diff --git a/docs/docs.json b/docs/docs.json
index eadbefcf..2236c79e 100644
--- a/docs/docs.json
+++ b/docs/docs.json
@@ -34,7 +34,8 @@
             "group": "Tutorials",
             "pages": [
               "tutorial/generate-presentation-over-api",
-              "tutorial/generate-presentation-from-csv"
+              "tutorial/generate-presentation-from-csv".
+              "tutorial/create-data-reports-using-ai"
             ]
           }
         ]
diff --git a/docs/tutorial/create-data-reports-using-ai.mdx b/docs/tutorial/create-data-reports-using-ai.mdx
new file mode 100644
index 00000000..5a216313
--- /dev/null
+++ b/docs/tutorial/create-data-reports-using-ai.mdx
@@ -0,0 +1,225 @@
+---
+title: "Create Data Reports Using AI"
+description: "Step-by-step guide to generating company sales reports from a CSV file"
+---
+
+In this tutorial, we will generate detailed, multi-slide sales data reports for multiple companies using a self-hosted Presenton's API and a Python script.
+
+This tutorial extends [Generate a PPT via API in 5 Minutes](./generate-presentation-over-api) and shows you how to automate the creation of structured sales reports from a CSV file using Python.
+
+So, do check it before continuing with this and make sure you have Presenton running locally or on any server, and you are able to generate presentations with it.
+
+---
+
+## 1. Prepare Your CSV File
+
+Save your sales data as `sales_data.csv`:
+
+```csv
+Company,Month,Region,Total Sales,Product A Sales,Product B Sales,Product C Sales,Quarter Target Achieved,Top Sales Rep,New Clients,Client Churn Rate,Growth vs Last Quarter,Marketing Spend,Customer Satisfaction,Notable Events
+AcmeCorp,2024-03,North,98000,45000,37000,16000,Yes,Sarah Dee,13,2%,5.5%,11500,8.9,"Launched B2B platform"
+AcmeCorp,2024-03,South,76800,30000,39000,7800,Yes,John Lee,9,3%,4.5%,9200,8.3,"New partnership established"
+BetaBiz,2024-03,West,82000,22000,47000,13000,No,Monica Tai,7,4%,-1.0%,10900,7.3,"Ad campaign underperformed"
+BetaBiz,2024-03,East,94500,40000,41000,13500,Yes,Derek Shah,11,2.2%,7.2%,12400,8.6,"Exceeded upsell targets"
+ZenithLtd,2024-03,Central,101300,38000,51200,12000,Yes,Rita Ganesh,14,1.1%,9.6%,13800,9.2,"Record-high client retention"
+ZenithLtd,2024-03,East,85450,25000,47000,13450,No,Marcus Bell,8,3.8%,-2.8%,10100,7.9,"Sales dip in Product C"
+GammaInc,2024-03,North,91200,39000,43000,9200,Yes,Emily Jones,10,1.5%,6.2%,11800,8.8,"Employee incentive program"
+GammaInc,2024-03,Sales Ops,79000,31000,39000,9000,No,David Yu,6,5.5%,-3.2%,8700,7.1,"System migration delayed"
+```
+
+---
+
+## 2. Install Python Requirements
+
+You’ll need the `requests` and `pandas` libraries:
+
+```bash
+pip install requests pandas
+```
+
+---
+
+## 3. Write the Python Script
+
+Let’s build the script step by step.
+
+### a. Import Libraries
+
+```python
+import os
+import pandas as pd
+import requests
+```
+
+### b. Create reports directory
+
+```python
+os.makedirs('reports', exist_ok=True)
+```
+
+### c. Load the CSV
+
+```python
+df = pd.read_csv("sales_data.csv")
+```
+
+### d. Group Data by Company
+
+```python
+company_groups = df.groupby("Company")
+```
+
+### e. Define a Function to Build the Prompt
+
+```python
+def build_prompt(company, group):
+    """
+    Build a markdown prompt with data summary, chart instructions, and slide structure.
+    """
+    summary = []
+    regions = group['Region'].unique()
+    total_sales = group['Total Sales'].sum()
+    total_clients = group['New Clients'].sum()
+    churn = group['Client Churn Rate'].mean()
+    satisfaction = group['Customer Satisfaction'].mean()
+    growth = group['Growth vs Last Quarter'].mean()
+    marketing = group['Marketing Spend'].sum()
+    notable = "; ".join(group['Notable Events'].unique())
+
+    # Markdown-structured prompt
+    prompt = f"""
+## Sales Report for {company}
+
+### 1. Executive Summary
+- Total sales: **${total_sales:,.0f}**
+- Average client churn: **{churn:.2f}%**
+- Customer satisfaction: **{satisfaction:.2f}/10**
+- Notable events: _{notable}_
+
+### 2. Regional Performance
+**Bar Chart:** Regional Total Sales
+
+| Region | Sales |
+|---|---|
+"""    
+    for region in regions:
+        reg_sales = group[group['Region'] == region]['Total Sales'].sum()
+        prompt += f"| {region} | ${reg_sales:,.0f} |\n"
+
+    prompt += """
+
+### 3. Product Performance
+**Bar Chart:** Sales by Product per Region
+
+| Region | Product A | Product B | Product C |
+|---|---|---|---|
+"""
+    for region in regions:
+        gr = group[group['Region'] == region]
+        a = gr['Product A Sales'].sum()
+        b = gr['Product B Sales'].sum()
+        c = gr['Product C Sales'].sum()
+        prompt += f"| {region} | ${a:,.0f} | ${b:,.0f} | ${c:,.0f} |\n"
+
+    prompt += f"""
+
+### 4. Key Metrics & Trends
+- Aggregate new clients this month: **{total_clients}**
+- Mean growth vs last quarter: **{growth:.2f}%**
+- Total marketing spend: **${marketing:,.0f}**
+
+### 5. Top Performers
+| Region | Top Sales Rep | New Clients |
+|---|---|---|
+"""
+    for region in regions:
+        gr = group[group['Region'] == region]
+        rep = gr['Top Sales Rep'].iloc[0]
+        clients = gr['New Clients'].iloc[0]
+        prompt += f"| {region} | {rep} | {clients} |\n"
+
+    prompt += """
+
+---
+
+**Instructions:**
+- Create 1 slide per section (5 total).
+- Use clean, professional visuals.
+- For charts, display the specified bar chart with given data.
+- Use summary bullet points before every chart or table for clarity.
+**Do exactly as in said here.**
+"""
+
+    return prompt
+```
+
+### f. Loop Over Each Company and Generate a Report
+
+```python
+for company, group in company_groups:
+    print(f"Generating report for {company}")
+    prompt = build_prompt(company, group)
+    data = {
+        "prompt": prompt,
+        "n_slides": "5",
+        "language": "English",
+        "theme": "light_red",
+        "export_as": "pdf"
+    }
+    response = requests.post(
+        "http://localhost:5000/api/v1/ppt/generate/presentation",
+        data=data
+    )
+    if response.ok:
+        result = response.json()
+        print("Downloading report...")
+        download_url = f"http://localhost:5000{result['path']}"
+        filename = f"reports/{company}_Sales_Report.pdf"
+        file_response = requests.get(download_url)
+        if file_response.ok:
+            with open(filename, 'wb') as f:
+                f.write(file_response.content)
+            print(f"Report for {company} saved as {filename}")
+        else:
+            print(f"Failed to download report for {company}: {file_response.status_code}")
+    else:
+        print(f"Failed to generate report for {company}: {response.text}")
+```
+
+Generated reports will be saved in the `reports` directory.
+
+You may change the URL `http://localhost:5000` to the URL of your Presenton instance.
+
+---
+
+## 4. Run the Script
+
+Save your script as `generate_sales_reports.py` and run:
+
+```bash
+python generate_sales_reports.py
+```
+
+Each company will get a detailed, multi-slide sales report, and you’ll see the download path for each file in your terminal.
+
+---
+
+## 5. How It Works
+
+- The script reads and groups your CSV by company.
+- It builds a well-structured markdown prompt for Presenton’s API (see [API Reference](./generate-presentation-over-api)).
+- It sends a POST request to generate a report for each company.
+- The API returns a download path for each generated PDF.
+- The file is downloaded and saved in the `reports` folder.
+
+---
+
+## 6. Next Steps
+
+- You can further customize the prompt or number of slides as needed.
+- For more on API options, see [Generate a PPT via API in 5 Minutes](./generate-presentation-over-api).
+- For advanced configuration (for example, using Ollama or GPU), see [Environment Variables](../configurations/environment-variables), [Using GPU](../configurations/using-gpu), and [Using Ollama Models](../configurations/using-ollama-models).
+
+<Info>
+  Need help? See the [full documentation](./index) or open an issue on GitHub.
+</Info>
\ No newline at end of file