Inspiration
As a finance professional, I saw SMEs struggle with audit prep—hours of manual data wrangling, missed discrepancies, and sky-high accountant fees. I wanted to build a tool that levels the playing field, making audit prep efficient and affordable for startups and small businesses.
What it does
AuditBot unifies financial data from QuickBooks/Xero/banks, auto-detects errors (prioritized by impact), generates auditor-compliant reports, tracks document collection, and visualizes audit trails—slashing prep time and reducing accountant costs by up to 40%.
How we built it
We started with core data sync logic (Python/Pandas) to connect financial APIs, then built a React frontend for the dashboard. AWS hosted the backend; PostgreSQL stored transaction data; TensorFlow powered AI discrepancy detection. We iterated with SME finance teams to refine workflows.
Challenges we ran into
API rate limits caused sync delays; AI struggled with edge-case discrepancy categorization; ensuring report compliance with regional audit standards took rigorous testing. We resolved sync issues with queuing logic and trained the AI on 1000+ real audit scenarios.
Accomplishments that we're proud of
Our AI flags 90% of actual financial inconsistencies; reports generate in <10 seconds; users cut audit prep time by 60% on average. The tool now supports 3 major financial platforms and scales for SMEs of all sizes.
What we learned
We mastered balancing real-time data sync with compliance; learned to prioritize user workflows over technical complexity; and discovered how critical iterative feedback from end-users (small business owners) is to product fit.
What's next for this project
We’ll add more accounting platform integrations, build role-based access for teams, and pilot a mobile web version. We also plan to integrate predictive analytics to flag potential discrepancies before they impact audits.
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