Avkash Kakdiya
🚀 Founder of iTechNotion — we build custom AI-powered automation workflows for startups, agencies, and founders. 💡 Specializing in agentic AI systems, content automation, sales funnels, and digital workers. 🔧 14+ years in tech | Building scalable no-code/low-code solutions using n8n, OpenAI, and other API-first tools. 📬 Let’s automate what slows you down.
Categories
Templates by Avkash Kakdiya
Create short-form AI videos for any topic using OpenAI, Veo 3 & Gmail
How it works This workflow automatically creates daily AI-generated videos for any niche. It generates a short script, converts it into a cinematic video prompt, and produces an 8-second video with Veo 3. The workflow waits for the video, downloads it, and sends it via Gmail with a ready-to-post social media description. You can customize the script prompt to match any industry or topic. Step-by-step Trigger the workflow Daily Trigger – Starts the workflow automatically every day. Generate content Generate Script – Creates a short, engaging script for your chosen niche. Generate Veo3 Prompt – Turns the script into a cinematic video prompt for Veo 3. Social Media Description – Writes an SEO-friendly description for LinkedIn, Instagram, and YouTube. Generate the video Create Video – Sends the prompt to Veo 3 for video generation. Wait for Video – Pauses until video processing is complete. Status – Checks whether the video is ready. If – Loops until the video is successfully generated. Download and share Download Video – Fetches the completed video file. Send a message – Emails the video with the social media description attached. Why use this? Create short, engaging videos in any niche automatically. Combine scriptwriting, video creation, and content delivery in one workflow. Save time by eliminating manual editing and waiting. Ensure consistent, professional social content for multiple platforms. Flexible for marketing, education, news, product updates, and more.
By Avkash KakdiyaConsolidate data from 5 sources for automated reporting with SQL, MongoDB & Google tools
How it works This workflow consolidates data from five different systems — Google Sheets, PostgreSQL, MongoDB, Microsoft SQL Server, and Google Analytics — into a single master Google Sheet. It runs on a scheduled trigger three times a week. Each dataset is tagged with a unique source identifier before merging, ensuring data traceability. Finally, the merged dataset is cleaned, standardized, and written into the output Google Sheet for reporting and analysis. Step-by-step Trigger the workflow Schedule Trigger – Runs the workflow at set weekly intervals. Collect data from sources Google Sheets Source – Retrieves records from a specific sheet. PostgreSQL Source – Extracts customer data from the database. MongoDB Source – Pulls documents from the defined collection. Microsoft SQL Server – Executes a SQL query and returns results. Google Analytics – Captures user activity and engagement metrics. Tag each dataset Add Sheets Source ID – Marks data from Google Sheets. Add PostgreSQL Source ID – Marks data from PostgreSQL. Add MongoDB Source ID – Marks data from MongoDB. Add SQL Server Source ID – Marks data from SQL Server. Add Analytics Source ID – Marks data from Google Analytics. Merge and process Merge – Combines all tagged datasets into a single structure. Process Merged Data – Cleans, aligns schemas, and standardizes key fields. Store consolidated output Final Google Sheet – Appends or updates the master sheet with the processed data. Why use this? Centralizes multiple data sources into a single, consistent dataset. Ensures data traceability by tagging each source. Reduces manual effort in data cleaning and consolidation. Provides a reliable reporting hub for business analysis. Enables scheduled, automated updates for up-to-date visibility.
By Avkash KakdiyaAutomate LinkedIn comment replies with GPT-3.5 & track in Google Sheets
How it works This workflow automates LinkedIn community engagement by monitoring post comments, filtering new ones, generating AI-powered replies, and posting responses directly on LinkedIn. It also logs all interactions into Google Sheets for tracking and analytics. Step-by-step Trigger & Fetch A Schedule Trigger runs the workflow every 10 minutes. The workflow fetches the latest comments on a specific LinkedIn post using LinkedIn’s API with token-based authentication. Filter for New Comments Retrieves the timestamp of the last processed comment from Google Sheets. Filters out previously handled comments, ensuring only fresh interactions are processed. AI-Powered Reply Generation Sends the new comment to OpenAI GPT-3.5 Turbo with a structured prompt. AI generates a professional, concise, and engaging LinkedIn-appropriate reply (max 2–3 sentences). Post Back to LinkedIn Automatically posts the AI-generated reply under the original comment thread. Maintains consistent formatting and actor identity. Data Logging Appends the original comment, AI response, and metadata into Google Sheets. Enables tracking, review, and future engagement analysis. Benefits Saves time by automating LinkedIn comment replies. Ensures responses are timely, professional, and on-brand. Maintains authentic engagement without manual effort. Prevents duplicate replies by filtering with timestamps. Creates a structured log in Google Sheets for auditing and analytics.
By Avkash KakdiyaAutomate job search & curation with JSearch API & Google Sheets
How it works This workflow automates the job curation process by retrieving pending job search inputs from a spreadsheet, querying the JSearch API for relevant job listings, and writing the curated results back to another sheet. It is designed to streamline job discovery and reduce manual data entry. Step-by-step Trigger & Input The workflow starts on a defined schedule (e.g., once per day). It reads a row from the Job Scraper sheet where the status is marked as "Pending". The selected row includes fields like Position and Location, which are used to build the search query. Job Search & Processing Sends a search request to the JSearch API using the Position and Location from the spreadsheet. Parses the API response and extracts individual job listings. Filters out empty, irrelevant, or invalid entries to ensure clean and relevant job data. Output & Status Update Writes valid job listings to the Job Listing output sheet with fields such as job title, company name, location, and more. Updates the original row in the source sheet to mark it as Scraped, ensuring it will not be processed again in future runs. Benefits Reduces manual effort in job research and listing. Ensures only valid, structured data is stored and used. Prevents duplicate processing with automatic status updates. Simple to expand by adding more job sources or filters.
By Avkash KakdiyaAutomated product ad image creation with OpenAI, Gemini & Google Workspace
How it works This workflow automates the generation of ad-ready product images by combining product and influencer photos with AI styling. It runs on a scheduled trigger, fetches data from Google Sheets, and retrieves product and influencer images from Google Drive. The images are processed with OpenAI and OpenRouter to generate enhanced visuals, which are then saved back to Google Drive. Finally, the result is logged into Google Sheets with a ready-to-publish status. Step-by-step Trigger & Data preparation Schedule Trigger – Runs workflow automatically on a set schedule. Google Sheets (Get the Raw) – Retrieves today’s product and model URLs. Google Drive (Download Product Image) – Downloads the product image. Google Drive (Download Influencer Image) – Downloads the influencer image. Extract from File (Binary → Base64) – Converts both product and model images for AI processing. AI analysis & image generation OpenAI (Analyze Image) – Creates an ad-focused visual description (lighting, mood, styling). HTTP Request (OpenRouter Gemini) – Generates an AI-enhanced image combining product + influencer. Code Node (Cleanup) – Cleans base64 output to remove extra prefixes. Convert to File – Transforms AI output into a proper image file. Save & update Google Drive (Upload Image) – Uploads generated ad image to target folder. Google Sheets (Append/Update Row) – Stores the Drive link and updates publish status. Why use this? Automates the entire ad image creation process without manual design work. Ensures product visuals are consistent, styled, and ad-ready. Saves final creatives in Google Drive for easy access and sharing. Keeps campaign tracking organized by updating Google Sheets automatically. Scales daily ad production efficiently for multiple products or campaigns.
By Avkash KakdiyaAutomate unified marketing reports with Google Analytics, Google Ads, Meta Ads & HubSpot
How it works This workflow runs on scheduled weekly and monthly triggers to generate unified marketing performance reports. It processes multiple websites by collecting analytics data, paid ads performance, and CRM leads, then calculates KPIs and insights automatically. The workflow sends structured reports via email and stores historical data in Google Sheets. It ensures consistent reporting without manual effort. Step-by-step Step 1: Trigger & report type detection Schedule Trigger2 – Triggers the workflow weekly at a predefined time. Schedule Trigger3 – Triggers the workflow monthly at a predefined time. check month and week1 – Identifies whether the run is weekly or monthly and sets flags. Set Websites and Campaings1 – Defines websites, GA4 property IDs, and mapped ad campaigns. Expand Websites1 – Expands the website array into individual website items. Attach Run Flags1 – Attaches weekly or monthly flags to each website record. Step 2: Website & ads data processing Loop Websites1 – Iterates through each website independently. Get a report – Fetches website traffic and engagement metrics from analytics. Get many campaigns – Retrieves Google Ads campaign data. Fetch Meta Ads – Fetches Meta Ads performance data via API. Filter Google Ads By Website1 – Filters Google Ads campaigns by website. Filter Meta Ads By Website1 – Filters Meta Ads campaigns by website. Merge1 – Merges analytics, Google Ads, and Meta Ads datasets. Build Website Dataset1 – Builds a unified dataset per website. Calculate KPIs & Campaign Insights1 – Calculates spend, CTR, CPA, CPL, conversions, and performance insights. Append or update row in sheet2 – Stores website-level marketing metrics in Google Sheets. Step 2.1: Marketing report generation Prepare Report Data2 – Combines all website datasets into a unified report object. Switch – Routes execution based on weekly or monthly report type. Send Weekly Marketing report2 – Sends the weekly marketing performance email. Send Monthly Marketing Report2 – Sends the monthly marketing performance email. Step 3: HubSpot lead analysis Fetch1 – Fetches leads from HubSpot CRM. Filter Hubspot Leads – Filters leads based on weekly or monthly time range. Summarize Hubspot Leads – Aggregates lead status and lifecycle metrics. Prepare Report Data3 – Prepares CRM summary data for reporting. Step 3.1: CRM reporting & storage Switch3 – Routes CRM reporting by report type. Send Weekly Marketing report3 – Sends the weekly CRM summary email. Send Monthly Marketing Report3 – Sends the monthly CRM summary email. Code in JavaScript1 – Transforms CRM data for storage. Append or update row in sheet3 – Stores CRM lead performance data in Google Sheets. Switch3 – Routes CRM reporting by report type. Send Weekly Marketing report3 – Sends the weekly CRM summary email. Send Monthly Marketing Report3 – Sends the monthly CRM summary email. Code in JavaScript1 – Transforms CRM data for storage. Append or update row in sheet3 – Stores CRM lead performance data in Google Sheets. Why use this? Automates complex weekly and monthly marketing reporting. Unifies website analytics, ad platforms, and CRM data in one flow. Delivers consistent KPI calculations and insights every run. Maintains historical performance logs in Google Sheets. Scales easily across multiple websites and campaigns.
By Avkash KakdiyaDaily competitor research automation using SerpAPI, Google Sheets & Airtable
How it works This workflow automatically collects a list of companies from Google Sheets, searches for their competitors using SerpAPI, extracts up to 10 relevant competitor names with source links, and logs the results into both Google Sheets and Airtable. It runs on a set schedule, cleans and formats the company list, processes each entry individually, checks if competitors exist, and separates results into successful and “no competitors found” lists for organized tracking. Step-by-step Trigger & Input Auto Run (Scheduled) – Executes every day at the set time (e.g., 9 AM). Read Companies Sheet – Pulls the list of companies from a Google Sheet (List column). Clean & Format Company List – Removes empty rows, trims names, and attaches row numbers for tracking. Loop Over Companies – Processes each company one at a time in batches. Competitor Search Search Company Competitors (SerpAPI) – Sends a query like "{Company} competitors" to SerpAPI, retrieving structured search results in JSON format. Data Extraction & Validation Extract Competitor Data from Search – Parses SerpAPI results to: Identify the company name Extract up to 10 competitor names Capture the top source URL Count total search results Has Competitors? – Checks if any competitors were found: Yes → Proceeds to logging No → Logs in “no results” list Logging Results Log to Result Sheet – Appends or updates competitor data into the results Google Sheet. Log Companies Without Results – Records companies with zero competitors found in a separate section of the results sheet. Sync to Airtable – Pushes all results (successful or not) into Airtable for unified storage and analysis. Benefits Automated Competitor Research – Eliminates the need for manual Google searching. Daily Insights – Runs automatically at your chosen schedule. Clean Data Output – Stores structured competitor lists with sources for easy review. Multi-Destination Sync – Saves to both Google Sheets and Airtable for flexibility. Scalable & Hands-Free – Handles hundreds of companies without extra effort.
By Avkash KakdiyaScrape LinkedIn job listings with Phantombuster & save to Google Sheets
How it works This workflow automatically scrapes LinkedIn job postings for a list of target companies and organizes the results in Google Sheets. Every Monday morning, it checks your company list, runs a LinkedIn job scrape using Phantombuster, waits for the data to be ready, and then fetches the results. Finally, it formats the job postings into a clean structure and saves them into a results sheet for easy analysis. Step-by-step Start with Scheduled Trigger The workflow runs automatically at 9:00 AM every Monday. It reads your “Companies Sheet” in Google Sheets and filters only those marked with Status = Pending. Scrape LinkedIn Jobs The workflow launches your Phantombuster agent with the LinkedIn profile URLs from the sheet. It waits 3 minutes to let the scraper finish running. Then it fetches the output CSV link containing the job posting results. Format the Data The scraped data is cleaned and structured into fields like: Company Name Job Title Job Description Job Link Date Posted Location Employment Type Save Everything in Google Sheets The formatted job data is appended into your “Job Results” Google Sheet. Each entry includes a scrape date so you can track when the data was collected. Why use this? Automates job market research and competitive hiring analysis. Collects structured job posting data from multiple companies at scale. Saves time by running on a schedule with no manual effort. Keeps all results organized in Google Sheets for easy review and sharing. Helps HR and recruitment teams stay ahead of competitors’ hiring activity.
By Avkash KakdiyaAutomate lead enrichment & personalized outreach with HubSpot, Phantombuster & GPT
How it works This workflow enriches and personalizes your lead profiles by integrating HubSpot contact data, scraping social media information, and using AI to generate tailored outreach emails. It streamlines the process from contact capture to sending a personalized email — all automatically. The system fetches new or updated HubSpot contacts, verifies and enriches their Twitter/LinkedIn data via Phantombuster, merges the profile and engagement insights, and finally generates a customized email ready for outreach. Step-by-step Trigger & Input HubSpot Contact Webhook: Fires when a contact is created or updated in HubSpot. Fetch Contact: Pulls the full contact details (email, name, company, and social profiles). Update Google Sheet: Logs Twitter/LinkedIn usernames and marks their tracking status. Validation Validate Twitter/LinkedIn Exists: Checks if the contact has a valid social profile before proceeding to scraping. Social Media Scraping (via Phantombuster) Launch Profile Scraper & 🎯 Launch Tweet Scraper: Triggers Phantombuster agents to fetch profile details and recent tweets. Wait Nodes: Ensures scraping completes (30–60 seconds). Fetch Profile/Tweet Results: Retrieves output files from Phantombuster. Extract URL: Parses the job output to extract the downloadable .json or .csv data file link. Data Download & Parsing Download Profile/Tweet Data: Downloads scraped JSON files. Parse JSON: Converts the raw file into structured data for processing. Data Structuring & Merging Format Profile Fields: Maps stats like bio, followers, verified status, likes, etc. Format Tweet Fields: Captures tweet data and associates it with the lead’s email. Merge Data Streams: Combines tweet and profile datasets. Combine All Data: Produces a single, clean object containing all relevant lead details. AI Email Generation & Delivery Generate Personalized Email: Feeds the merged data into OpenAI GPT (via LangChain) to craft a custom HTML email using your brand details. Parse Email Content: Cleans AI output into structured subject and body fields. Sends Email: Automatically delivers the personalized email to the lead via Gmail. Benefits Automated Lead Enrichment — Combines CRM and real-time social media data with zero manual research. Personalized Outreach at Scale — AI crafts unique, relevant emails for each contact. Improved Engagement Rates — Targeted messages based on actual social activity and profile details. Seamless Integration — Works directly with HubSpot, Google Sheets, Gmail, and Phantombuster. Time & Effort Savings — Replaces hours of manual lookup and email drafting with an end-to-end automated flow.
By Avkash KakdiyaAutomate Shopify Product Posting to Social Media with GPT-4.1-Mini & Data Tracking
How it works This workflow listens for new products in Shopify and transforms the product data into polished social media content. It generates captions and hashtags using an AI model, then posts the product to Instagram and Facebook using the Facebook Graph API. It logs every post to Google Sheets and sends a confirmation message to Discord. The flow ensures consistent publishing across all platforms with automated formatting and tracking. Step-by-step Trigger on Shopify product creation Shopify Trigger – Activates when a new product is added to the store. Prepare product data parse product data – Extracts product name, price, description, URL, image, and timestamp. Generate caption and hashtags Generate caption and hashtags – Uses an AI model to craft a caption and produce 10 relevant hashtags. Configure posting parameters Set Configuration – Stores access tokens, platform IDs, caption text, hashtags, and image URL. Publish to Instagram Create Instagram Media Container – Sends the image and caption to create a media container. Wait for Processing – Waits for the container to finish processing. Publish Instagram Media – Publishes the processed container to the Instagram feed. Publish to Facebook Download Image for Facebook – Downloads the product image from Shopify. Post to Facebook Page – Uploads the image with the caption and hashtags to the Facebook Page. Merge publishing results Merge – Combines responses from Instagram and Facebook for unified logging. Log post to Google Sheets Log Product Post Data – Appends product info, caption, and hashtags to a spreadsheet. Notify via Discord Notify Discord About Post – Sends a message summarizing the published product. Why use this? Ensures every new Shopify product is promoted instantly across major social platforms. Eliminates manual posting and caption creation with reliable automation. Maintains centralized logging for auditing, tracking, or analytics. Provides real-time team notifications to confirm successful posts. Reduces errors and keeps brand messaging consistent across channels.
By Avkash KakdiyaAutomate sales follow-ups with GPT-4o-mini, HubSpot, Slack, Teams & Telegram
How it works This workflow automatically generates personalized follow-up messages for leads or customers after key interactions (e.g., demos, sales calls). It enriches contact details from HubSpot (or optionally Monday.com), uses AI to draft a professional follow-up email, and distributes it across multiple communication channels (Slack, Telegram, Teams) as reminders for the sales team. Step-by-step Trigger & Input Schedule Trigger – Runs automatically at a defined interval (e.g., daily). Set Sample Data – Captures the contact’s name, email, and context from the last interaction (e.g., “had a product demo yesterday and showed strong interest”). Contact Enrichment HubSpot Contact Lookup – Searches HubSpot CRM by email to confirm or enrich contact details. Monday.com Contact Fetch (Optional) – Can pull additional CRM details if enabled. AI Message Generation AI Language Model (OpenAI) – Provides the underlying engine for message creation. Generate Follow-Up Message – Drafts a short, professional, and friendly follow-up email: References previous interaction context. Suggests clear next steps (call, resources, etc.). Ends with a standardized signature block for consistency. Multi-Channel Communication Slack Reminder – Posts the generated message as a reminder in the sales team’s Slack channel. Telegram Reminder – Sends the follow-up draft to a Telegram chat. Teams Reminder – Shares the same message in a Microsoft Teams channel. Benefits Personalized Outreach at Scale – AI ensures each follow-up feels tailored and professional. Context-Aware Messaging – Pulls in CRM details and past interactions for relevance. Cross-Platform Delivery – Distributes reminders via Slack, Teams, and Telegram so no follow-up is missed. Time-Saving for Sales Teams – Eliminates manual drafting of repetitive follow-up emails. Consistent Branding – Ensures every message includes a unified signature block.
By Avkash KakdiyaAuto-enrich & sync companies from Google Sheets to HubSpot using GPT-4o-mini
How it works This workflow starts whenever you add a new company name to a Google Sheet. It checks if the company name is filled in, then uses AI to find more details about the company like industry, size, location, and website. Next, it looks for the company in your HubSpot CRM. If the company is not there, it adds it automatically. Finally, it updates the Google Sheet with all the new company information so you have everything organized in one place. Step-by-step Start with Google Sheets The workflow watches your Google Sheet for new company names. It ignores any empty or incomplete entries. Get Company Details Uses AI (OpenAI GPT-4o-mini) to find more information about the company. Formats the AI results so they can be used easily. Check and Update HubSpot Searches your HubSpot CRM to see if the company already exists. If the company is new, it creates a record in HubSpot with the AI details. Save Everything in Google Sheets Prepares the enriched data for saving. Adds or updates the company information in the Google Sheet for easy tracking. Why use this? Automatically adds useful company info without manual work. Keeps your CRM clean by avoiding duplicates. Stores all updated company details in one place for easy access. Runs smoothly in the background without you needing to do anything after setup.
By Avkash Kakdiya