Browse 12,955 Workflows

By Khairul Muhtadin

Maintenance agreements only pay off when someone remembers the next service date. This n8n workflow takes a new agreement from a webhook, has gpt-6-luna write the welcome email, logs it to Google Sheets, then handles the follow-up: a daily check for services due within 3 days or overdue, and a weekly AI review of the agreement book. Last updated: October 2026. Quick Overview Agreements arrive on a webhook, get normalized and validated, and anything missing key details is rejected by email instead of being saved. Valid agreements get an AI-written welcome and land in the Agreements tab in Google Sheets with status active. Every morning at 07:00 the workflow checks the book: agreements due within 3 days or overdue get a reminder to the customer, and when anything is overdue the office gets one escalation email listing who to call. Every Monday at 09:00 an AI review goes to the office. How it works Receives the new agreement on the "When Agreement Added" webhook (POST, path hvac-agreement-intake-0930). Normalize New Agreement builds the record: agreement_id (auto-generated as AG-yyyyMMdd-### when not supplied), customer name, email, phone and address, system_type, filter_size, service_frequency_months, last_service_date, next_due_date, agreement_end_date, status set to active, office_email and welcomed_at. Validate Agreement requires customer_name, customer_email, next_due_date and office_email. Anything missing goes to Alert Office on Invalid Entry, which emails the office what was missing plus the posted values, and nothing is saved. Valid entries go to Draft Welcome Email, where gpt-6-luna writes a welcome under 130 words with a subject and a body. Prepare Welcome Email parses that JSON and merges it onto the agreement. Add Agreement to Tracker appends the record to the Agreements tab with reminder_count 0, then Email Welcome to Customer sends the welcome. Daily Service Check runs at 07:00, reads the Agreements tab, and Flag Due Agreements keeps active agreements with 3 days or fewer until next_due_date, adding days_left and an is_overdue flag. Draft Reminder Email has gpt-6-luna write a reminder under 120 words for each due agreement and Email Reminder to Customer sends it. Collate Overdue for Office then builds one email covering only overdue customers, with due date, days overdue and phone, and Email Overdue Alert to Office sends it. With nothing overdue, no office email goes out. Weekly Agreement Review runs every Monday at 09:00 and Collate Agreement Stats counts active agreements, services due within 7 days, overdue ones and renewals ending within 60 days. Draft Weekly Review has gpt-6-luna write the review and Email Weekly Review to Office sends it. Setup Create a Google Sheets file with a tab named "Agreements" and these columns: agreement_id, customer_name, customer_email, customer_phone, address, system_type, filter_size, service_frequency_months, last_service_date, next_due_date, agreement_end_date, status, office_email, welcomed_at, last_reminded_at, reminder_count. Add credentials for Google Sheets OAuth2, Gmail OAuth2 and an [OI] chat model. Paste your spreadsheet id into the three Google Sheets nodes (Add Agreement to Tracker, Read Agreements, Read Agreements for Review). Set the office email in the webhook payload, or change the default in Normalize New Agreement, so rejections, alerts and the weekly review reach the right inbox. Point the webhook URL (path hvac-agreement-intake-0930) at your CRM, form tool or intake process. Confirm the daily 07:00 and Monday 09:00 schedules match your office timezone, then activate the workflow. To change the reminder window, adjust the 3-day threshold in Flag Due Agreements and the 7-day and 60-day windows in Collate Agreement Stats. Quick Answers What happens if an agreement arrives incomplete? Validate Agreement checks customer name, customer email, next due date and office email. If any are missing, nothing is added to the tracker and the office gets an email listing what was missing plus the posted values. What does gpt-6-luna actually do? It writes the customer welcome on intake, the service reminder for each agreement due within 3 days or overdue, and the Monday review of the agreement book for the office. Who gets notified when a service is overdue? The customer gets a reminder email first, then the office gets one escalation email listing each overdue customer with due date, days overdue and phone number. How do I know the state of the agreement book? Every Monday at 09:00 it reads the Agreements tab and emails the office a review covering active agreements, services due this week, overdue agreements by name and renewals in the next 60 days. Additional info Built with n8n. Need an assessment on your business? Feel free to reach out at https://khmuhtadin.com/consultation/. An n8n automation workflow template by Khairul Muhtadin.

By Khairul Muhtadin

Farm box members change their plans, and someone has to catch every skip, pause and pickup swap before the next delivery. This n8n workflow takes each change request from a form, has gpt-6-luna classify it and draft the confirmation, logs it to Google Sheets and emails the member. It also sends the weekly harvest newsletter to active members every Thursday, and every Monday it emails friendly balance reminders plus a summary to the farm inbox. Last updated: October 2026. Quick Overview This workflow runs the admin side of a community supported agriculture (CSA) farm box share. A member submits the Box Change Request Form, the request is normalized and validated, gpt-6-luna classifies it (skip, pause, box size change, pickup change or other) and drafts a short confirmation that is logged to the Requests tab and emailed to the member, while an incomplete request goes to the farm inbox instead of being saved. Every Thursday at 07:00 a newsletter is written from the member roster and this week's harvest list and emailed to every active member with each send logged, and every Monday at 08:00 the balance sweep chases members with an amount due and reports the totals to the farm. How it works A member submits the "Farm box change request" form with member name, member email, the change they want and an effective date. Normalize Request maps those fields, stamps received_at and generates a request_id like REQ-20261005-123, then Validate Request checks member name, member email and request text are present. If anything is missing, the request is not saved and Email Farm About Invalid Request emails the farm inbox listing the missing fields together with the values that were posted. Valid requests go to Classify and Draft Reply, where gpt-6-luna sorts the request into skip_week, pause_membership, box_size_change, pickup_change or other, sets decision to confirmed or needs_review, and writes a subject and a body under 120 words. Parse Reply reads that JSON back onto the request. Log Request to Register appends the request, the classification and the drafted reply to the Requests tab, then Email Confirmation to Member sends the reply to the member. Every Thursday at 07:00 (Weekly Harvest Newsletter) the workflow reads the Members and Harvest tabs, collapses them into a member count and this week's harvest list, and Compose Harvest Newsletter has gpt-6-luna write a newsletter under 180 words with a storage tip per item. Prepare Newsletter Email fans it out to every member whose share_status is not paused, Email Members the Newsletter sends it, and Build Newsletter Log plus Log Newsletter Sent record sent_at, week_of, recipient and subject in the NewsletterLog tab. Every Monday at 08:00 (Weekly Balance Sweep) Read Member Balances reads the Members tab, Find Outstanding Balances keeps everyone with a balance_due above 0 and builds the reminder, and Email Balance Reminders sends it to each member. The same sweep emails the farm one summary listing the members with an outstanding balance. When nobody owes anything, no email is sent. Setup Create a Google Sheets spreadsheet with four tabs: Requests, Members, Harvest and NewsletterLog, with columns matching the fields written by the Google Sheets nodes. Add credentials for Google Sheets OAuth2, Gmail OAuth2 and an [OI] chat model. Fill the Members tab with your roster (member_name, member_email, share_status, balance_due) and the Harvest tab with this week's list (week_of, item, quantity). Set the farm inbox in the Normalize Request node (farm_email) so invalid requests reach the right person. Publish the Box Change Request Form and share the form link with members. Confirm the Thursday 07:00 and Monday 08:00 schedules match your timezone, then activate the workflow. Quick Answers What happens when a member asks to skip a week? The submission is normalized and validated, gpt-6-luna classifies it as skip_week and drafts a confirmation that restates the change and the effective date, the request is appended to the Requests tab, and the member gets the confirmation email in the same run. What does gpt-6-luna do in this workflow? It does two jobs. On each box change request it classifies the request type, decides between confirmed and needs_review, and drafts the reply. Every Thursday it writes the harvest newsletter from this week's harvest list. Where does the newsletter content come from? From the Harvest tab. The workflow collapses this week's rows into a single list, gpt-6-luna writes the newsletter from that list only, and it goes to every member whose share_status is not paused. Who gets the balance reminders? Every member whose balance_due is above 0. Each gets a friendly reminder email, and the farm gets one summary listing the members with an outstanding balance. Additional info Built with n8n. Need an assessment on your business? Feel free to reach out at https://khmuhtadin.com/consultation/. An n8n automation workflow template by Khairul Muhtadin.

By Khairul Muhtadin

Food cost creep is quiet. A supplier puts up the price of chicken, nobody updates the recipe card, and the damage only shows up at month end. This n8n workflow keeps every recipe cost current, recomputes what each menu item costs to make, and emails you the moment an item passes its target food cost. Last updated: October 2026. Quick Overview This workflow takes supplier price updates through a webhook, logs them to the Prices tab of a Google Sheets tracker, and recomputes every recipe cost from the latest ingredient prices. A daily sweep at 06:00 flags any menu item whose food cost has passed its target, logs it to the CostAlerts tab and emails an alert listing each flagged recipe with its portion cost and percentage. Every Monday at 07:00 gpt-6-luna reads the week's cost stats and writes one plain-text digest with the worst items and the menu prices that would bring them back in line. How it works Receives a price change on the "When Price Update Received" n8n webhook (POST path menu-cost-intake-0926) and normalizes ingredient, unit_price, unit, supplier, submitted_by and owner_email, stamping an update_id and a received timestamp. Validates that ingredient and unit_price are present. If either is missing, the price is not logged and a rejection email lists the required fields and the payload that was received. Appends valid updates to the Prices tab (ingredient, unit_price, unit, price_date, supplier, submitted_by, update_id) and sends a confirmation email naming the ingredient, the new price and the reference. Runs the Daily Margin Sweep at 06:00, reading the Prices, Recipes and Menu tabs. Compute Recipe Costs takes the newest price per ingredient by price_date, multiplies each recipe line's qty_per_portion by that price, and works out cost_per_portion and cost_pct against the item's sale_price and target_cost_pct. Ingredients with no price are listed in missing_ingredients. Any item whose cost_pct is above target_cost_pct is flagged, appended to the CostAlerts tab with alert_date, recipe, cost_per_portion, cost_pct, target_cost_pct and status flagged, and gathered into one email headed "Menu margin alert: N item(s) over target" that shows portion cost, food cost against target and any missing prices. Runs the Weekly Menu Digest every Monday at 07:00, re-reading the three tabs and computing menu_items, flagged_count, flagged_recipes, the three worst items, avg_cost_pct and the best-margin item. Passes those stats as JSON to the AI Write Digest agent, which writes a plain-text body under 180 words naming the biggest problems first, suggesting a menu price close to portion cost divided by target cost, and saying what to check with suppliers. Emails that digest as "Weekly menu cost digest". If nothing is flagged, it says the menu is in good shape and names the best-margin item. Setup Create a Google Sheets file with four tabs: Prices, Recipes, Menu and CostAlerts. Add the columns the nodes use: ingredient, unit_price, unit, price_date, supplier, submitted_by, update_id in Prices; recipe, ingredient, qty_per_portion in Recipes; recipe, sale_price, target_cost_pct in Menu; alert_date, recipe, cost_per_portion, cost_pct, target_cost_pct, status in CostAlerts. Replace the sample rows with your own ingredients, recipes and menu items, and point the Google Sheets nodes at your own spreadsheet. Add credentials for Google Sheets OAuth2, Gmail OAuth2 and an [OI] chat model. Set the recipients: the webhook accepts owner_email in the payload, and the margin alert and weekly digest nodes use a placeholder address. POST price updates to /webhook/menu-cost-intake-0926 sending ingredient and unit_price, plus optional unit, supplier, submitted_by and owner_email. Confirm the 06:00 sweep and the Monday 07:00 digest match your timezone, then activate the workflow. Quick Answers What counts as margin erosion here? Each menu item carries a target_cost_pct in the Menu tab. The sweep divides the recomputed portion cost by the sale price, and when that percentage is above the target the item is flagged, logged to CostAlerts and included in the alert email. What happens when an ingredient has no price? The recipe line is left out of the cost total and the ingredient is named in missing_ingredients, which appears in the alert email and the CostAlerts record so you know the number is incomplete. What does gpt-6-luna actually do? Once a week it reads the computed stats and writes the plain-text digest body under 180 words, with a suggested menu price for each problem item and a note on what to check with suppliers. Additional info Built with n8n. Need an assessment on your business? Feel free to reach out at https://khmuhtadin.com/consultation/. An n8n automation workflow template by Khairul Muhtadin.

By Khairul Muhtadin

Boarding bookings only get approved when the vaccination records actually hold up. This n8n workflow takes boarding requests from a form, checks rabies, DHPP and bordetella expiry dates against the stay, has gpt-6-luna write the owner reply for whatever the check decided, logs every booking to Google Sheets, and alerts the kennel inbox when a pet is not cleared. A daily watch emails owners whose vaccine is about to run out, and a Monday digest sums up the week. Last updated: October 2026. Quick Overview This workflow collects pet boarding requests through an n8n Form and compares each pet's rabies, DHPP and bordetella expiry dates against the booked stay. Every booking comes out as approved, conditional or blocked, and gpt-6-luna writes the owner reply for that outcome. All bookings are appended to the "Bookings" tab in Google Sheets, non-approved bookings also alert the kennel inbox, a daily 07:00 watch emails owners whose vaccine expires within 30 days, and a Monday 09:00 digest summarizes the week for the kennel. How it works Receives a request through the "Boarding Request Form" with owner name, owner email, pet name, species, check in and check out dates, the rabies, DHPP and bordetella expiry dates, and notes. Normalizes the entry and adds a booking ID in the BKG-YYYYMMDD-### format, a received_at timestamp and the kennel inbox address. Validates that owner name, owner email, pet name, check in date and check out date are present. If anything is missing the booking is not saved and the kennel gets an email listing what was missing. Runs the deterministic check in Check Vaccine Validity: each expiry date is compared against the check out date. A missing or expired record gives blocked (noncompliant), an expiry within 14 days of the stay gives conditional (expiring_soon), and anything further out gives approved (compliant). The node also writes the issues text and the smallest number of days left on any record. Sends the decision to gpt-6-luna, which writes the owner email: a confirmation for approved, a renewal nudge for conditional, or a request for an updated record for blocked. Subject max 10 words, body under 140 words, plain text. Appends the full record to the "Bookings" tab in Google Sheets, including the decision, compliance, issues, the drafted subject and body, and an empty last_watch_at column. Emails the owner the drafted reply, then for any decision that is not approved alerts the kennel inbox with the pet name, owner, stay dates and the vaccine issues so staff can chase the record. Runs daily at 07:00, reads the Bookings tab, keeps the newest row per owner and pet, and emails a heads up to every owner whose pet has a vaccine expiring within 30 days. Runs Monday at 09:00, counts approved, conditional and blocked bookings for the week plus pets with a vaccine expiring in 30 days, and has gpt-6-luna draft the digest email (subject max 12 words, body under 160 words) to the kennel. Setup Create a Google Sheets file with a tab named "Bookings" and columns booking_id, received_at, owner_name, owner_email, pet_name, species, check_in_date, check_out_date, rabies_expiry, dhpp_expiry, bordetella_expiry, compliance, decision, issues, notes, kennel_email, email_subject, email_body and last_watch_at. Add credentials for Google Sheets OAuth2, Gmail OAuth2 and an [OI] chat model, then select them in the nodes. Point the three Google Sheets nodes (Log Booking to Register, Read Booking Register, Read Register for Digest) at your spreadsheet. Set the kennel inbox in the Normalize Booking node (kennel_email) so intake problems, non-approved alerts and the weekly digest reach the right mailbox. Publish the boarding request form and share the link with owners. Confirm the 07:00 daily watch and the Monday 09:00 digest match your timezone, then activate the workflow. Quick Answers How does a booking get approved, conditional or blocked? Check Vaccine Validity compares the rabies, DHPP and bordetella expiry dates against the check out date. A missing or expired record gives blocked, an expiry within 14 days of the stay gives conditional, and anything further out gives approved. What does gpt-6-luna actually do? Two jobs. On every request it writes the owner reply for the decision that the deterministic check produced. On Monday it drafts the weekly kennel digest from the counts in the register. What happens when a booking is not approved? The owner still gets the drafted reply asking for an updated record, and the kennel inbox gets a "Booking needs action" alert with the pet name, the decision and the vaccine issues. When do the reminders go out? Daily at 07:00 the watch reads the Bookings tab and emails owners whose pet has a vaccine expiring within 30 days, including records that already expired. Monday at 09:00 the digest goes to the kennel inbox. Additional info Built with n8n. Need an assessment on your business? Feel free to reach out at https://khmuhtadin.com/consultation/. An n8n automation workflow template by Khairul Muhtadin.

By Khairul Muhtadin

Patrol reports that reach the right person before the shift ends. This workflow takes guard reports from an n8n Form, has gpt-6-luna grade the severity and write a summary a supervisor can read in ten seconds, logs every report to Google Sheets, and emails the ops supervisor and the site client the moment a report is urgent. Last updated: October 2026. Quick Overview This workflow collects security patrol and incident reports through an n8n Form, uses gpt-6-luna to classify each report as urgent, normal or informational and write a supervisor-ready summary, logs every report to Google Sheets, and escalates urgent incidents by email to the ops supervisor and the site client. A daily 06:00 digest covers the last 24 hours, and a monthly AI review summarizes the last 30 days. How it works Receives a patrol log or incident report through an n8n Form and normalizes the officer, site, shift, report type and event time fields while generating a unique report ID (SEC-yyyyMMdd-###) and a submission timestamp. Validates that officer name, officer email, site or client, and the description are present. If anything is missing the report is not saved and the officer gets an email listing what was missing and the values that were posted. Sends the report to gpt-6-luna, which classifies severity as urgent (immediate threat to people or property), normal (needs attention but not an emergency) or informational, and writes a plain-text summary under 60 words with one suggested action for urgent items. Merges the AI severity, summary and suggested action back onto the report, flags it as urgent or not, and appends the full record including the supervisor and client addresses to the "Security Log" tab in Google Sheets. For urgent reports, emails the ops supervisor an URGENT alert with the summary and suggested action, then emails the site client an urgent incident notice confirming the supervisor is coordinating the response. Runs daily at 06:00, reads the log, keeps the last 24 hours of reports and emails a daily activity report to the ops manager, one line per report, with "(INCLUDES URGENT ITEM)" in the subject when the window holds an urgent report. Runs on the 1st of the month at 08:00, collates the last 30 days into totals, incident and urgent counts and reports by site, and has gpt-6-luna draft the monthly review email (subject plus body) for the ops manager. Setup Create a Google Sheets file with a tab named "Security Log" and make sure the columns match the fields written by the Google Sheets nodes, then paste the spreadsheet id into those nodes. Add credentials for Google Sheets OAuth2, Gmail OAuth2 and an [OI] chat model, and select the correct accounts in the respective nodes. Set the supervisor and client email addresses in the Normalize Report node, and review the fallback addresses used by the alert nodes. Publish the patrol report form and share its URL with the guards. Confirm the daily (06:00) and monthly (1st, 08:00) schedule times match your timezone, then activate the workflow. Quick Answers How does a guard report get escalated? The guard submits the form, the report is normalized and validated, gpt-6-luna grades the severity, and the record is appended to the Security Log. When the severity is urgent the ops supervisor gets an email alert and the site client gets an urgent incident notice in the same run. What does gpt-6-luna actually do? Two things. On intake it classifies the report as urgent, normal or informational, writes a summary a supervisor can read in ten seconds and adds one suggested action for urgent items. On the 1st of the month it drafts the monthly site review email from the collated totals. What happens if a guard leaves something out? The report is not saved. The officer gets an email listing the required fields (officer name, officer email, site or client, and what happened) plus the values that were posted, and can fix the form and resubmit. How do I know what happened overnight? A daily activity report runs at 06:00 with the last 24 hours of reports, one line per report, and the subject is flagged when the window includes an urgent item. Additional info Built with n8n. Need an assessment on your business? Feel free to reach out at https://khmuhtadin.com/consultation/. An n8n automation workflow template by Khairul Muhtadin.

By Mario Gorgious

Quick overview This workflow runs daily at 07:00, pulls Arabic headlines from an RSS feed, uses Google Gemini to rank and rewrite the top five stories into a short Modern Standard Arabic briefing, then sends the briefing as text and ElevenLabs-generated audio to Telegram while logging delivery details to Google Sheets. How it works Runs every morning at 07:00 on a schedule. Reads up to 20 items from the configured Arabic RSS news feed. Sends the feed items to Google Gemini to select the five most important stories and rewrite them into a JSON briefing in Modern Standard Arabic. Parses Gemini’s JSON response into a formatted Telegram message and extracts key fields like date, top headline, and top summary. Sends the formatted text briefing to a Telegram chat using Markdown formatting. Converts the briefing text to Arabic speech with the ElevenLabs Text-to-Speech API and sends the resulting audio file to the same Telegram chat. Appends a delivery log row to a Google Sheets document with the date, top headline, top summary, audio sent status, and overall status. Setup Add Google Gemini credentials (API key) for the Google Gemini node. Create a Telegram bot and add your Telegram bot token as credentials, then set the target Telegram chat ID in both Telegram send steps. Add an ElevenLabs API key using an HTTP header authentication credential and update the ElevenLabs voice ID in the Text-to-Speech request URL if needed. Connect Google Sheets credentials and replace YOUR_GOOGLE_SHEET_ID with your document ID, ensuring the Briefings sheet exists with matching columns (Date, Headline, Summary, Audio Sent, Status). Review and update the RSS feed URL if you want to source headlines from a different publisher or feed. An n8n automation workflow template by Mario Gorgious.

By Incrementors

Quick overview This weekly workflow audits how often your brand is named versus cited by link in ChatGPT (with web search) and Perplexity, then identifies which external pages win those citations, classifies them with OpenAI, and logs a trend report plus a content-gap backlog in Google Sheets. How it works Runs weekly on a schedule and reads one brand’s settings from Google Sheets (domain, sitemap path, competitors, sampling and notification settings). Fetches the site sitemap, follows a sitemap index one level down when needed, and scores URLs to select the most commercial pages to sample. Uses OpenAI to turn the selected page themes into buyer-style questions without naming the brand, then expands each question into multiple repeat runs. Sends every repeated question to Perplexity and to the OpenAI Responses API with web search, then normalizes both outputs into a single record with answer text and cited URLs. Calculates mention rate, citation rate, and stability per question/engine, and ranks the external cited URLs that are not on your own domain. Fetches the top cited external pages and uses OpenAI to classify each page’s format, topic, and why it earns citations. Builds a week-over-week HTML report, logs the run to Google Sheets History, emails the report via Gmail, optionally alerts Slack on large drops, and writes each citation gap as its own row in a Google Sheets Content Gaps backlog. Setup Create a Google Sheets file with tabs named Settings, History, and Content Gaps, and add the columns referenced in the Google Sheets nodes (including Settings fields like Domain, Sitemap Path, Competitors, Pages To Sample, Repeats Per Question, Report Email, and Slack Channel). Add Google Sheets credentials and replace YOUR_GOOGLE_SHEET_ID in all Google Sheets nodes with your spreadsheet ID. Add OpenAI API credentials (used for question generation, page classification, and the ChatGPT web-search calls). Add a Perplexity API credential for the Perplexity chat completions request. Add Gmail credentials for sending the report email, and set the Slack channel name (and Slack credentials) for the optional alert message. An n8n automation workflow template by Incrementors.

By Pankaj Patidar

Quick overview This workflow validates DigiParser purchase order extraction events, flags problematic orders for review, and exports two CSV files: one with staging-ready line items and another with orders that need manual follow-up. How it works Starts when you manually run the workflow to simulate processing DigiParser document.exported events. Loads a batch of sample DigiParser payloads that contain purchase order header fields and line items. Validates required PO fields, currency and date formats, line-item quantities and arithmetic, order-total reconciliation, and detects duplicate customer+PO pairs within the batch. Splits the results into valid orders that are ready for staging and invalid orders that need review, including the reasons for failure. Converts valid orders into a line-level CSV file for import into downstream order-entry or ERP staging. Converts invalid orders into a separate CSV file so an operator can correct data issues and reprocess. Setup Run the included synthetic demo first; no account connection is required. For real data, replace Load synthetic DigiParser events with a trusted source and map each item to event: document.exported, data.id and data.extracted_data. Match Customer Name, PO Number, PO Date, Currency, Order Total and Line Items to your parser fields. For API output, map documentId to data.id and combine fields and tables into data.extracted_data. Store credentials in n8n. For webhook input, verify the DigiParser webhook signature before passing data into this workflow. The supplied JSON contains no public webhook endpoint. Adjust the validation and mapping logic if your purchase orders include taxes, freight, discounts, different money precision, or different line-item field names. Requirements An n8n instance with JavaScript Code and Convert to File nodes. A DigiParser account and trusted extracted data are required only when replacing the synthetic demo source. Additional info Contributed by DigiParser with AI assistance. Tested in n8n 2.41.7 using three synthetic events: one valid order produced two staging CSV rows, and two cases entered the review CSV. Live DigiParser authentication, extraction and ERP writes were not tested. Duplicate checks cover one batch only. Setup: https://www.digiparser.com/solutions/purchase-order-parser. Webhook documentation: https://www.digiparser.com/docs/api/webhooks. An n8n automation workflow template by Pankaj Patidar.

By Rahul Joshi

Quick overview This workflow captures warranty registrations from an n8n Form or a webhook, saves each product to a Google Sheets warranty registry, and upserts the buyer into GoHighLevel with tags, notes, and a welcome SMS/email certificate; it also runs daily to send OpenAI-written service and warranty reminders via GoHighLevel. How it works Receives a warranty registration either from the hosted n8n Form or from a DMS/POS webhook. Normalizes the submitted data, calculates warranty end and next service dates, and filters out duplicate serial/VIN numbers by checking the existing Google Sheets registry. Upserts the customer as a contact in GoHighLevel and builds a warranty registry row plus a welcome SMS and an HTML warranty certificate email. Appends the registration to the Google Sheets Warranty Registry, then tags and notes the GoHighLevel contact and sends the welcome message and certificate email via GoHighLevel Conversations. Runs every day at 9:30 AM, loads the Google Sheets warranty registry, and determines which service-due, overdue, or warranty-expiry reminder stage applies for each active registration. Uses OpenAI (gpt-4o-mini) to draft reminder SMS and email copy, then sends them through GoHighLevel, tags and notes the contact, and updates the reminder stage fields in Google Sheets. When a new paid service or warranty renewal cycle starts, creates a GoHighLevel opportunity and saves the opportunity ID back to the matching registry row in Google Sheets. Setup Create a GoHighLevel Private Integration token (scoped for contacts, conversations/messages, notes/tags, and opportunities) and add it as HTTP Header Auth for all GoHighLevel HTTP Request nodes. Connect Google Sheets OAuth credentials and create a spreadsheet with a sheet/tab named "Warranty Registry" (or update the registry sheet name in both config nodes). Add an OpenAI API credential for the OpenAI node (gpt-4o-mini). Update the values in “Set Registration Config” and “Set Reminder Config” (location ID, pipeline/stage IDs, sheet ID, booking/review links, and message channel). If using the DMS/POS intake, copy the webhook URL from “Receive Sale from DMS / POS” and configure your source system to POST registrations to it, and optionally adjust the service/warranty offset settings in the config nodes. An n8n automation workflow template by Rahul Joshi.

By iamvaar

Quick overview Youtube Video: https://youtu.be/Fh0QR48f9is This workflow runs every weekday morning, reads active construction projects and related data from Google Sheets, pulls a 7-day forecast from Open-Meteo, computes delivery and cost risk scores, and uses Google Gemini to generate a structured escalation decision that is logged and emailed via Gmail. How it works Runs on a cron schedule at 7:00 AM Monday–Friday. Reads all projects marked Active from a Google Sheets “Projects” tab and fetches a 7-day weather forecast for each project from the Open-Meteo API using its latitude and longitude. Loads supporting project data (budget/accounting, procurement, labor, site reports, and disputes) from other tabs in the same Google Sheets document. Computes per-project schedule, procurement, labor, disputes, weather, reporting integrity, and budget risk metrics, then derives a rule-based decision (CONTINUE, INTERVENE, or STOP_REVIEW) plus the most impactful mitigation lever and deadline. Sends the computed metrics to Google Gemini to produce a validated decision JSON (headline, reasons, critical action, and confidence) while enforcing guardrails on any decision override. Appends the final decision record to a Google Sheets “Decision_Log” tab. Emails the project manager via Gmail only when the decision is INTERVENE or STOP_REVIEW. Setup Create and connect a Google Sheets Service Account credential with access to the spreadsheet, and update the spreadsheet ID and tab names (Projects, Budget_Accounting, Procurement, Labor, Site_Reports, Disputes, Decision_Log) to match your file. Ensure your sheets contain the expected columns (for example project_id, status, latitude/longitude, planned and actual progress, procurement promised dates and critical_path, labor headcounts, dispute status/severity, and budget totals/spend/commitments). Add a Google Gemini (PaLM) API credential for the Gemini chat model used in the decision step. Add a Gmail OAuth2 credential and set the recipient(s) and email content fields as needed for your PM notifications. An n8n automation workflow template by iamvaar.

By Rahul Joshi

Quick overview This workflow collects client document requests for a CA firm, creates a Google Drive folder and Google Sheets tracker entry, and sends upload links via WhatsApp Cloud API and Gmail, then chases pending items with OpenAI-written reminders, logs activity, and serves a password-protected status board. How it works Accepts a new document request either from a staff form submission or a POST webhook and normalizes the client details, due date, and required-document list. Creates a dedicated client folder in Google Drive and appends a new tracking row in Google Sheets with the upload link and reminder schedule. Sends the initial document request to the client via a WhatsApp Cloud API template message and a Gmail email containing the checklist and personal upload link, then logs the request in the Google Sheets activity log. Receives client uploads through an n8n Form, looks up the matching request in Google Sheets, saves each uploaded file into the client’s Google Drive folder, and updates the received/pending checklist and status in the tracker. Sends the client an upload receipt by WhatsApp and Gmail showing what is still missing, and emails the assigned CA when all required documents are received. Runs every day at 10:00 (Mon–Sat) to pull open requests from Google Sheets, email a team digest, generate reminder email copy with OpenAI, send WhatsApp and Gmail reminders, update reminder counters/dates, and escalate to the assigned CA by email when required. Serves a live HTML status board via a webhook that reads request data from Google Sheets and returns 401 unless the correct board key is provided. Setup Create a Google Sheet with two tabs named “Document Requests” and “Activity Log”, and update the sheet ID and tab names in the three configuration steps used for intake, uploads, and the daily chaser. Create a Google Drive root folder for client documents, connect Google Drive credentials, and set the root folder ID in the configuration steps. Connect Gmail credentials for sending client emails, CA escalations, and the daily team digest, and set the team email address. Add an OpenAI credential (model set to gpt-4o-mini) for drafting reminder emails. Configure WhatsApp Cloud API header authentication, set your WhatsApp phone number ID and API version, and create/approve the message templates named document_request, document_reminder, and documents_received. Set your public n8n base URL and change the board_key value, then use the generated upload link and status board URL (with ?key=…) in your internal process before activating the workflow. An n8n automation workflow template by Rahul Joshi.

By iamvaar

Quick overview Youtube Video: https://youtu.be/XHT46n4b1lg This workflow receives a shift-close webhook and reconciles fuel tank wet-stock in Google Sheets, optionally using Google Gemini to explain anomalies, then logs results back to Google Sheets and posts investigation alerts to Slack. How it works Receives a POST webhook at shift close with a station_id and shift_id. Looks up the station’s active tanks and the shift’s tank readings, nozzle totalizer sales, deliveries, and prior audit history from Google Sheets. Calculates per-tank expected vs actual closing volume, variance, tolerance, direction (loss/surplus), baseline z-score, drift patterns, and a risk score, and flags data gaps or meter/delivery issues. When the variance warrants review, sends the computed context to Google Gemini to produce a non-accusatory JSON investigation summary with likely causes and recommended actions. Writes the full reconciliation record (including AI verdict/summary when present) to an Audit_Log sheet in Google Sheets. Formats and posts Slack messages for tanks that need notification (alerts, critical variances, delivery shortfalls, or data gaps) and returns a JSON summary response to the webhook caller. Setup Create a Google Sheets Service Account credential in n8n and grant it access to the spreadsheet used for Tanks, Tank_Readings, Nozzle_Sales, Deliveries, and Audit_Log. Update the Google Sheets document ID and ensure the sheet/tab names and required columns match what the workflow reads and appends. Add a Google Gemini (Google PaLM) API credential for the LangChain Gemini chat model used for anomaly explanations. Add Slack credentials, choose the target channel, and adjust the channel ID/message destination as needed. Copy the webhook URL for the Shift Close endpoint and configure your POS/shift-close system to POST station_id and shift_id (and optionally shift_end) to it. An n8n automation workflow template by iamvaar.