through Zernio (Late) for publishing. How it works Receives a webhook request for YouTube PubSubHubBub verification and responds with the provided hub challenge. Receives a POST webhook event for a new YouTube video and extracts the title, video ID, channel ID, and video URL from the feed payload. Uses Apify to fetch and process the YouTube Short and returns a downloadable MP4 URL. Sends the video to the Google Generative Language (Gemini) API to generate an analysis used for Pinterest-focused metadata. Uses a LangChain LLM chain (with structured output validation) to produce a Pinterest-ready title, description, hashtags, and a board selection from a fixed list. Maps the selected board name to a Pinterest board ID and schedules the video post to Pinterest via the Zernio (Late) API. Setup Create the YouTube webhook/PubSubHubbub subscription and configure it to call this workflow’s webhook URL at the manga-monarch-webhook path for both veri
Draft Google review reply emails with Gmail, OpenAI, and Google Sheets
Quick Overview This workflow monitors Gmail for Google Business Profile “new review” alert emails, uses OpenAI to extract the rating and review text and draft a policy-safe reply, then emails the draft to you and logs the review and reply draft to Google Sheets. How it works Triggers when a new Google Business Profile review notification email arrives in Gmail. Looks up the email’s message ID in a Google Sheets ledger to prevent drafting duplicate replies. Sends the email content and your configured business details to OpenAI to extract the rating, reviewer first name, and review text and generate a reply draft as structured JSON. Emails you a formatted message containing the review excerpt, the suggested reply, and a link to your Google reviews page. Appends a new row to Google Sheets with the message ID, extracted review details, the reply draft, a timestamp, and a “draft-sent-to-owner” status. Setup Connect your Gmail account and ensure Google review alerts are delivered from [email protected]. Add an OpenAI API key/credential and select the chat model in the OpenAI node. Create a Google Sheets “reply ledger” with columns like processed_at, gmail_message_id, rat
Generate sound effects from chat with Groq, ElevenLabs and Google Drive
Quick Overview This workflow turns an n8n Chat message into a generated sound effect using Groq (Llama 3.3) to refine the prompt, calls the ElevenLabs sound-generation API to create an MP3, uploads the file to Google Drive, and replies in chat with a shareable link. How it works Receives a message in an n8n Chat trigger containing the user’s description of a sound. Uses Groq (Llama 3.3) to rewrite the description into a single detailed ElevenLabs sound-effects prompt and choose duration and prompt-influence settings. Parses the model’s JSON response and clamps duration (0.5–30s) and prompt influence (0–1), falling back to the original message if parsing fails. Sends the prompt and settings to the ElevenLabs sound-generation API and downloads the generated MP3. Uploads the MP3 to Google Drive with a timestamped filename based on the prompt text. Responds in chat with the prompt used, the final settings, and a Google Drive link, or returns a friendly error message if generation fails. Setup Create an ElevenLabs API credential using HTTP Header Auth (header name xi-api-key) and select it on the ElevenLabs request. Add a Groq API credential and select it on the Groq Llama model node. C
Validate invoice tax compliance from Gmail using Groq, Notion, and Google Sheets
Quick overview This workflow monitors a Gmail inbox for PDF invoices, uses Groq (Llama 3.3) to extract structured invoice fields, validates the invoice against Purchase Orders in Google Sheets and tax rules in Notion, logs an audit entry to Notion, and notifies Slack and the supplier based on pass/fail. How it works Triggers every minute when a new email arrives in Gmail and downloads the attached PDF invoice. Extracts text from the PDF and sends it to Groq (Llama 3.3) to parse invoice fields into a structured JSON schema, including SEZ/LUT detection. Looks up the referenced PO number in Google Sheets and fetches applicable tax rules from a Notion database. Validates the invoice against the PO (existence, approval status, currency, and total amount) and against Notion tax rules (SEZ/import/domestic matching and GST expectations). Writes the compliance result, matched rule, and any violations to a Notion “Compliance Audit Log” database. If the invoice passes, posts an approval message to Slack and archives the PDF to a Google Drive folder. If the invoice fails, posts a blocking alert to Slack and emails the supplier a rejection notice listing the violations. Setup Connect your Gmail
Predict supplier churn and generate retention plans with Notion, Slack, and Groq
Quick overview This workflow runs weekly to pull supplier activity from Notion, engineer churn-risk features, and use Groq-hosted LLM prompts to classify supplier churn risk and generate retention plans. It updates each supplier record in Notion and posts a Slack alert only when a supplier is rated High risk. How it works Runs every week on a schedule. Retrieves all supplier records from a Notion database. Calculates behavioral risk features such as PO trend, engagement score, and delivery/financial/contract-risk flags from the Notion fields. Processes suppliers one at a time and sends the features to a Groq LLM to return structured JSON with churn risk level, risk score, confidence, and key drivers. Sends the churn assessment to a second Groq LLM prompt to generate a structured retention plan with priority, recommended actions, suggested owner, and summary. If the supplier’s churn risk is High, posts a formatted alert with drivers and recommended actions to a Slack channel. Updates the supplier’s Notion page with the churn risk, risk score, key drivers, retention plan, and a “Last Evaluated” timestamp, then continues to the next supplier. Setup Connect your Notion credentials and
Review contract risk and rewrite clauses with Groq, Google Drive, Notion, and Slack
Quick overview This workflow watches a Google Drive folder for newly uploaded contract PDFs, extracts key clauses with Groq-hosted LLMs, compares them to standard clauses stored in Notion, generates a structured risk report and clause rewrites, sends a Slack alert for high-risk contracts, and saves the review to Notion. How it works Triggers when a new file is created in a specific Google Drive folder. Downloads the file and extracts text from it (using PDF text extraction when the uploaded file is a PDF). Uses a Groq-hosted LLM to extract key contract clauses (payment terms, penalties, SLA, termination, renewal, liability, and data protection) into structured JSON. Pulls the company’s standard clause library from Notion and compares each extracted vendor clause to the corresponding standard text. Uses a Groq-hosted LLM to generate a structured legal risk report with an overall risk level, executive summary, clause-by-clause risk review, missing protections, and negotiation recommendations. Rewrites medium- and high-risk clauses with a Groq-hosted LLM to produce negotiation-ready alternative wording aligned to the Notion standards. If the overall risk level is High, posts a formatt
Send weekly Salesforce sales behavior coaching reports with Groq and Gmail
Quick overview This scheduled workflow pulls last week’s Salesforce opportunities, tasks, and events for a specific rep, computes activity and pipeline health metrics, uses Groq (LLM) to generate coaching insights, creates a QuickChart performance chart URL, and emails a weekly behavioral report via Gmail. How it works Runs weekly on a schedule. Retrieves a target Salesforce user and queries that user’s opportunities with activity in the last week. Builds an Opportunity ID list, then pulls related Salesforce Tasks and Events and merges them into a single activity stream alongside the opportunities. Calculates per-opportunity engagement metrics (touches, calls, emails, follow-ups, meetings) and the days since last activity based on activity subjects and dates. Aggregates the opportunity metrics into per-rep totals including revenue, won/lost deals, and a stale-deal count based on activity gaps. Generates a QuickChart URL visualizing weekly activity versus outcomes and sends the rep metrics to Groq to produce structured coaching insights. Combines the chart and AI insights and sends an HTML weekly coaching email through Gmail. Setup Connect Salesforce OAuth2 credentials and set the S
Track meal nutrition from photos with LINE, Google Gemini and Google Sheets
Quick Overview This workflow receives meal photos via LINE, uses Google Gemini to estimate nutrition facts and generate advice, stores the photo in Google Drive, logs the results to Google Sheets, and replies to the user in LINE with a formatted analysis. How it works Receives a POST webhook event from LINE when a user sends a message. Checks whether the incoming LINE message contains an image and stops processing if it does not. Downloads the image content from the LINE Messaging API and sends it to Google Gemini to identify foods, estimate nutrition values, and generate health guidance. If the AI response indicates the image is not food, sends a LINE push message asking the user to submit a clearer meal photo. If the AI response is valid, parses the returned text into structured fields (food items, macros, calories, score, and advice) and calculates remaining calories based on a daily goal. Uploads the meal photo to Google Drive, appends the nutrition log (including the Drive image URL) to Google Sheets, and sends the formatted nutrition summary back to the user via LINE. Setup Create a LINE Messaging API channel, enable the webhook, and add the workflow’s webhook URL (the /MealT
Send daily brand mention digests to Slack with ScraperAPI and OpenAI
Quick Overview This workflow runs every morning at 8am, searches Google News for configured brand terms using ScraperAPI, stores previously seen article URLs in an n8n Data Table, summarizes the new coverage with OpenAI, and posts a daily brand-mention digest to a Slack channel. How it works Runs every day at 8am on a schedule. Sets the search terms, Google News country and time-period filters, and the target Slack channel. Creates (if needed) and reads an n8n Data Table of previously seen article URLs. Queries Google News via ScraperAPI for each search term and extracts article details from the responses. Deduplicates results against the seen-articles table and the current run, then stores new article URLs back into the Data Table. Groups new articles by brand, asks OpenAI to write a per-brand Slack-formatted summary, and posts the final digest message to Slack. Setup Add ScraperAPI credentials and ensure your ScraperAPI plan supports the Google News SDE endpoint used by the workflow. Add an OpenAI credential that can access the configured chat model (gpt-5-mini) or change the model selection to one available in your account. Add a Slack credential with permission to post messages
Review stale Notion docs with Gmail alerts, Slack reports, and OpenAI
Quick overview This workflow runs every Friday to scan a Notion documentation database for pages not edited in 90+ days, marks them as “Needs review,” emails owners of critical stale docs via Gmail, and uses OpenAI to generate a prioritized weekly review plan that it posts to a Slack channel. How it works Runs every Friday at 10:00 on a schedule. Retrieves all pages from a selected Notion database and calculates how many days it has been since each page was last edited, along with its title, URL, owner email, and importance. Filters the list to only documentation pages that have been untouched for 90 days or more. Updates each stale page in Notion by setting its Status to “Needs review.” Sends a Gmail email to the page owner when the stale document is marked as Critical and an owner email is present. Aggregates all stale documents and sends them to OpenAI to draft a short, risk-ranked weekly docs review plan. Posts the generated review plan to a specified Slack channel. Setup Connect credentials for Notion, Gmail, OpenAI (Chat Model), and Slack. Select your target Notion database in the Notion “getAll” step and ensure it contains properties for Owner Email, Importance (Critical/Nor
WAnswer legal questions with Groq using CanLII and CourtListener
Quick overview This workflow collects a legal question via an n8n form, retrieves supporting authorities from CourtListener or CanLII, and uses a Groq-hosted Llama model to produce an answer grounded only in the retrieved text with verified, non-hallucinated citations. How it works Receives a legal question through an n8n form and captures the selected source database (CourtListener or CanLII) plus optional CanLII database and case IDs. Routes the request to CourtListener full-text search or to CanLII case metadata and citator endpoints based on the selected database. For CourtListener, pulls the top search results and fetches the full text of the top-ranked opinion; for CanLII, loads the selected case and a list of related cases from the CanLII citator. Normalizes the retrieved items into a single numbered “sources” block with excerpts that the model can cite. Sends the question and sources to a Groq Chat Model (Llama 3.3 70B) and parses the response into a structured format containing an answer, a supported flag, and a list of citations. Verifies every cited source index against the retrieved sources, drops any mismatches, and renders an HTML result page showing the answer, verif
Draft grounded Gmail support replies from a Notion KB with Groq and Cohere
Quick Overview This workflow ingests published Notion knowledge base articles into an in-memory vector store using Cohere embeddings, then monitors a support Gmail inbox and uses Groq to draft grounded reply emails based only on retrieved KB sources, saving the result as a Gmail draft for review. How it works Manually runs an ingestion flow that pulls all pages from a Notion database and keeps only articles marked as Published. Fetches each article’s Notion page blocks, assembles them into a single document, splits the text into chunks, and embeds the chunks with Cohere. Clears and loads the resulting embeddings and metadata into an in-memory vector store for retrieval. Triggers when an unread Gmail message arrives matching the support inbox query and normalizes the subject, body, sender, and thread details. Uses Groq to classify the email as a support question, noise, or already resolved, and continues only for real support questions. Embeds the question with Cohere, retrieves and reranks the most relevant KB chunks, and stops if the best match does not meet the configured relevance threshold. Uses Groq to draft a reply using only the retrieved sources and, if an answer is produce
Triage PubMed clinical literature with Gemini and Google Sheets and Docs
Quick overview Automatically retrieve recent PubMed articles, identify the three papers most worth reading first using AI, and generate structured clinical literature triage reports in Google Sheets and Google Docs. How it works Reads the first pending literature request from the Google Sheets "Search Requests" tab. Marks the request as “processing” in Google Sheets and builds the PubMed query parameters (keyword, max results, specialty, clinical question, and output language). Searches PubMed via the NCBI E-utilities API (esearch) and fetches the corresponding article abstracts and metadata as XML (efetch). Parses and normalizes the XML into a structured list of candidate articles including title, abstract, journal, publication year, DOI, and PubMed URL. Sends the aggregated candidate articles to Google Gemini to select and rank the best three papers and generate a structured clinical evaluation for each. Appends the three ranked papers with summaries and triage fields to a Google Sheets “Triage Results” tab. Generates a formatted triage report in Google Docs and updates the original request status to “completed” in Google Sheets. Setup Create a Google Sheets OAuth connection and
WGenerate SEO-friendly robots.txt with OpenAI and Google Drive
Quick overview This workflow runs manually to check a website’s existing robots.txt, detect the site’s CMS from the homepage HTML using OpenAI, and generate an optimized robots.txt (including the provided sitemap URL) that is saved as a file and uploaded to Google Drive. How it works Starts when you click “Execute workflow” and sets the target website URL and sitemap URL. Requests the site’s existing robots.txt via HTTP and checks whether the response returns status code 200. If robots.txt exists, the workflow stops without making changes. If robots.txt is missing, it fetches the website homepage HTML via HTTP. Sends the HTML to OpenAI to detect the CMS and parses the model output into structured JSON. Uses OpenAI again to generate a production-ready robots.txt tailored to the detected CMS and including the sitemap directive. Converts the generated text into a robots.txt file and uploads it to a chosen folder in Google Drive. Setup Add an OpenAI API credential and ensure the selected chat model is available for both CMS detection and robots.txt generation. Add a Google Drive OAuth2 credential and choose the target Drive and folder for the uploaded robots.txt file. Update the websit
Send AI market briefings to email and Discord with AlphaAI and GPT-4
Quick Overview This workflow runs every 15 minutes to fetch AlphaAI’s trending market news, filter for new high-relevance, ticker-linked stories, and post them to a Discord channel via webhook as rich embed cards with sentiment and impact details. How it works Runs every 15 minutes on a schedule trigger. Requests the current trending news feed from the AlphaAI API using Bearer authentication. Filters out already-posted articles, keeps only stories with relevance score ≥ 8 and at least one ticker, and formats up to 10 items into Discord embed cards with AlphaAI sentiment, confidence, actionability, and likely price impact. Posts a single Discord webhook message containing a header and the generated embeds, and stores the posted article IDs to prevent duplicates in future runs. Setup Create an AlphaAI API key and add it as an n8n HTTP Bearer Auth credential used by the AlphaAI request. Create a Discord channel webhook and paste its URL into the Discord webhook HTTP request node. Activate the workflow and keep it running on the same n8n instance so its stored posted-article IDs can be reused across executions.
Triage and retry failed workflow executions with Anthropic, Jira and OpenTelemetry
Quick overview This workflow triggers on n8n execution errors, uses Anthropic (Claude) to classify the failure as transient or logic, and then either retries the failed execution via the n8n API with exponential backoff or creates a Jira issue, while also sending incident telemetry to an OpenTelemetry collector. How it works Triggers automatically when an n8n workflow execution errors. Extracts key telemetry like workflow name, failing node, error message/stack, execution URL, and any detected HTTP status code. Sends the error context to Anthropic (Claude) to return structured JSON with a category, confidence, and remediation guidance. Combines the AI diagnostics with telemetry and tracks a per-incident retry counter (up to three attempts) to decide if the failure is eligible for automated retry. If the error is transient with sufficient confidence and retry budget remains, waits using exponential backoff and calls the n8n API to retry the failed execution, then records the retry outcome. If the error is not retry-eligible (or the retry budget is exhausted), creates a Jira issue with the diagnostics, execution link, and failure details. Posts an OpenTelemetry trace span to your col
Nurture leads from Google Sheets with Gmail, SMS, and OpenRouter AI
Quick overview Automatically nurture leads with AI-personalized email follow-ups (plus optional SMS) across 3 stages triggered hourly, respecting business hours, and fully tracked in Google Sheets. How it works Runs every hour, filtered to a business-hours window (default 9am–6pm, timezone configurable). Reads all leads from Google Sheets and filters those due for follow-up skipping replies, unsubscribes, and completed leads. Routes by stage Stage 1 (Welcome), Stage 2 (Check-in), or Stage 3 (Final nudge). AI writes the email an LLM (via OpenRouter) generates a personalized subject + body using the lead's name, source, and service of interest. Sends via Gmail, and optionally an SMS via Seven/Twilio (Day 1 and Day 4, with consent and dedupe checks). Updates Google Sheets advances the lead's stage, sets the next follow-up timestamp, and marks SMS sent. Setup Import all 4 workflows they share one Google Sheet. Paste your Sheet ID/tab name into each 🔧 CONFIG node (same Sheet ID throughout). Connect Google Sheets, Gmail, and OpenRouter credentials. Edit the 3 LLM prompt nodes to replace "YOUR NAME/company" with your actual brand name. (Optional) Connect Seven/Twilio for SMS, and adjust