Browse case studies by tool and use case: automations, AI agents, dashboards, and custom platforms.
The complete text of the site in 4 parts, shortest case studies first. Parts:
This Make scenario is implemented so that whenever an order is fulfilled in Shopify, the order details are added to ClickUp.
Section: Make Automations
This Make scenario is implemented so that whenever an order is fulfilled in Shopify, the order details are added to ClickUp.
Utilized Google Apps Script to automate the generation and saving of chart images to Google Drive, streamlining the reporting process.
Section: Google Apps Script
Utilized Google Apps Script to automate the generation and saving of chart images to Google Drive, streamlining the reporting process.
This Make scenario is implemented whenever a task gets completed in ClickUp.
Section: Make Automations
Created Google Apps Script to automatically format data into PDF invoices and send them via email, saving manual effort and enhancing operational efficiency.
Section: Google Apps Script
Created Google Apps Script to automatically format data into PDF invoices and send them via email, saving manual effort and enhancing operational efficiency.
This scenario is implemented so that whenever the status of an opportunity is changed in Go High Level, the associated email is added to Beehiv as a subscriber.
Section: Make Automations
This scenario is implemented so that whenever the status of an opportunity is changed in Go High Level, the associated email is added to Beehiv as a subscriber.
The automation is designed to send daily updates to Slack. The data in Google Sheets is updated daily, and the KPI data is sent to Slack every day using a Make scenario.
Section: Make Automations
The automation is designed to send daily updates to Slack. The data in Google Sheets is updated daily, and the KPI data is sent to Slack every day using a Make scenario.
RB2B is a platform that collects website visitor profiles.
Section: Make Automations
A Zap is being built to connect GoHighLevel with Beehiv.
Section: Zapier Automations
This scenario is built so that whenever there is a refunded order in Shopify, the order details are added to ClickUp as tasks.
Section: Make Automations
Designed a dynamic growth model in Google Sheets, complete with Key Performance Indicators (KPIs) to enhance visibility and guide decision-making.
Section: Google Apps Script
Designed a dynamic growth model in Google Sheets, complete with Key Performance Indicators (KPIs) to enhance visibility and guide decision-making.
Image: The growth funnel model: awareness, engagement, and retention KPIs tracked month over month.
Created a script to automate data entry in an inventory sheet from CSV files.
Section: Google Apps Script
Created a script to automate data entry in an inventory sheet from CSV files. The script also includes a data cleaning function to ensure accuracy and integrity of the imported data.
Image: Multi-warehouse inventory data with flagged data-quality issues the cleaning step catches: mismatched locations and unidentified SKUs.
Implemented a robust data pipeline using SyncWith and SQL to extract and sync data from BigQuery to Google Sheets for real-time analytics and reporting.
Section: Google Apps Script
Implemented a robust data pipeline using SyncWith and SQL to extract and sync data from BigQuery to Google Sheets for real-time analytics and reporting.
Image: A scheduled BigQuery SQL query joining employer and sign-up data by month for the KPI sheet.
Created an interactive dashboard within Google Sheets for effective data visualization and tracking, serving as a quick reference tool for stakeholders.
Section: Google Apps Script
Created an interactive dashboard within Google Sheets for effective data visualization and tracking, serving as a quick reference tool for stakeholders.
Image: A CRM dashboard inside Google Sheets tracking hiring totals, job closures, and feedback scores.
This automation is implemented to create a Pinterest pin whenever RSS data is received.
Section: Zapier Automations
Worked on developing a Project Tracker in Google Sheets to allocate tasks, track project milestones, and monitor team performance, complete with real-time updates and visual dashboards for easy interpretation.
Section: Google Apps Script
Worked on developing a Project Tracker in Google Sheets to allocate tasks, track project milestones, and monitor team performance, complete with real-time updates and visual dashboards for easy interpretation.
Image: A Gantt-style project schedule generated directly in Google Sheets.
This Zap connects Skool, Slack, LeadConnector and Close, starting when a member answers the Skool membership questions.
Section: Zapier Automations
This Zap connects Skool, Slack, LeadConnector and Close, starting when a member answers the Skool membership questions. It then sends a message to a Slack channel, adds or updates the contact in LeadConnector, and looks up the matching contact and lead in Close.
Image: The five-step Zap: a Skool trigger, a Slack channel message, a LeadConnector contact update and two Close lookups.
This Zap streamlines the process of appointment cancellations by integrating ClickUp with Calendly.
Section: Zapier Automations
This Zap streamlines the process of appointment cancellations by integrating ClickUp with Calendly. When a cancellation is initiated from within ClickUp, by pressing the cancel button on a specific task, the relevant appointment is automatically cancelled in Calendly. This automation ensures that appointment slots are efficiently managed and updated in real time, reducing manual oversight and the potential for scheduling conflicts.
Developed an app script to automatically update columns in an inventory sheet based on values in another sheet, enabling seamless data synchronization within Google Sheets.
Section: Google Apps Script
Developed an app script to automatically update columns in an inventory sheet based on values in another sheet, enabling seamless data synchronization within Google Sheets.
Image: Syncing active/inactive status between a main sheet and a linked inventory spreadsheet.
Image: A custom menu for updating inventory values and normalizing leading zeros on demand.
This Zap automates the process of task creation in ClickUp based on incoming emails from a specified sender in Gmail.
Section: Zapier Automations
This Zap automates the process of task creation in ClickUp based on incoming emails from a specified sender in Gmail. Whenever an email is received from the designated sender, the Zap automatically creates a new task in ClickUp. Additionally, any attachments included in the email are uploaded and attached to the newly created ClickUp task, ensuring all pertinent information and documents are consolidated and accessible directly within the task.
A Looker Studio dashboard tracking Meta ad spend, clicks, impressions and campaign-level ROAS in one live view.
Section: Looker Studio
Built in Looker Studio to track Meta ad spend, clicks and campaign performance in one place, replacing manual exports from Meta Ads Manager.
Image: Meta Ads dashboard overview: clicks, link clicks, impressions, ROAS and spend for a single brand’s campaigns.
Image: Campaign-level breakdown: ROAS, clicks, spend, impressions and CPM for every ad and campaign, filterable by name.
A Looker Studio dashboard tracking Google Ads cost, revenue, orders, profit and ROAS for the same multi-channel account.
Section: Looker Studio
The same multi-channel Looker Studio report includes a dedicated Google Ads page, tracking cost, revenue, orders, profit and ROAS alongside clicks and conversion rate.
Image: Google Ads dashboard for the same account: cost, revenue, orders, profit and ROAS alongside clicks and conversion rate.
The dashboard runs on Looker Studio so paid media and finance read from the same live numbers instead of a separate export from Google Ads.
The script reads from a spreadsheet cell that lists email addresses authorized for file access.
Section: Google Apps Script
A Google Sheets weekly tracker that brings Google Analytics traffic and Klaviyo email and SMS performance into one view.
Section: Dashboards & Reporting
A weekly tracker pulls Google Analytics traffic and Klaviyo email and SMS performance into one Google Sheet, so acquisition and retention numbers sit side by side instead of living in separate tools.
Image: Weekly dashboard tracking Google Analytics traffic by source alongside Klaviyo email and SMS sales and subscriber counts.
Built in Google Sheets so marketing can compare traffic sources, email and SMS sales and subscriber growth week over week without logging into each platform.
This automation is implemented to create a Pinterest pin whenever RSS data is received.
Section: Make Automations
Leveraged expertise in API integration and Google Sheets to create an automated system that transfers data from Shopify to Google Sheets using the ‘Sync With’ extension.
Section: Google Apps Script
Leveraged expertise in API integration and Google Sheets to create an automated system that transfers data from Shopify to Google Sheets using the ‘Sync With’ extension. Utilized Google Apps Script and various functions to allocate customer-specific tasks to agents, and integrated this data into Aircall for seamless customer outreach. The system is set to update daily.
Image: The task-distribution function that splits unattended calls evenly across the agent roster.
A Looker Studio dashboard rolling up Facebook ad spend, revenue, ROAS and profit margin across a 9-month window.
Section: Looker Studio
Part of a larger multi-channel Looker Studio report, this page rolls up spend, revenue and profit for Facebook campaigns specifically, alongside a daily revenue-vs-spend trend.
Image: Facebook performance overview across a 9-month window: spend, revenue, ROAS and profit margin alongside a daily revenue-vs-spend trend.
The dashboard runs on Looker Studio so paid media and finance read from the same live numbers instead of a separate export from Meta.
This Zap facilitates seamless integration between Google Calendar and ClickUp, enhancing task management and operational efficiency.
Section: Zapier Automations
This Zap facilitates seamless integration between Google Calendar and ClickUp, enhancing task management and operational efficiency. Whenever a new event is created in Google Calendar, the Zap automatically generates a corresponding task in ClickUp. It transfers relevant details from the calendar event, such as the date, time, and event description, to the ClickUp task. Furthermore, the Zap is configured to assign these tasks to specific individuals, optimizing task allocation and ensuring the right team members are engaged with relevant events and responsibilities.
The script initiates by creating a structured main folder in Google Drive.
Section: Google Apps Script
Image: The batch-creation script that generates each client’s folder structure, contract, and accounting files from templates.
Automatically collect detailed info from YouTube videos of popular creators for content analysis.
Section: AI Agents
Objective:
Automatically collect detailed info from YouTube videos of popular creators for content analysis.
Implementation:
The workflow pulls the url from your database, scrapes their details using a scraping tool, waits for results, and then saves everything back to the database.
Outcome:
To automatically download a TikTok video and store it in Google Drive with a public share link.
Section: AI Agents
Objective:
To automatically download a TikTok video and store it in Google Drive with a public share link.
Implementation:
This workflow fetches a TikTok video, extracts its direct video link, downloads it without watermark, and saves the file to your Google Drive, for content reposting.
Outcome:
This Zap runs when a new booking is made in TidyCal, adds or updates the contact in LeadConnector, and records the booking in Google Sheets.
Section: Zapier Automations
This Zap runs when a new booking is made in TidyCal, adds or updates the contact in LeadConnector, and records the booking in Google Sheets. After a filter and a text formatting step, it looks up the matching row in the spreadsheet and then splits into two paths, so each booking ends up in the sheet.
How it works
Image: The ten-step Zap: a TidyCal booking trigger, filter and text formatting, LeadConnector, a Google Sheets lookup, and two paths that update or create a row.
The script is scheduled to run daily to ensure real-time relevancy of its functions.
Section: Google Apps Script
Image: Extracting a hyperlink from a spreadsheet cell to locate the right file before checking its dates.
Image: A due-diligence checkup variant: comparing today’s date against the sheet before sending a scheduled compliance email.
Image: The companion screening script that walks each row and extracts the linked spreadsheet before processing it.
Automatically create short, engaging, and fact-based posts (with emojis!) based on your content ideas, and publish them to the right platform.
Section: AI Agents
Objective:
Automatically create short, engaging, and fact-based posts (with emojis!) based on your content ideas, and publish them to the right platform.
Implementation:
This workflow grabs an idea from your Google Sheet, uses AI to turn it into a social-ready post, and then posts it to either LinkedIn or X (Twitter), depending on your selection.
Outcome:
Posts It Where It Belongs
Done. One idea, one click, and you’ve got content live on the right platform, no copy-pasting needed.
A Python job that reads daily Ticketmaster audit PDFs from email, stores every figure in BigQuery and publishes a Google Sheet that mirrors the team’s existing workbook.
Section: Python Automation
An events company received daily Ticketmaster audit PDFs by email and re-typed the figures into a workbook by hand.
A daily job reads the report emails through the Gmail API (with an OAuth refresh token), downloads and parses the audit PDFs, stores every figure in BigQuery, and publishes a Google Sheet that mirrors the team’s existing workbook. It was built spec first: a design spec, then an implementation plan, then tests with fixture PDFs, then the pipeline.
Image: The project repository, with the ticket-count source code, tests, scripts and design documents.
Image: The Google Sheet the job publishes: tickets sold per day against capacity, split into GA and VIP, with the percentage sold. Event names and some tab names are hidden.
Image: The Run Log tab, with one row for each run of the job and its time.
Built with
Python, the Gmail API (OAuth), PDF parsing, BigQuery, the Google Sheets API and pytest.
To turn positive and interesting news stories into podcast-style audio scripts using AI.
Section: AI Agents
Objective:
To turn positive and interesting news stories into podcast-style audio scripts using AI.
Implementation:
The system collects news stories from the BBC website, checks if they are podcast-friendly, rewrites them into an engaging script, and finally prepares them for audio conversion.
Outcome:
To fetch product details from Amazon and alert you if the price drops, because who doesn’t love a good deal? 💸
Section: AI Agents
Objective:
To fetch product details from Amazon and alert you if the price drops, because who doesn’t love a good deal? 💸
Implementation:
The workflow grabs product links from a database, scrapes product info, compares old vs new prices, updates the records, and, if there's a discount, sends you an email so you can grab it before it’s gone.
Outcome:
Developed an automated solution for a client who received daily PDFs via email.
Section: Google Apps Script
Developed an automated solution for a client who received daily PDFs via email. Created a Google Apps Script that scans Gmail for specific emails containing PDF attachments, downloads and parses these PDFs to extract vital information, and transfers this extracted data into a designated Google Sheet. The script is scheduled to run automatically at a pre-defined time each day, ensuring timely data processing and minimal manual intervention.
Features
Image: Feature list and the two-workflow design: a scheduled main flow (PDF parsing → validation → sheet integration) alongside a manual upload flow (login → upload).
Image: The FastAPI backend that handles the upload, invoice parsing, and Sheets integration.
This Zap runs every day, goes through the cards on a Trello board, and uses ChatGPT to write a social media caption and hashtags that are saved on each Trello card.
Section: Zapier Automations
This Zap runs every day, goes through the cards on a Trello board, and uses ChatGPT to write a social media caption and hashtags that are saved on each Trello card. It looks up the cards from a single Trello pillar and loops over them, so every step after the loop runs once for each card. For each card it checks the card, reads its attachments, asks ChatGPT for the caption and hashtags, and updates the Trello card with them.
How it works
Image: The first ten steps of the Zap: a daily schedule, the Trello card lookup, a loop over each card, a filter, the card attachments, ChatGPT and a Trello card update.
This Zap runs every day, picks up the Trello cards for that day, and publishes their images and captions to Facebook, LinkedIn and Instagram.
Section: Zapier Automations
This Zap runs every day, picks up the Trello cards for that day, and publishes their images and captions to Facebook, LinkedIn and Instagram. Each card holds the post images and a caption for each platform, so content is prepared in Trello and published without manual uploading.
How it works
Image: Steps 1–11: the daily schedule, the Trello card lookup, a loop over each card, and date and status formatting.
Image: Steps 12–48: caption extraction, Trello updates, and the Paths that publish to Facebook Pages, LinkedIn and Instagram for Business.
Automatically fetch and analyze top-performing Instagram videos from popular creators to uncover what makes them stand out.
Section: AI Agents
Objective:
Automatically fetch and analyze top-performing Instagram videos from popular creators to uncover what makes them stand out.
Implementation:
The workflow starts by pulling Instagram usernames from your list, finds the creator’s most viewed video, and uses AI to break it down (frame by frame, word by word) to reveal the hidden ingredients of viral success.
Outcome
This Zap watches the timeline stages of Monday.com items and notifies the team in Slack each time an item reaches a new stage.
Section: Zapier Automations
This Zap watches the timeline stages of Monday.com items and notifies the team in Slack each time an item reaches a new stage. Items on the Monday.com boards follow a programme timeline: 45, 60 and 90 days in, and 60, 45 and 1 day left. When an item reaches one of these stages, the Zap triggers, updates the item and sends a message to the team’s Slack channel.
At the 45-days-left stage it also checks Close for the opportunity: if it is found, the stage is updated, and if not, a new opportunity is created. A Slack notification goes out either way.
How it works
Image: Steps 1–16 and 31–33: the webhook trigger, the monday.com lookup, the Python step, and the Paths that update items and notify Slack.
Image: Steps 17–30: the Close branches that find contacts and create leads and opportunities, each ending in a Slack message.
The primary goal of this automation is to streamline the process of managing Shopify orders by automatically distributing them to the appropriate fulfillment sheets.
Section: Make Automations
The primary goal of this automation is to streamline the process of managing Shopify orders by automatically distributing them to the appropriate fulfillment sheets. This is particularly useful for a dropshipping e-commerce store that sources products from multiple suppliers, such as AliExpress.
A hosted, OAuth-protected MCP server in Python that lets a home-services business ask Claude about customers, jobs, invoices and leads, with write actions hidden unless allowed.
Section: Python Automation
A home-services business wanted to ask Claude questions about customers, jobs, invoices and leads, and to take safe actions, without giving it raw database access.
A Model Context Protocol server that exposes the full REST API of the business’s field-service software (Housecall Pro) as about 20 domain modules: customers, jobs, estimates, invoices, leads, employees, scheduling, webhooks and more. They are all mounted under one FastMCP app. It is deployed on Railway and connects straight into claude.ai.
Image: The server entry point: GitHub OAuth in front, one FastMCP app, and each domain module (customers, jobs, estimates, invoices, leads, employees) mounted under its own namespace.
Image: The repository: one Python module for each area of the field-service API, plus a Procfile for deployment on Railway. The commit messages are blurred.
Built with
Python, FastMCP, OAuth 2.0, REST and Railway.
A single Google Sheets template that turns raw sales, COGS and marketing cost data into live real-vs-estimated profit numbers for any date range.
Section: Dashboards & Reporting
An automated profit & loss tracker built in Google Sheets for an ecommerce business. Pulling sales, real COGS, marketing spend and other expenses into one model, it calculates real vs. estimated profit automatically for any date range instead of being rebuilt by hand every month.
Image: Monthly sales and profit dashboard: total sales, real/estimated profit, margins and marketing cost calculated automatically from raw order data.
Image: The same template applied to a different brand: totals, COGS and marketing cost recalculated instantly for any date range.
A daily dashboard view surfaces total and trailing-30-day sales, profit and expense metrics side by side, so the team can catch a bad week before it becomes a bad month.
Image: Daily dashboard: total and last-30-days sales, profit and expense metrics side by side for fast day-to-day monitoring.
A rolling 12-month view breaks total profit down into COGS, marketing cost, other expenses and disputes won, so the team can see exactly where margin is being gained or lost.
Image: Last-12-months pie chart breaking total profit down into COGS, marketing cost, other expenses and disputes won.
Built as a single Google Sheets template so finance reads live profit numbers for any date range without exporting from five different tools first.
An audit of the single Ubuntu server behind a financial-data subscription site, a fix for its silently failed social-posting pipeline, and a documented setup so it can be maintained safely.
Section: Python Automation
A financial-data subscription site ran a Python backend, scheduled jobs, blog and email automation and a social-posting pipeline, all on one Ubuntu VPS. The social pipeline had silently died. The client needed an audit, a fix and a roadmap.
A single source of truth: one SQLite database plus JSON outputs.
20:00 ET systemd timer → nightly_pipeline.sh
ingest OHLC → run scanners → build JSON → DB backup to Drive (rclone)
→ build newsletter + blog post (publish via WP REST API)
→ send daily email (Brevo)
15:45 ET systemd timer → live_pipeline.py (real-time signals + options pricing)
always systemd service → gunicorn Flask API :5500 behind nginx + Cloudflare Tunnel
cron 08:15 / 08:45 / every 15 min market hours / 21:00 → content engine renders PNG/MP4 cards and posts to IG / X / TikTokBuilt with
Python, Flask, SQLite, systemd, cron, bash, nginx, gunicorn, Cloudflare Tunnel, rclone, JWT auth, Stripe, the WordPress REST API, Brevo and the Post for Me API.
Turning a signed DocuSign travel contract into a master sheet row, a filed contract and an itinerary slide, automatically.
Section: Make Automations
An internal operations automation for a group travel company that manages college formal events.
When a group signs a travel contract in DocuSign, the operations team has several follow-up jobs: record the trip in the master ops spreadsheet, file the signed contract in the group’s Drive folder, and produce a Friday/Saturday/Sunday itinerary slide for the group.
This scenario does those three jobs automatically as soon as a DocuSign envelope is completed.
Built with Make, DocuSign, Google Apps Script, Anthropic Claude (claude-sonnet-4-6), Google Sheets, Google Slides and Google Drive.
Each signed contract holds the details the team needs in several places: hotel names and room counts, check-in ages, buses, venues, event times, food and bar packages, and payment and task due dates. Moving these by hand into the master sheet, then building a customer-facing itinerary from them, is repetitive and easy to get wrong.
A Make scenario that:
Image: Part of the Make scenario: the DocuSign trigger and download, the HTTP call to the Apps Script web app, Claude, and a router that splits into Google Sheets, Slides and Drive paths.
Image: An example three-day itinerary slide (group, dates, hotel and company details blurred for privacy).
A Make scenario that lets a team member ask a plain-English trip question in Slack and get an answer drawn only from the ops master sheet.
Section: Make Automations
An internal operations tool for a group travel team.
The operations team keeps all trip data in one Google Sheet (a “MASTER” tab in the workbook “Master Ops Fall 26/Spring27”). Each row is one group trip, with columns for dates, destination, ops coordinator, sales rep, contracts, hotel and rooming, transport, events, task due dates, and payment status.
This scenario lets a team member ask a plain-English question in Slack and get a structured answer drawn only from that sheet, without opening it and searching for the right row and column.
Built with Make, Anthropic Claude (claude-sonnet-4-6), Google Sheets and Slack.
The sheet is wide. The blueprint’s column list runs from column A to column BH, with more than 55 labelled fields per trip. Finding a single fact, such as a group’s hotel or room counts, means locating the right row, then scrolling to the right column.
A six-module Make scenario, triggered by a webhook, that:
Image: The Make scenario: a custom webhook, Claude turning the question into search terms, a Google Sheets search, a text aggregator, Claude answering from the results, and a Slack message.
Image: An example answer in Slack: the question, the search terms Claude worked out, and the matching groups with their dates and destination (group names blurred for privacy).
Create an AI-powered chatbot that helps The Fast Bite( a fast food restaurant) customers with menu queries, placing orders, and providing restaurant details in a fast and friendly manner.
Section: AI Agents
Objective:
Create an AI-powered chatbot that helps The Fast Bite( a fast food restaurant) customers with menu queries, placing orders, and providing restaurant details in a fast and friendly manner.
Implementation:
The RAG Chatbot for The Fast Bite automatically updates itself with the latest menu and restaurant info from Google Drive and quickly uses that to help customers with orders or questions. It provides fast and accurate responses to make the customer experience smoother.
Outcome:
Triggered by New Files
The chatbot starts working whenever a new file is added to The Fast Bite’s Google Drive folder. This could include updates to the menu or any other important information.
Downloading the Information
The chatbot downloads the new file automatically from Google Drive for processing.
Understanding the Data
It uses Google Gemini (AI) to turn the downloaded content into a format that the chatbot can understand.
Storing the Info
The processed data is stored in a system called Pinecone. This helps the chatbot quickly find the answers when customers ask questions.
Handling Customer Queries
When customers ask questions, the chatbot uses this stored information to provide relevant and helpful responses instantly.
Key Features
Two n8n workflows that find athlete news, draft the post, and publish it to Instagram once a person approves.
Section: n8n Automations
PeakNIL connects college athletes with brands for NIL deals. To stay visible and attract brands, it needs a steady stream of social media posts celebrating athlete achievements. These two workflows automate that process, from finding the news to publishing on Instagram, with a human approving every post.
Two connected automations handle the work, and a person approves the result.
Image: Workflow 1, Athlete Monitor: a schedule trigger reads the roster from Google Sheets, searches for news, has Claude draft the post, and emails it to the content manager through Gmail.
Image: Workflow 2, Reply Detection: a Gmail trigger reads the manager’s reply, then one branch builds the graphic with Placid and another publishes to Instagram after approval.
An n8n workflow that checks every 15 minutes for cards that are no longer approved and removes their still-scheduled posts from Metricool, without touching anything already published or about to go out.
Section: n8n Automations
A content team schedules social posts through Metricool from cards in Airtable. Each card stores the Metricool post ID for X, Facebook, LinkedIn and Threads. If a card is later denied, sent back to review, or its scheduling fails, the posts already scheduled for it would still go out. This workflow finds those cards and removes the leftover scheduled posts safely.
Image: Unschedule cleanup in n8n: a 15-minute schedule trigger, an Airtable search, a code step that splits each card into one item per Metricool ID, a lookup of each post, a decision step, a Delete? branch that either calls Metricool’s delete or skips to the merge, and a code step and Airtable update that clear the IDs and write the log.
AI-Powered Contract Validation, Human Review, Automated Google Drive Filing, Folder Organization, Missing-Term Detection & Document Tracking.
Section: Custom SaaS Platforms
The Contract Intake Tool is a web app that uses Claude AI to extract key terms from supplier contracts, flags missing information for human review, and automatically files approved contracts into the correct Google Drive folders. It also maintains a record of all filing activities..
Supplier contracts such as hotel, venue, and bus services) Were reviewed and filed manually, making the process time-consuming. Important terms like cancellation clauses, fees, and tax rates could be missed, and contracts sometimes ended up in the wrong Google Drive folders, making them difficult to find later for billing or disputes.
The solution is a web app that uses Claude AI to extract required terms from supplier contracts (PDFs), allows users to review missing information, and automatically files approved contracts into the correct Google Drive folders. PostgreSQL maintains a record of each filing, such as who filed it, what was filed, where it was filed, and when
Image: Figure: AI-Powered Supplier Contract Processing Workflow
The application is built using the following technologies:
The Contract Intake Tool simplifies supplier contract processing by combining AI-powered term extraction, human review, and automated Google Drive filing. It helps reduce manual work, identify missing terms, and maintain a clear record of filing activities.
A governed Power BI model unifying scheduling, EHR, billing and finance across four systems into two role-based dashboards refreshed every morning.
Section: Power BI
Multi-site clinic network: scheduling, EHR, billing & finance unified · 6-week engagement
Reports that used to take days across sites now land by 6am, and we act on them the same morning.
The network ran on four disconnected systems: scheduling, the EHR, billing/claims and finance. Leadership could never see patient flow, provider utilisation and revenue-cycle health in the same place, and each site’s monthly report was rebuilt by hand. I consolidated all four into one governed Power BI model behind two role-based dashboards, refreshed automatically every morning, turning days of manual reporting into a screen the team reads with their coffee.
Appointments vs utilisation, department mix, top sites, a day-by-hour utilisation heat map and capacity gauge.
Image: Patient Flow & Utilisation: Executive Overview
Billed vs collection rate, a claims funnel, AR aging buckets and net revenue by payer.
Image: Revenue Cycle & Claims
| Stage | What We Built | Tools |
|---|---|---|
| Sources | 4 systems: Scheduling · EHR · Billing · GL | REST / API / file connectors |
| Clean | Key standardisation | Power Query |
| Model | Star schema, shared date table, DAX | Power BI model + DAX |
| Secure | RLS by site, per-site access | RLS roles |
| Deliver | 06:00 refresh via gateway & service | Power BI Service + gateway |
After six weeks
With utilisation and no-shows visible by site and hour, the network reallocated clinic slots and tightened reminders, lifting utilisation five points while trimming no-shows, and replacing days of manual work with an automatic 6am refresh reconciled to the ledger.
A Make scenario that turns one row of a Google Sheets newsletter planner into a finished draft campaign in Campaign Monitor, in one of three layouts chosen by the editor.
Section: Make Automations
A publishing business sends a regular email newsletter with news articles, sponsored posts, a destination report and a podcast episode. Building each issue by hand in the email tool means copying titles, images, excerpts and links into a template, block by block. This Make scenario lets the editors plan the whole issue in a Google Sheet and creates the campaign automatically.
Image: The Make scenario: Google Sheets searches for a row marked Create, a router picks one of three templates, a code step builds the newsletter content, an HTTP call creates the campaign from the template, and Google Sheets updates the row. A Skip step on each route handles errors.
An AI reporting system that pulls Meta Ads data, flags underperforming ads in real time, and recommends budget and creative changes.
Section: AI Agents for Ecommerce, AI Agents
Before this system, marketers spent hours manually collecting and analyzing campaign data for Facebook and Instagram:
After implementing AI-Powered Meta Ads Reporting:
The system was designed to
🟦 Massive Time Savings
Each marketer saves ~7 hours/week, translating to ~364 hours/year
🟦 Faster Optimization
Campaign adjustments happen within 1 hour instead of 1–2 days
🟦 Improved ROI
ROAS increases by 15–25% due to timely reallocations and creative optimization
🟦 Error Reduction
Human errors in campaign adjustments drop by ~90%
🟦 Scalability
Campaign management scales from 10 ad sets to 50+ ad sets per account without extra staff
With AI-Powered Meta Ads Reporting
Detailed ClickUp workspace structure for a staffing company’s operations.
Section: ClickUp Setups
Lists
Lists
Lists
Lists
An AI tool that writes five cold email sequences in spintax format in minutes and checks each one against eight quality rules, rewriting any that fail.
Section: Python Automation
Cold email copy generation and quality control. Instead of spending hours writing email variations by hand in spintax format and checking each line against banned phrases and formatting rules, teams now get five production-ready email sequences in minutes.
Creating cold email variations meant hours of manual work. Writers had to draft email sequences by hand, then apply spintax format line by line, a tedious process where every variation had to be written and formatted separately. Quality control was completely manual: each line had to be checked against banned phrases and banned words, word counts verified, spintax coverage confirmed, and offer rotation rules checked. With no automated checklist, mistakes slipped through before emails went into the sending tool. Creating five email sequences took 5 to 10 hours of work, was error-prone, and depended entirely on someone being available to do it correctly.
Image: The team interface: a chat assistant on the left, a button to generate the week’s strategy, and Copy Variations and History at the top.
Step 1: Email sequences are generated
The automation takes the email parameters and requirements, then uses AI to generate five complete cold email sequences in full spintax format, with multiple variations per email step (A/B variants) so testing options are built in.
Step 2: Automatic quality checks run
Every generated copy is automatically checked against eight quality rules: word count, spintax coverage on every line, banned phrases, banned words, offer accuracy, hook uniqueness, offer rotation compliance, and more. If a copy passes all checks, it is flagged as production-ready. If it fails, the system automatically rewrites it (up to three retries) to meet the requirements.
Step 3: Ready-to-send copies are delivered
The team receives five email sequences with a pass or fail verdict on each. Every copy is either production-ready or clearly flagged as needing manual revision, so there are no surprises or quality issues after the copy goes into the sending tool.
Teams no longer spend 5 to 10 hours writing and quality-checking email sequences by hand. Five production-ready sequences now generate automatically in minutes. Quality control shifted from a manual checklist to an automated pipeline that catches banned phrases, spintax gaps, word count violations and formatting mistakes instantly. Every copy follows the same proven structure with consistent formatting. What used to take hours of manual writing and QA now happens automatically, freeing the team to focus on strategy and testing instead of production work.
The tool automates the full cycle from email copy generation to quality-checked delivery. Teams provide their email requirements, the automation generates five complete sequences in spintax format, automatic quality checks verify everything, and production-ready emails are delivered in minutes instead of hours. The team stays in control, since they review and approve the output, while the repetitive writing and quality-checking work is handled automatically.
An n8n workflow that turns one product photo into AI-generated model images plus eCommerce and lifestyle campaign shots, saved to Google Drive.
Section: n8n Automations, AI Agents
Before automation, the creative team manually handled photo shoots and model image generation, resulting in:
The goal was to integrate the entire creative photo shoot pipeline into one automated, AI-powered system to rapidly produce consistent, high-quality fashion campaign images.
By using n8n with AI models and image generation APIs, this workflow:
Here is how the automation changes creative production:
🟦 Zero manual promptwriting
All creative direction and prompt engineering is baked into the workflow.
🟦 Consistent, onbrand visuals
Every product gets a full set of standardized eCommerce shots plus lifestyle scenes.
🟦 Massive time savings
What used to take hours of backandforth between creative, photography, and AI tools now runs in minutes.
🟦 Scalable for any catalog
You can run this for 1 product or 1,000 products with the same quality bar.
🟦 Organized assets
All outputs go straight into the right Google Drive folder, named in a predictable way.
Here are the KPIs this automation improves
Time Savings
Manual creative + prompt time reduced by 70–90%.
A brand manager or designer saves several hours per campaign.
Error & Inconsistency Reduction
No more forgotten angles, missing lifestyle shots, or halfbaked prompts.
Every product gets the same full coverage: front, angle, back, detail, plus lifestyle.
Content Production Speed
Campaignready visuals can be generated the same day products arrive.
Faster gotomarket for new drops and collections.
Asset Organization
100% of generated images land in the correct Google Drive folder.
Standard naming like “AI Model” and “Result #X” keeps sets easy to browse.
Creative ROI
You reuse the same expert logic and creative direction across unlimited products.
More content, more speed, and less dependency on external shoots for every variation.
An always-on automation that detects abandoned Shopify carts and sends personalized, AI-written recovery emails.
Section: n8n Automations, Make Automations, AI Agents
Before automation, abandoned carts were handled manually or not followed up at all:
On average
For stores with 40–60 abandoned carts per day, this resulted in:
After implementing the abandoned cart recovery automation:
Time & Revenue Impact
Before
After
Monthly time savings
~100–120 hours saved per month
Revenue uplift (conservative example)
This system works like an always-on sales assistant:
The entire process runs silently in the background.
No dashboards to monitor. No buttons to click.
Open the JSON file preview
Open the attached file
Open Make.com
Log in to Make.com
Go to Scenarios
Click Create a new scenario
Choose Import Blueprint
Click Save
Rename it to
Shopify Abandoned Checkout Recovery with Order Verification
Email (Gmail / SMTP)
Confirm flow
The system now automatically sends AI-written recovery emails for verified abandoned checkouts.
With this automation in place
This workflow transforms abandoned carts from a missed opportunity into an automated revenue recovery system.
An n8n workflow that finds each newsletter issue after it is sent, removes machine clicks from the numbers, scores it against the account’s own baseline, and posts an AI analysis to the team.
Section: n8n Automations
A publisher sends a regular email newsletter through Kit. This n8n workflow scores every sent issue automatically. It pulls the issue’s stats from Kit, corrects the click numbers for machine traffic, compares the result with the account’s own history, asks Claude for an analysis, and shares it with the team.
Image: The Newsletter Performance Agent in n8n: a daily trigger or a manual run, a look-up of past issues and Kit broadcasts, a step that picks the sent issue, Kit stats and link clicks, the metrics code, the Claude analysis, and an Airtable row. The row then leads to the Telegram summary and run log on one branch, and to the proposed rules on the other.
End of part 1 of 4. Continue with part 2.