# Conversational Razorpay Analytics with Gemini and Telegram Bot: n8n workflow

> Started by an incoming Telegram message, and works across Telegram. It hands the judgement calls to Gemini.

Source: https://millionrounds.com/workflow/conversational-razorpay-analytics-with-gemini-and-telegram-b (Millionrounds; every figure on the page links to its filing or article)

[Automation library](https://millionrounds.com/workflows) · [Research and reporting](https://millionrounds.com/workflows?category=Research+and+reporting#library)

# Conversational Razorpay Analytics with Gemini and Telegram Bot

Started by an incoming Telegram message, and works across Telegram. It hands the judgement calls to Gemini. 22 steps, 4 branches: large, and worth reading before you trust it with anything live.

Large Calls a model: Gemini

[Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fconversational-razorpay-analytics-with-gemini-and-telegram-b)

**22 steps** Large: read it before trusting it with anything live

**4** Branches: places the flow splits

**0** Loops or waits

**1** Service it connects to

## The flow

Starts it 1 Model 12 Logic 5 Service 4

The steps in the order they run, from what starts it.

- 1 **Telegram Trigger** Telegram trigger *Starts it*
- 2 **Google Gemini Chat Model1** Lm Chat Google Gemini *Model*
- 3 **Google Gemini Chat Model** Lm Chat Google Gemini *Model*
- 4 **Google Gemini Chat Model2** Lm Chat Google Gemini *Model*
- 5 **Google Gemini Chat Model3** Lm Chat Google Gemini *Model*
- 6 **Intent Classifier** Agent *Model*
- 7 **Payments Processor** Agent *Model*
- 8 **AI Agent3** Agent *Model*
- 9 **Orders** Agent *Model*
- 10 **Order Processing Agent** Agent *Model*
- 11 **Refunds** Agent *Model*
- 12 **Refund Processing Agent** Agent *Model*
- 13 **General Chat Processing Agent** Agent *Model*
- 14 **Payment Branch** If *Logic*
- 15 **Refund Branch** If *Logic*
- 16 **Order Branch** If *Logic*
- 17 **General Chat Branch1** If *Logic*
- 18 **Fetch all payments** Razorpay *Service*
- 19 **Merge Responses** Merge *Logic*
- 20 **Fetch all orders** Razorpay *Service*
- 21 **Fetch all refunds** Razorpay *Service*
- 22 **Send a text message** Telegram *Service*

## How it's built

- **Starts on:** An incoming Telegram message
- **Steps:** 22, with 4 branches
- **Size:** Large: read it before trusting it with anything live
- **Connects to:** Telegram
- **Model:** Gemini

## Questions

What does it need to run?

An n8n account, plus your own Telegram account, and a key for Gemini. You connect your own accounts after importing it; none are included.

What starts it?

It starts on an incoming Telegram message.

Does it use AI?

Yes. It calls Gemini. Model calls are billed by the provider, not by n8n.

How long does it take to set up?

Take your time. At 22 steps it is large: read it before trusting it with anything live.

How do I import it?

Copy the workflow, open a new workflow in n8n and paste. The steps appear on the canvas, ready for your own accounts.

**Before you run it**

Nothing here has been tested by us. It is somebody's working automation, read and described from its own steps. Treat the connections it wants as a list of accounts it will touch, and read the 22 steps before you point it at anything that matters.

## Run it in n8n

- **Create your n8n account** Free to start. n8n is where the workflow runs. [Create an n8n account ↗](https://millionrounds.com/n8n)
- **Download the workflow** Free with a Millionrounds account. [Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fconversational-razorpay-analytics-with-gemini-and-telegram-b)
- **Paste it into n8n** Open a new workflow in n8n and paste. Then connect your own accounts.

Stored with the author's traces removed: canvas notes, instance identifiers, saved credential names and any live document they had left behind.

## Connects to

Each opens the other workflows that use it.

[Telegram](https://millionrounds.com/workflows?service=Telegram#library)

## Workflows like it

Also research and reporting, with the same services where possible, closest in size first.

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