Hard prerequisites
None. Basic computer literacy — you should be comfortable navigating a browser, using Google Workspace or Microsoft 365, and installing software.
// FLAGSHIP PROGRAM
AI Workflow Design and Automation
Stop doing manually what a well-designed workflow can do for you — faster, more consistently, at scale.
6 weeks · Intensive, project-driven
In-Person
Online
Hybrid
Workflow automation as a professional skill
Every organisation runs on repetitive processes. A lead comes in through a form — someone copies it into a spreadsheet, someone else pastes it into a CRM, a third person sends a welcome email. A client submits a document — someone downloads it, reads it, summarises it, and forwards the summary to another team. A report is due every Monday — someone pulls data from three places, pastes it into a template, formats it, and sends it. Every week.
These processes are not complex. They are just manual. And manual means slow, inconsistent, and dependent on a person being available, undistracted, and not making a copy-paste error.
Workflow automation is the discipline of identifying these processes, designing systems that handle them reliably, and integrating AI where human judgment is actually needed — not where a trigger and an action will do.
This program teaches workflow automation as a professional skill — not just clicking buttons in Zapier, but understanding automation architecture, designing for failure, integrating AI intelligently, and measuring the business impact of what you build. You will leave with real workflows you deployed yourself, a methodology for identifying automation opportunities in any organisation, and the ability to make a measurable case for the work you do.
Built for people who want automation impact
This program is designed for:
- Business operations and administrative professionals who want to eliminate manual work from their roles
- Marketing, sales, HR, and finance professionals who want to automate the repetitive parts of their workflow
- Entrepreneurs and small business owners who want to run more efficient operations without hiring
- Graduates from any stream who want to position themselves as the person who makes a team more productive
- Developers and technical professionals who want a structured approach to automation alongside coding skills
This program works particularly well for students who completed the AI-Powered Data Science course, operations roles at startups and SMEs, and applicants to RevOps, Operations, Marketing Ops, or Business Analyst positions.
No prior coding experience is required for most of the program. Some modules involve light scripting — we support you through it.
Module 5 (Google Workspace Automation) involves basic Apps Script — we teach it from scratch. Module 6 (n8n) involves some JSON and HTTP familiarity — we cover the minimum needed.
Straightforward entry requirements
Soft prerequisites
Familiarity with at least one business tool — Google Sheets, HubSpot, Notion, Slack, Gmail, Airtable, or similar. You do not need to be an expert; you need real usage in your work.
Setup required before day one
A Google account, a free Zapier account, a free Make account, and a free n8n cloud account. Full setup instructions are sent after enrollment. All tools used have free tiers adequate for the course — no paid subscriptions required.
Design reliable workflows, then make them intelligent
Think like an automation designer before you touch any tool. Processes are automated only after they are understood, failure cases are anticipated, and edge cases are handled.
Topics
- Automation vs digitising a mess
- Trigger-action model: events start workflows; actions execute steps
- Conditions and branching: routers, filters, branch behaviour
- Data mapping: transformations, formatting, mismatched data types
- Webhook vs polling: latency implications and when to use each
- Process documentation: swim lanes, inputs, outputs, decisions, exceptions
- Five questions to ask before automating
- Identifying bad candidates: where errors have serious consequences
- ROI framing: time saved, error reduction, consistency improvement
- Error handling: retries, fallback paths, failure notifications
- Testing strategy and idempotency: what happens if a workflow runs twice
- Documentation: so someone else can maintain what you build
Hands-on
- Map three real business processes: lead intake, invoice approval, and content publishing
- Document triggers, steps, decision points, exception paths, and failure modes
- Identify automatable parts vs human-judgment parts, and where AI adds genuine value
Apply the mental model in two automation platforms. Build real workflows with deliberate failure testing and documentation.
Topics
- Zapier architecture: Zaps, triggers, actions, execution model
- Connecting apps: authentication, scopes, permissions
- Multi-step Zaps and chaining actions
- Filters, formatters, paths/branching, delays and schedules
- Zapier Tables/Interfaces and built-in data storage
- Error handling: task history, replaying failed tasks, notifications
- Zapier limits and cost logic at different usage levels
- Make architecture: scenarios, modules, visual canvas
- Routers, iterators/aggregators, error handlers, directives
- Data stores and webhooks in Make
- Choosing between Zapier vs Make: simplicity vs power, cost at scale, debugging
Hands-on
- Lead capture form → Google Sheets + HubSpot CRM + personalised welcome email (Zapier)
- New invoice in Sheets → Slack approval → send to accounting software + notify client (Make)
- Social monitoring → sentiment check → weekly digest email (Zapier)
- Drive upload → extract metadata → log to Airtable → notify via Slack (Make)
- Student enrollment form → CRM contact → email sequence → tracking sheet (Zapier)
Add genuine intelligence to workflows where interpretation, drafting, categorisation, or extraction is needed — with verification and fallbacks.
Topics
- The judgment test: interpret vs rule-based steps
- AI as a workflow step: calling LLM APIs from Zapier/Make
- AI for classification: leads, support tickets, documents
- AI for extraction: structured data from unstructured text
- AI for drafting: personalised context-aware writing
- AI for summarisation: documents, email threads, meeting notes
- AI for decision support: recommendations a human reviews
- Calling OpenAI/Claude APIs inside Zapier and Make (HTTP modules, auth, request structure)
- Prompt design for workflows and structured output parsing
- Verification checkpoints: human review before workflow continues
- Cost management at workflow volume
- Failure handling for AI steps and fallback logic
- Native AI integrations: Zapier AI actions, Make AI modules, tradeoffs
Hands-on
- Lead intake: AI classifies industry and urgency, routes to a sales rep with AI briefing
- Support ticket intake: AI categorises and extracts details, drafts response, human approves and sends
- Drive document received: AI extracts key info → populates structured Sheet → flags missing fields and notifies owner
Outcome
- Each extended automation includes a verification checkpoint and failure fallback
- Time saved vs manual version is measured and reported
Automation is not only connecting apps. Often the highest-leverage work is building smarter databases and workspaces where data flows correctly and AI assists cognitive work.
Topics
- Airtable architecture: bases, tables, records, fields, views
- Linked records and lookups: relational structures without a database
- Rollups and formulas: aggregating and computing across tables
- Airtable automations and AI actions inside Airtable
- Interfaces: dashboards and forms for non-technical users
- Connecting Airtable to Zapier and Make
- Notion databases: properties, views, filters, grouping
- Notion AI: summarisation, drafting, action extraction
- Notion automations and when Notion is the right tool
- Building a small-team operations system and keeping a single source of truth
Hands-on
- Airtable CRM with automated lead scoring and weekly pipeline emails
- Notion project workspace with AI-assisted meeting note processing feeding Airtable
- Zapier connection that creates projects automatically when deals are won in Airtable
Automate inside Google Workspace beyond no-code. Build real workflows using Apps Script — including AI steps.
Topics
- Apps Script essentials: what it is, where it runs, what it can access
- Script editor workflow: writing, saving, running
- JavaScript basics for Apps Script
- Sheets: reading, writing, formatting, creating sheets
- Gmail: reading emails, sending, labelling, filtering
- Drive: create, move, read file contents
- Forms: reading responses and triggering actions on submission
- Triggers: time-driven and event-driven triggers
Practical automations
- Report generation pipeline and scheduled email delivery
- Form-to-sheet-to-email pipelines without Zapier
- Automated data validation and cleaning
- Document generation from templates and data sources
Integrating AI
- Calling OpenAI/Claude from Apps Script using UrlFetchApp
- AI-powered email triage: classify, summarise, label, draft responses
- AI-powered report narration: table-to-natural-language summaries
Hands-on
- Weekly performance report: pull data, AI narrative, email list delivery
- Form-triggered onboarding: personalised Google Doc + tracking sheet + welcome email
- AI email classifier: runs on schedule, uses Claude to classify urgency/topic and drafts responses
n8n gives capabilities Zapier and Make cannot — especially for control, self-hosting, and code nodes. You learn to build workflows with reliability patterns.
Topics
- n8n architecture and when it is the right choice
- n8n cloud vs self-host tradeoffs and who should self-host
- Workflows, nodes, connections, and the n8n canvas
- Core nodes: HTTP Request, Set, If, Switch, Merge, Loop Over Items, Code, Wait
- Trigger nodes: Webhook, Schedule, app-specific triggers
- Credentials management: storing API keys and OAuth tokens securely
- Error workflows and separate failure paths
- Waiting and resuming for human checkpoints or external events
- Webhook response patterns (synchronous replies)
- AI integration in n8n: native AI nodes, AI Agent node, memory, LangChain integration
- RAG in n8n: vector store nodes, embeddings, retrieval pipeline
- When n8n AI workflows are enough vs building LangGraph agents
Hands-on
- AI triage inbox system: webhook receives requests, normalises data, AI agent classifies/prioritises, routes to escalation flows, error workflow alerts Slack
- Document intelligence pipeline: folder drop triggers extraction via HTTP Request, Code node structures output, vector store embeds and stores, Webhook exposes Q&A endpoint
Design and build a complete, real-world automation system for a business context — process analysis, deployed workflows, documentation, and measured impact. This is the artifact you take into job applications and client conversations.
Format
- Project scoped with your trainer during Module 6
- You bring business context; your trainer helps identify highest-leverage opportunities, select tools, and scope an achievable project
The project must include
- Documented process map of the current manual workflow
- At least three connected automations as a coherent system
- At least one AI-integrated step
- Error handling and failure notification path
- Before-and-after measurement: time saved, error reduction, or consistency improvement
- Documentation so someone else can maintain it
Example projects
- Content operations system: brief → draft outline + social teasers → routed writing → AI quality check → Airtable calendar + weekly analytics digest
- Candidate screening and onboarding: enrich applications → AI score + extract qualifications → schedule interviews → create accounts + send documents + reminders
- Invoice processing and reconciliation: AI extraction → match against purchase orders → flag discrepancies → log and notify vendor → monthly reconciliation reports
- Student lifecycle automation: enrollment → welcome → weekly check-in → attendance tracking → engagement alerts → reminders → certificate → alumni follow-up
- Customer operations system: WhatsApp/web inquiry → AI response + qualification → CRM → proposal generation → follow-ups → onboarding → invoice tracking → feedback collection
Assessment
- 20-minute presentation: process map, design decisions, demo each workflow live, show before-and-after measurement, answer what breaks and how you handle it
- Measurement is essential: proven impact beats technical complexity without evidence
What you will use to build
No-code automation: Zapier, Make, n8n
AI integration: OpenAI API, Anthropic Claude API, Zapier AI actions, Make AI modules, n8n AI Agent node
Productivity and data tools: Airtable, Notion, Google Workspace (Sheets, Gmail, Drive, Forms, Docs), Google Apps Script, Slack, HubSpot (free tier), Calendly
Supporting tools: Postman, Webhooks.site, JSON Formatter
All tools have free tiers adequate for the full program. No paid subscriptions required.
Make the team more productive
Operations Associate / Operations Analyst
Marketing Operations Executive
RevOps Associate
Business Analyst with automation skills
Growth Operations at a startup
AI Tools Specialist
Automation Consultant (freelance)
EA or Chief of Staff with automation capability
The positioning this program creates: in most organisations, the person who builds automation is the person who makes everyone else more productive. That visibility is disproportionate to the seniority of the role. A junior operations associate who automates the team's lead intake process, saves four hours a week, and can measure and present the impact is on a fast track that has nothing to do with tenure.
Freelance angle: automation consulting is one of the most accessible technical freelance services in the Indian market. A Zapier or Make specialist who can scope, build, document, and hand over a workflow system charges between ₹15,000 and ₹80,000 per project depending on complexity, with ongoing retainer arrangements common for maintenance. The project from this course is a credible portfolio piece for this market.
Companies hiring these profiles from Tamil Nadu: D2C brands and e-commerce companies, SaaS startups in Chennai, marketing and PR agencies, fintech and BFSI operations teams, EdTech companies, logistics and supply chain operations — any organisation running manual processes on spreadsheets is a potential employer or client for this skill set.
What you walk in with vs. what you walk out with
| Walk in with | Walk out with |
|---|---|
| Manual, repetitive processes | Designed, documented, deployed automation systems |
| No automation tool experience | Proficiency in Zapier, Make, n8n, and Airtable |
| No AI integration experience | AI steps embedded in workflows with verification checkpoints |
| No Apps Script knowledge | Working Google Workspace automations with scheduled triggers |
| No measurement habit | Before-and-after quantification of every workflow you build |
| No automation portfolio | A multi-workflow project system with documented impact |
| A fresher | The person on any team who makes everyone else more productive |
Pick a mode that fits your life
In-Person
Tiruvallur campus: daily sessions, live building alongside trainer, immediate help when a workflow breaks. Automation debugging benefits significantly from in-person collaboration — a second pair of eyes in a scenario saves an hour of frustration.
Online
Live instructor-led sessions via Zoom or Google Meet. Screen sharing works well for automation tools — canvas-based interfaces translate clearly to a shared screen. Same curriculum, same project, same assessment.
Hybrid
Attend for denser modules (Module 3 AI integration, Module 6 n8n). Online for the others. Recordings are available for review — not as a replacement for live attendance.
All three modes deliver the same curriculum and the same assessment. No mode is a reduced version.
// Enquire
Ready to start automating?
Call us or use the button below — we will call you within 24 hours.
