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A larger-input check of the same synthetic CSV-to-PDF demo. Saved evidence records 1,000 rows across 34 PDF pages, a USD 6,500.00 total, every order ID exactly once and byte-identical reruns. Continuation and final pages were visually checked. This proves correctness for that dataset, not speed or compatibility with unseen client files. It is another part of the same demo, not a separate client project.
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🚀 My First AI Automation Project with n8n
I recently built my first automation project — an AI-Powered Invoice Extraction & Tracking System.
The problem I wanted to solve was simple:
Imagine a business receiving dozens of invoices or cash memos every week. Someone has to open each file, read the information, and manually enter the vendor name, date, items, total amount, and category into a spreadsheet.
That’s repetitive, time-consuming, and easy to get wrong.
So I built a workflow where:
📂 An invoice is uploaded to Google Drive
→ 🤖 Gemini AI reads and extracts the invoice data
→ ⚙️ n8n processes and validates the information
→ 📊 The data is automatically added to Google Sheets
The best part?
No manual data entry. Just upload the invoice and the rest happens automatically.
While building it, I also worked with things like workflow triggers, loop control, API errors/retries, and handling multiple files.
For me, this project was less about simply “building an n8n workflow” and more about learning how AI + automation + data workflows can solve real business problems.
This is just my first step into AI automation, and I’m excited to build more practical systems like this.
If your business has a repetitive process that could be automated with AI, n8n, or data workflows, feel free to DM me. I’d be happy to discuss it.
#AIAutomation #n8n #Automation #ArtificialIntelligence #DataAnalytics #DataAnalyst #WorkflowAutomation #GenerativeAI #BusinessAutomation #AI
Smart pipeline! Have you added strict JSON schema validation after Gemini extracts the invoice fields? Found that it stops edge case hallucinations before the data ever hits Sheets.
Agentic AI Order-to-Cash Pipeline for E-Commerce
An end-to-end intelligent automation architecture designed to bridge e-commerce sales, payment processing, cognitive AI data enrichment, automated bookkeeping, and team notifications. This workflow transforms rigid, manual financial operations into a self-managing, responsive pipeline.
Trigger (Shopify): Captures incoming e-commerce orders instantly upon successful customer payment.
Data Enrichment (Stripe): Retrieves detailed payment gateway metadata, customer risk scores, and transaction status for enhanced security validation.
AI Reasoning Engine (OpenAI): Acts as the cognitive core to analyze unstructured order data, dynamically categorize products into appropriate accounting ledger codes, and flag anomalies.
Financial Settlement (Xero): Automatically provisions customer profiles and generates structured sales invoices within the accounting platform.
Operational Loop (Slack): Dispatches real-time, context-rich notifications and alerts directly to internal finance and operations channels.
'Prompt configuration hidden for client confidentiality
Amazing work
Stock Market Analysis & Insights Dashboard
An interactive stock market analysis platform for exploring market data, trends, and investment insights.
I developed an interactive stock market analysis web application that transforms financial market data into understandable insights through data analysis and visualization.
The platform enables users to explore stock performance, historical trends, market movements, and analytical indicators through an intuitive dashboard.
Key highlights:
Historical stock price analysis
Interactive charts and visualizations
Market trend analysis
Performance comparison
Data-driven insights
User-friendly dashboard experience
Automated data analysis workflow
Tech Stack: Python, Pandas, NumPy, Matplotlib/Plotly, Data Analysis, HTML, CSS, JavaScript
