Inspiration

Manual invoice processing is slow, expensive, and vulnerable to fraud. Existing AI systems often automate approvals without verifying their own reasoning, creating risks for financial teams. We wanted to build an AI system that could not only process invoices but also audit itself.

What it does

PlutusAudit AI uses five specialized AI agents to automate invoice auditing:

• Extracts invoice data from PDFs/images using multimodal AI
• Validates accounting logic with GAAP/IFRS knowledge retrieval
• Detects fraud patterns using financial signals
• Verifies AI decisions through independent checks
• Generates explanations and tamper-proof audit trails

It reduces invoice processing from days to seconds while improving accuracy and trust.

How we built it

We built a multi-agent pipeline combining:

• Gemini 2.5 Flash for document intelligence
• FAISS + BM25 hybrid retrieval for accounting standards
• Qwen3-32B for fraud risk scoring
• PostgreSQL with SHA-256 hash chaining for audit logs
• Automated verification loops for AI reliability

Challenges we ran into

The biggest challenges were ensuring AI-generated accounting decisions were accurate, preventing hallucinated reasoning, handling diverse invoice formats, and creating a system that could detect its own mistakes.

Accomplishments that we're proud of

• Achieved 57% touchless invoice processing
• Reduced processing time to around 45 seconds
• Reduced cost per invoice significantly
• Built an AI auditor capable of detecting fraud before payment
• Created a self-verifying financial AI workflow

What we learned

We learned that enterprise AI requires more than just powerful models. Reliability, verification, explainability, and auditability are essential when AI handles financial decisions.

What's next for PlutusAudit AI

We plan to expand accounting coverage, improve fraud detection models, integrate with enterprise finance systems, and build a fully autonomous AI finance operations platform.

Built With

• gemini
• vultr