PayrollPilot - LLM Parsing + Accountant's World Automation
PayrollPilot is a production-grade automation system that uses LLMs (Google Gemini) and Playwright-based bots to parse messy payroll reports and upload them seamlessly to Accountant’s World. It was used in a live business, processing over 1,000 payrolls, saving $20K+ in labor costs, and generating $2K+ in new revenue.
🚀 Key Features
- 🔍 LLM-powered Parsing: Converts messy payroll reports (PDF, RTF, Excel) into structured JSON.
- 📄 CSV Auto-Fill: Populates Accountant’s World-compatible CSV templates per client.
- 🤖 Portal Automation: Automates CSV uploads and tax payments to Accountant’s World (AW).
- 🧠 Smart Field Detection: Dynamically maps earnings, deductions, and tax categories.
- 📂 Batch Payroll Support: Processes multiple client folders in one click.
- 📊 Streamlit Interface: Simple UI to review extracted data and approve uploads.
📌 Use Cases
- Bookkeeping firms handling 50+ client payrolls
- Automation-first accountants aiming to cut labor costs
- LLM startups showcasing GenAI for operations
- Any business tired of manual AW uploads
🧠 Tech Stack
- Python 3.10+
- Streamlit – UI
- Playwright – Headless browser automation
- Google Gemini API – Large Language Model parsing
- pandas, PyMuPDF, python-docx, striprtf – Data + doc processing
🧰 Project Structure
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Payroll-LLM-Extractor/
│
├── streamlit_app.py # Main Streamlit app
├── upload_runner.py # Automates payroll CSV uploads to AW
├── upload_tax.py # Automates tax form filling on AW
│
├── src/
│ ├── send_chunk_llm.py # Gemini API integration
│ ├── excel_raw_text_chunk.py # Raw text extraction from Excel
│ └── populate_csv_template.py # Populates CSV template
│
├── utils/
│ ├── gemni_parser.py # Gemini prompt + parsing logic
│ ├── extract_rtf_pdf.py # PDF/RTF chunker
│ ├── label_analysis.py # Detects suspicious earnings
│ ├── populate_csv.py # Final CSV output generator
│
├── agent_project/
│ ├── agents.py # Playwright login + upload logic
│ └── opt.py # Browser headless setup
│
├── misc/ # Experimental scripts + prompts
├── requirements.txt
└── README.md
🧪 How It Works
- Upload a client’s payroll file (PDF, RTF, Excel).
- Extracts text chunks →
src/excel_raw_text_chunk.py - Sends chunks to Gemini →
src/send_chunk_llm.py - Post-processes earnings/deductions →
utils/label_analysis.py - Auto-fills CSV using template →
src/populate_csv_template.py - Uploads CSV and fills taxes on AW →
upload_runner.py,upload_tax.py
▶️ Streamlit Demo
1
2
3
pip install -r requirements.txt
streamlit run streamlit_app.py
Make sure you have a .env file with your Gemini API key:
1
GEMINI_API_KEY=your_gemini_key_here
AW credentials are managed securely within the agent_project/ automation scripts or set manually before automation.
💡 Created for a live payroll system in NY: 1,000+ payrolls processed, $20K+ labor saved, $2K+ new revenue.
🧭 Future Enhancements
✅ SharePoint sync for final reports
✅ AI-driven field mapping & validation
✅ Full audit trail + override logging
✅ Email notifications for payroll events
⚖️ License
MIT — free to use and modify with credit.