Ai invoices

Inspiration

Manual invoice processing creates delays, payment errors, and financial risks for businesses when exceptions occurs. We built this AI assistant to automate exception detection and streamline resolution workflows.

What it does

Our AI-Powered Invoice Exception Resolution Assistant extracts invoice data, validates details against supporting documents (PO/contracts), detects discrepancies (like amount mismatches or missing info), and presents actionable insights for human review.

How we built it

• Python: Core logic and validation engine
• PyMuPDF: Document parsing and text extraction from invoices
• Gemini API: AI-powered document analysis and exception detection
• Pydantic: Data validation and structured output formatting
• Streamlit: Interactive user dashboard for review

Challenges we ran into

Extracting key details accurately from unformatted or noisy invoice PDFs was challenging. We also had to structure complex validation rules to detect mismatch exceptions efficiently using LLM outputs.

Accomplishments that we're proud of

Built an automated AI pipeline that accurately identifies invoice exceptions and provides clear human-in-the-loop audit insights on an interactive dashboard.

What we learned

Learned how to effectively prompt Gemini API for structured JSON extraction using Pydantic schemas, and built smooth interactive UI components with Streamlit.

What's next for Ai invoices

Integrating real-time ERP/accounting software integration (like SAP/QuickBooks), expanding fraud signal detection, and adding automated email notifications for vendors.

Built With

• artificial-intelligence
• automation
• data-extraction
• data-validation
• exception-handling
• finance-tech
• fintech
• gemini-api
• invoice-processing
• llm
• machine-learning
• ocr
• optical-character-recognition
• pardot-marketing-automation
• pdf-parser
• prompt-engineering
• pydantic
• pymupdf
• python
• rtckit
• smart-contracts
• streamlit
• three.js
• workflow-automation