Regal Swiss developed sophisticated AI auditing software tailored for ongoing monitoring of tokenized investment projects on a pre-launch platform. Our solution leverages machine learning models built with TensorFlow to analyze financial data, detect anomalies, and ensure regulatory adherence. Key features include automated report generation, predictive risk scoring, and integration with blockchain ledgers for immutable audit trails. We trained models on diverse datasets covering real estate and infrastructure metrics, incorporating natural language processing for contract reviews. The system supports real-time alerts and dashboard visualizations for stakeholders. This collaborative effort, spanning requirements gathering to beta testing, equips the platform with robust tools to maintain transparency and investor trust. Ideal for tokenization marketplaces, it minimizes fraud risks, streamlines due diligence, and enhances operational efficiency for issuers managing unique Argentine opportunities.
RegisWorks
TensorFlow, Machine Learning, NLP, Blockchain integration
Pre-launch development and beta testing
Regal Swiss AI and blockchain development team
Processing vast datasets for accurate anomaly detection in audits
Ensuring AI models comply with evolving financial regulations
Integrating auditing tools with blockchain for real-time monitoring
Handling diverse project types like real estate and infrastructure
Utilized TensorFlow for custom ML models in risk prediction
Implemented regulatory APIs for dynamic compliance updates
Developed blockchain hooks for seamless data synchronization
Trained on specialized datasets for sector-specific accuracy
Detected 95% of potential risks pre-emptively in simulations
Cut auditing time by 60%, accelerating project approvals
Improved compliance scores, reducing regulatory penalties
Enhanced investor confidence with transparent audit reports