🔄️ AI warehouse inventory cycle count bot using GPT, Telegram and Google Sheets

Open on n8n.io

$20/month : Unlimited workflows

2500 executions/month

Try free

THE #1 IN WEB SCRAPING

Scrape any website without limits

Try free

HOSTINGER

Early Deal
DISCOUNT 20%

Self-hosted n8n

Unlimited workflows - from $4.99/mo

Try free

#1 hub for scraping, AI & automation

6000+ actors - $5 credits/mo

Try free

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Tags: Logistics, Supply Chain, Warehouse Operations, Paperless Processes, Inventory Management Context Hi! I’m Samir, Supply Chain Engineer, Data Scientist based in Paris, ...

Best for

Miscellaneous automation workflows
AI Chatbot automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.telegramtrigger, @n8n/n8n-nodes-langchain.openai, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.if, n8n-nodes-base.telegram, n8n-nodes-base.googlesheets, @n8n/n8n-nodes-langchain.agent

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Samir Saci.

Original n8n.io source

1.1 Workflow description

Title: 🔄️ AI warehouse inventory cycle count bot using GPT, Telegram and Google Sheets
Workflow name: 🔄️ AI warehouse inventory cycle count bot using GPT, Telegram and Google Sheets

Tags: Logistics, Supply Chain, Warehouse Operations, Paperless Processes, Inventory Management

Context

Hi! I’m Samir, Supply Chain Engineer, Data Scientist based in Paris, and founder of LogiGreen.

> Let's use AI with n8n to help SMEs digitalise their logistics operations!

Traditional inventory cycle counts often require clipboards, scanners, and manual reconciliation.

With this workflow, the operator walks through the warehouse, sends voice messages, and the bot automatically updates the inventory records.

Using AI-based transcription and structured extraction, we optimise the entire process with a simple mobile device connected to Telegram.

📬 For business inquiries, you can find me on LinkedIn

Demo of the workflow

In this example, the bot guides the operator through the cycle count for three locations.

The workflow automatically records the results in Google Sheets.

Who is this template for?

This template is ideal for companies with limited IT resources:

Inventory controllers who need a hands-free, mobile-friendly counting process
Small 3PLs and retailers looking to digitalise stock control

🎥 Tutorial

A complete tutorial (with explanations of every node) is available on YouTube:

What does this workflow do?

This automation uses Telegram and OpenAI’s Whisper transcription:

The operator sends /start to the bot.
The bot identifies the first location that still needs to be counted.
The operator is guided to the location through a Telegram message.
The operator records a voice message with the location ID and the number of units counted.
AI nodes transcribe the audio and extract location_id and quantity.
If the message cannot be transcribed, the bot asks the operator to repeat.
If the location is valid and still pending, the Google Sheet is updated.
The bot sends the next location, until the final one is completed.
The operator receives a confirmation that the cycle count is finished.

Next Steps

Before running the workflow, follow the sticky notes and configure:

Connect your Telegram Bot API
Add your OpenAI API Key to the transcription and extraction nodes
Connect your Google Sheets credentials
Update the Google Sheet ID and the worksheet name in all Spreadsheet nodes
Adjust the AI prompts depending on your warehouse location naming conventions

Submitted: 20 November 2025
Template designed with n8n version 1.116.2

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Telegram Trigger

Type / Role: n8n-nodes-base.telegramTrigger - telegramTrigger
Config choices: Version 1.2

Block 2 - Transcribe Operator Command

Type / Role: @n8n/n8n-nodes-langchain.openAi - openAi
Config choices: Version 1.8

Block 3 - Model: Information Extraction

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 4 - Structured Output Parser

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.3

Block 5 - Transcription Error

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.2

Block 6 - Ask to repeat

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1.2

Block 7 - Update Inventory Quantity

Type / Role: n8n-nodes-base.googleSheets - googleSheets
Config choices: Version 4.7

Block 8 - Error Message: Wrong Location

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1.2

Block 9 - Get Location, Qty

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2.2

Block 10 - Command

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.2

Block 11 - Collect Remaining Locations

Type / Role: n8n-nodes-base.googleSheets - googleSheets
Config choices: Version 4.7

Block 12 - Collect Audio

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1.2

Block 13 - Command Selection

Type / Role: n8n-nodes-base.switch - switch
Config choices: Version 3.3

Block 14 - Help Message

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1.2

Block 15 - Wait

Type / Role: n8n-nodes-base.wait - wait
Config choices: Version 1.1

Block 16 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 17 - Sticky Note8

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 18 - Sticky Note9

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 19 - Sticky Note10

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 20 - Sticky Note11

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 21 - Sticky Note12

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 22 - Sticky Note13

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 23 - Remaining Locations

Type / Role: n8n-nodes-base.aggregate - aggregate
Config choices: Version 1

Block 24 - Number of Locations

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Showing the first 24 of 38 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow	🔄️ AI warehouse inventory cycle count bot using GPT, Telegram and Google Sheets
Complexity	advanced
Nodes	38
Categories	Miscellaneous, AI Chatbot
Author	Samir Saci
Published	20 Nov 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/11055/11055.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Miscellaneous workflows AI Chatbot workflows

Frequently asked questions

What does 🔄️ AI warehouse inventory cycle count bot using GPT, Telegram and Google Sheets do?

Tags: Logistics, Supply Chain, Warehouse Operations, Paperless Processes, Inventory Management Context Hi! I’m Samir, Supply Chain Engineer, Data Scientist based in Paris, ...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Miscellaneous, AI Chatbot use case.

Samir Saci

31 workflows

Nodes

n8n-nodes-base.telegramtrigger @n8n/n8n-nodes-langchain.openai @n8n/n8n-nodes-langchain.lmchatopenai @n8n/n8n-nodes-langchain.outputparserstructured n8n-nodes-base.if n8n-nodes-base.telegram n8n-nodes-base.googlesheets @n8n/n8n-nodes-langchain.agent

Complexity

advanced

Published 20 Nov 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/11055/11055.json

Share Your Workflow

Have a useful automation to share? Publish it and help the community.

Submit Your Template How to Submit

Related Workflows

Predict airport queue wait times and email alerts with OpenAI and SendGrid

## Quick Overview This workflow accepts traveler flight details via webhook or runs every 5 minutes, predicts airport queue wait times with a custom JavaScript model, generates an alert message using OpenAI, emails the traveler via SendGrid, and logs the prediction to Google Sheets. ## How it works 1. Receives a POST request to a webhook with traveler/flight details or runs on a 5-minute schedule. 2. Normalizes the incoming data into a consistent context (flight, airport/terminal, traveler contact details, and live queue inputs). 3. Waits briefly to throttle processing, then calculates predicted security, immigration, and boarding wait times plus risk flags and an optimal arrival time. 4. Sends the prediction to OpenAI to generate a short, traveler-friendly alert message. 5. Formats the final alert payload (alert level, email subject/body) and prepares a row for tracking. 6. Sends the alert email through the SendGrid Mail Send API and appends the prediction record to a Google Sheets tab. ## Setup 1. Configure the webhook URL in the system that submits traveler requests (POST to `/airport-queue-check`) or enable the schedule trigger for proactive runs. 2. Add OpenAI credentials and select the chat model used to generate the traveler message. 3. Add Google Sheets OAuth2 credentials and replace `YOUR_SHEET_ID` and the target range (for example, `Predictions!A1:append`) in the Google Sheets request URL. 4. Add your SendGrid API key by replacing `YOUR_SENDGRID_API_KEY` in the Authorization header, and update the sender/recipient fields (including ensuring `travelerEmail` is provided by the trigger payload).

View

Send transactional SMS with the OVHcloud SMS API

## Quick overview This workflow manually triggers an HTTP request to the OVHcloud SMS API, signing it with your OVH application credentials to send a transactional SMS to a specified phone number. ## How it works 1. Runs when you manually execute the workflow. 2. Sets the OVHcloud API credentials, SMS service name, sender, and target API region. 3. Defines the SMS recipient number and message text to send. 4. Generates the OVHcloud request URL, JSON body, timestamp, and SHA1-based X-Ovh-Signature headers. 5. Sends a POST request to the OVHcloud endpoint `/sms/{serviceName}/jobs` to create an SMS sending job. ## Setup 1. Create OVHcloud API application credentials (Application Key and Application Secret) and a Consumer Key with SMS permissions. 2. Replace the placeholder values for `APPLICATION_KEY`, `APPLICATION_SECRET`, `CONSUMER_KEY`, `SMS_SERVICE_NAME`, `SMS_SENDER`, and `OVH_REGION`. 3. Update the `receiver` (E.164 format) and `message` fields with the SMS details you want to send, and ensure your OVHcloud SMS account has available credits. ## Requirements - OVH account - SMS credits (API account)

View

Tutor English chat messages using OpenRouter with Postgres memory and log to Supabase

## Quick overview This workflow receives English practice messages via a webhook, uses an OpenRouter chat model with Postgres-backed conversation memory to generate tutoring feedback, logs the exchange to Supabase, and returns the tutor’s reply as a JSON response. ## How it works 1. Receives a POST webhook request containing a `user_id` and `message`. 2. Extracts and standardizes the incoming fields so the workflow has clean `user_id` and `message` values. 3. Sends the message to an AI English tutor powered by OpenRouter, using Postgres chat memory keyed by `user_id` to maintain per-student context. 4. Logs the tutor output to a Supabase `conversations` table along with the user identifier and original message. 5. Returns a JSON response to the caller containing the tutor’s reply. ## Setup 1. Add an OpenRouter API credential and (optionally) choose a different model in the OpenRouter chat model configuration. 2. Add Postgres credentials and ensure the database is reachable from n8n so chat memory can persist sessions by `user_id`. 3. Add Supabase credentials and create a `conversations` table, then confirm the mapped columns (`user_id`, `role`, `message`) match your schema. 4. Copy the webhook URL from n8n and configure your app to POST a JSON body with `user_id` and `message` to that endpoint.

View

Need Custom Automation?

Get help designing a custom n8n workflow that connects your stack and fits your process.

🔄️ AI warehouse inventory cycle count bot using GPT, Telegram and Google Sheets

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Context

Demo of the workflow

Who is this template for?

🎥 Tutorial

What does this workflow do?

Next Steps

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Telegram Trigger

Block 2 - Transcribe Operator Command

Block 3 - Model: Information Extraction

Block 4 - Structured Output Parser

Block 5 - Transcription Error

Block 6 - Ask to repeat

Block 7 - Update Inventory Quantity

Block 8 - Error Message: Wrong Location

Block 9 - Get Location, Qty

Block 10 - Command

Block 11 - Collect Remaining Locations

Block 12 - Collect Audio

Block 13 - Command Selection

Block 14 - Help Message

Block 15 - Wait

Block 16 - Sticky Note

Block 17 - Sticky Note8

Block 18 - Sticky Note9

Block 19 - Sticky Note10

Block 20 - Sticky Note11

Block 21 - Sticky Note12

Block 22 - Sticky Note13

Block 23 - Remaining Locations

Block 24 - Number of Locations

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions