Enterprise AI,
engineered for reality.

Leading enterprise Generative AI architecture for multimodal loan document intelligence and borrower servicing automation.

• Reduced manual document review time by 43.2% across 1.4M+ annual documents.
• Sustained zero downtime across more than 2.1M monthly inference requests on AWS EKS.
• Established continuous LangSmith and LLM-as-a-Judge evaluation to reduce flagged hallucinations by 19.4%.

Engineered a Google Cloud agentic AI platform supporting real-time member advocate workflows and governed healthcare retrieval.

• Deployed hierarchical agent orchestration to 18,400+ active advocates.
• Raised Medicare eligibility retrieval accuracy by 42.7% while reaching sub-850ms latency.
• Maintained 99.95% uptime across more than 1.2M daily AI API requests.

Built explainable credit-risk models and distributed transactional pipelines for an institutional debt marketplace.

• Delivered 99.88% validation accuracy with XGBoost and LightGBM risk models.
• Implemented SHAP explanations that supported production approval with zero Q2 compliance violations.
• Reduced reconciliation latency from 45.3 minutes to 9.2 minutes with Kafka and Snowflake.

Modernized predictive analytics and distributed data platforms for retail and financial clients.

• Cut daily batch processing from 52 to 14 minutes across 34.7M daily events.
• Improved fraud true-positive detection by 19.2% using real-time anomaly models.
• Reduced multi-cloud deployment time by 35% through Docker and GitHub Actions.

Developed physiological signal-processing and predictive-health systems for contactless patient monitoring.

• Reached 94.6% classification accuracy for respiratory anomalies with 1D-CNN and LSTM models.
• Predicted clinical deterioration trends an average of 4.2 hours before visible onset.
• Sustained sub-240ms processing latency in auto-scaling AWS services.