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B2· Business, management and commerce

AI for Finance, Accounting & GST

You will reconcile marketplace payouts, prepare a GSTR-1 working and build a cash-flow forecast with AI as your spreadsheet partner, and your numbers will be checked against Saarthi's own engines to the rupee.

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Who it is for
BCom students, MBA finance students and anyone heading into accounts, GST, AP/AR or FP&A work for growing businesses.
AI core
9 units · 20 h
This course
6 modules · 12 lessons · 4.4 h
Live projects
2, on Professional and Career
01Roles it prepares you for
  • Accounts and GST associate
  • Accounts payable / receivable executive
  • FP&A associate
  • E-commerce finance and reconciliation analyst

The skills these roles ask for. Preparation, not a promise of a job.

02Tools you will use
  • Google SheetsFree tier
  • Excel for the webFree tier
  • Copilot in Excel / Python in ExcelCollege licence
  • Gemini in Google SheetsCollege licence
  • NotebookLMFree tier
  • Claude (free plan)Free tier
  • ChatGPT (free plan)Free tier
  • Gemini (free plan)Free tier
  • Saarthi MCP server over the anonymised seller data packSaarthi sandbox
  • n8n (Saarthi-hosted sandbox)Saarthi sandbox
  • Saarthi anonymised seller data packSaarthi sandbox

You never pay for a tool subscription. “Verified” means we checked the free access on the vendor’s own site this month. Tool names describe what you learn; no vendor endorses Launchpad.

03Syllabus

What you will learn, in order.

Lesson films are narrated with an AI voice, over visuals made with AI tools and checked by our team. Saarthi, the coach, is an AI. Mentors and reviewers are people.

Part 1 · The AI core, shared by every stream

00Set up your coach1 hLearn how the core works, write the learning-context document that tells every AI tool who you are, and set Saarthi up as a coach that makes you think instead of thinking for you.
  1. How this core works6 min
  2. Write your learning-context document8 min
  3. Seven roles for AI, and study modes7 min
01How LLMs work and fail2.5 hBuild a working mental model of a large language model: tokens, prediction, context windows and memory. Then learn its predictable failures (hallucination, sycophancy, stale knowledge, bad arithmetic) and reproduce them yourself.
  1. Tokens and next-word prediction7 min
  2. Context windows and memory7 min
  3. Hallucination, sycophancy and other failures8 min
  4. Lab: one prompt, three models, five failures8 min
02Description and context engineering3.5 hWrite briefs that get the right output the first time: role, task, context, examples and format. Then make them reusable with Claude and ChatGPT Projects, Gemini Gems, custom GPTs and NotebookLM, and learn to work with PDFs, spreadsheets and images.
  1. The brief: role, task, context, format8 min
  2. Examples and output formats7 min
  3. Projects in Claude and ChatGPT8 min
  4. Gems, custom GPTs and NotebookLM8 min
  5. Working with files: PDFs, spreadsheets, images8 min
03Verify everything2.5 hCheck AI output the way fact-checkers do: lateral reading, tracing citations and numbers to the original, using deep-research modes without trusting them blindly, and testing a prompt properly with a 10-case golden set.
  1. Lateral reading7 min
  2. Checking citations and numbers8 min
  3. Deep-research modes: use and limits7 min
  4. Your first eval: a 10-case golden set8 min
04Connectors and MCP2 hConnect AI to the places your work lives (Drive, Gmail, Sheets, business data) without writing code. Learn what an MCP server is, why a reviewed directory differs from unreviewed community servers, how to grant the least access that works, and how to keep browser extensions on a short leash.
  1. What connectors and MCP are8 min
  2. Trust, least privilege and the reviewed directory8 min
  3. Browser extensions and AI browsers7 min
  4. Lab: ask the seller-data MCP server, check every answer8 min
05Agents and automations3.5 hHand multi-step work to AI safely. Tell an agent from an automation, decide what to delegate, use browser and coding agents with care, and build an n8n workflow that uses AI with a human-approval step before anything leaves the system.
  1. Agents vs automations: what to delegate8 min
  2. Browser agents, safely7 min
  3. Automation basics with n8n and Zapier8 min
  4. Lab: build an automation with a human-approval step8 min
  5. Failure modes and your failure-mode note7 min
06AI for learning and careers1.5 hUse AI to learn faster without outsourcing the learning, write applications that still sound like you, and practise interviews out loud with Saarthi.
  1. Learning with AI, not instead of learning7 min
  2. Applications in your own voice7 min
  3. Mock interview with Saarthi8 min
07Diligence: law, ethics, integrity2.5 hThe rules that apply when you use AI in India: the DPDP Act 2023 and its 2025 Rules, academic integrity and disclosure, copyright (including where Indian law is still unsettled), and bias. You finish by writing your own AI-use policy.
  1. DPDP Act 2023: personal data and AI8 min
  2. Academic integrity and disclosure7 min
  3. Copyright and AI in India8 min
  4. Bias and fairness7 min
  5. Write your personal AI-use policy7 min
08Core capstone1 hPut all four Ds together on one anonymised marketplace settlement file: ask good questions, automate one step, verify every number against Saarthi's P&L engine, and defend your work live in five minutes.
  1. The capstone brief6 min
  2. Lab: ask, automate, verify8 min
  3. Prepare your 5-minute defence7 min

Part 2 · AI for Finance, Accounting & GST

01How marketplace money actually flows2 lessonsFrom the price a buyer pays to the rupees that reach a seller's bank: fees, GST on fees, TCS, TDS, refunds and reserves.
  1. From ₹1,299 order to bank credit12 min
  2. Read a settlement file with AI and check every line25 min
02Reconciliation: orders, settlements and the bank2 lessonsThe three checks that find money a marketplace underpaid or never paid, how Saarthi's reconciliation engine runs them, and how to do them yourself.
  1. Three checks that find missing money12 min
  2. Reconcile a month and match Saarthi's engine35 min
03GST for online sellers and the GSTR-1 working2 lessonsPlace of supply, the B2CS/B2CL split, credit notes, HSN and the e-commerce table, and how to build a GSTR-1 working from an MTR without filing anything.
  1. GST basics every e-commerce accountant needs14 min
  2. Build a GSTR-1 working from an anonymised MTR40 min
04Spreadsheet copilots without spreadsheet disasters2 lessonsWhat Copilot in Excel, Python in Excel and Gemini in Sheets do, the free path when you have no licence, and the habits that stop an AI formula from quietly ruining a model.
  1. Copilots, formulas and the five checks10 min
  2. SKU unit economics with an AI pair30 min
05The 13-week cash-flow forecast2 lessonsForecasting a seller's cash week by week from settlement timing, supplier terms, ads and tax payments, with scenarios for the festive season.
  1. Why profitable sellers run out of cash10 min
  2. Build the forecast and stress it35 min
06Policies, month-end close and variance commentary2 lessonsAnswering fee and tax questions from source documents with citations, running a repeatable month-end close, and writing variance commentary a founder will read.
  1. Grounded answers and a close you can repeat10 min
  2. A close pack with cited policy answers30 min
04Live projects

Two briefs. Real-shaped work.

  1. Project 1

    Settlement reconciliation: orders vs payouts vs fees

    The sandbox seller suspects its marketplace payouts are short. Reconcile two months of orders, settlements and bank credits, find every unpaid, short-paid and over-credited item, explain each with evidence, and draft (but never send) the case text the seller would raise. Your findings are compared line by line with the frozen output of Saarthi's reconciliation engine on the same dataset version.

    You hand in

    • Reconciliation workbook with the three checks, tolerance and settlement-age rules stated at the top
    • Findings register: order or settlement id, type, amount, likely cause, evidence, confidence
    • Engine comparison: every difference with Saarthi's output explained, and which side is right
    • Draft case texts for the five largest findings (not sent)
    • A one-page summary for the seller: total at stake, what to chase first, what is noise
    • Prompt and formula log showing how AI was used and checked

    Built on Saarthi’s engines. Your key numbers are checked against Saarthi's own settlement reconciliation logic, run on the same anonymised data.

    Data: Saarthi anonymised seller data pack, frozen version: a synthetic apparel-and-home seller on Amazon.in and Flipkart with hashed order ids, invented SKUs and brand names, and no buyer names, phones or addresses. This project uses two months of orders, settlement files and a bank credit extract.. Reviewed by Saarthi against a published rubric, signed off by a mentor.

  2. Project 2

    GSTR-1 working from an anonymised MTR and a 13-week cash-flow forecast

    Prepare the month's GSTR-1 working for the sandbox seller from its anonymised MTR, reconciled to Saarthi's GSTR-1 engine, and build a 13-week direct cash-flow forecast with base, festive and stress scenarios that uses the GST payable you computed. Nothing is filed. Defend both in a live session with Saarthi playing the CA who will sign off.

    You hand in

    • GSTR-1 working: B2CS by state code and rate, B2CL invoices, credit notes, HSN summary, documents issued and Table 14 total
    • Tie-out sheet and engine-difference log
    • Open-questions list for the CA
    • 13-week forecast workbook (Inputs, Forecast, Checks, Notes) with three scenarios
    • Founder commentary: lowest cash balance and week per scenario, cause and two actions
    • A 5-minute live defence

    Built on Saarthi’s engines. Your key numbers are checked against Saarthi's own GSTR-1 logic, run on the same anonymised data.

    Data: Saarthi anonymised seller data pack, frozen version: a synthetic apparel-and-home seller on Amazon.in and Flipkart with hashed order ids, invented SKUs and brand names, and no buyer names, phones or addresses. This project uses one month's MTR (B2C and B2B), three months of orders and settlements for the lag, supplier terms and the bank opening balance.. Reviewed by Saarthi against a published rubric, signed off by a mentor.

05Practise out loud

In voice mock interviews and client calls, Saarthi plays: Mr Prakash Hegde (fictional), a Mangaluru chartered accountant whose practice handles GST and books for a dozen online sellers. He is hiring an associate. He hands you a settlement file and an MTR, asks where the money went, how you would build the month's GSTR-1 working, and what you would never let an AI tool do in his office.

On plans that include mock interviews. You get written feedback after every call.

06Enrol

Pick a plan for AI for Finance, Accounting & GST.

One payment. The access deadline for each plan is shown before you pay.

  • Foundation

    01

    Learn the AI your field now runs on.

    ₹2,999

    One payment. GST included.

    • Access for 120 days (about 4 months) from the day you pay
    • No 1:1 mentor sessions
    • The common AI core and your domain course
    • Saarthi, your AI coach, any hour
    • Hands-on labs on free tools
    • Verifiable certificate
    Enrol on Foundation

  • Professional

    02

    Prove it on real work.

    ₹7,999

    One payment. GST included.

    • Access for 180 days (about 6 months) from the day you pay
    • One 1:1 session with a mentor
    • Everything in Foundation
    • Two live projects, reviewed by Saarthi and a mentor
    • Public portfolio page of verified work
    • Voice mock interviews
    • One 1:1 coaching session
    Enrol on Professional

  • Career

    03

    Work alongside our team.

    ₹14,999

    One payment. GST included.

    • Access for 240 days (about 8 months) from the day you pay
    • Four 1:1 sessions with a mentor
    • One 1:1 call with an industry expert
    • Everything in Professional
    • Four-week supervised practicum with the Saarthi team
    • Four 1:1 coaching sessions with your mentor
    • An exclusive 1:1 call with an industry expert in your field
    • CV and LinkedIn review
    • Priority mentor replies
    Enrol on Career

Your access period starts the day you pay and is shown before you pay. One exam pause per enrolment, for up to 15 days. When access ends the course locks, and your portfolio page and certificate stay live. Full refund within 7 days, pro-rata after that, and an automatic refund for any practicum, 1:1 mentor or expert session we do not deliver. Refund policy