Production systems built for Fortune 500 and enterprise clients. Each project follows the same arc: understand the business problem, design the architecture, build the system, prove the ROI.
Thousands of invoices processed manually each month across multiple vendor accounts. High error rates, slow turnaround, and no integration with the existing SAP ERP system.
Built a deep learning field extraction pipeline in Python that reads, classifies, and routes invoices automatically. Integrated directly with SAP via F3041 template generation for seamless ERP ingestion.
Franchise locations relied on manual stock counts with high error rates. No real-time visibility into inventory levels, leading to stockouts and over-ordering across locations.
Engineered a computer vision system using PyTorch for barcode scanning and product detection. Deployed on AWS with real-time tracking dashboards and automated threshold alerts.
Client acquisition relied on manual outreach with no systematic qualification process. High cost per lead, low conversion rates, and no pipeline visibility for leadership.
Built 120+ targeted landing pages with AI voice agent qualification. Automated lead scoring, CRM pipeline integration, and follow-up sequencing across multiple channels.
Multiple disconnected tools, dashboards, and automation workflows running across different platforms with no unified orchestration, monitoring, or deployment strategy.
Designed and deployed a unified cloud architecture spanning 55 services on Azure and AWS — dashboards, AI agents, and automation workflows orchestrated through a central control plane.
Off-the-shelf language models lacked domain-specific knowledge for specialized business operations. Generic outputs required heavy human review and correction.
Curated 5,600+ domain-specific training examples. Fine-tuned using PyTorch and TensorFlow with systematic evaluation benchmarks to measure improvement over baseline.
12 vendor accounts across 5 currencies (USD, CAD, EUR, GBP, MXN) with no automated routing, duplicate detection, or NTE enforcement. Manual approval chains created bottlenecks.
Developed a 5-tier approval workflow with document fingerprinting for duplicate detection, automated GL code routing, NTE enforcement, and full audit trail for compliance.
Commercial real estate deal flow relied on manual market analysis, hand-built offering memorandums taking weeks per deal, and error-prone DST/1031 exchange document preparation with no automated compliance checks across niche commercial markets.
Built end-to-end deal automation: AI-powered comparative market analysis pulling from private data sources and all public records for niche commercial segments, automated OM generation from property data and financials, and programmatic DST/1031 document stack creation with QI coordination and compliance-ready closing packages. Integrated fund raising workflows with LP/GP reporting and automated fund administration.
Family neurology practice hitting growth ceiling — inefficient scheduling, billing bottlenecks, and no data-driven decision-making for capacity planning.
Technology-first operational redesign covering scheduling optimization, billing workflow automation, analytics dashboards, and staffing capacity models.