Engineering AI Systems That Make Decisions, Not Just Predictions.
I design and deploy intelligent automation systems that replace manual decision layers, transform unstructured data into action, and deliver measurable operational impact for enterprise workflows.
Expertise
I build AI systems that sit at the intersection of machine intelligence and business operations — where decisions happen.
AI Automation Architecture
End-to-end design of autonomous AI workflows that replace manual decision layers and scale operations without linear headcount growth.
Intelligent Document Processing
Extract structured intelligence from complex documents — PDFs, reports, medical records, legal filings — using OCR, NLP, and LLM pipelines.
Decision Support Systems
AI-powered platforms that analyze data, surface insights, and produce actionable recommendations — turning information overload into clarity.
Voice AI Systems
Conversational AI agents for real-time voice interactions — automating negotiations, dispatch coordination, and customer engagement at scale.
Applied LLM Engineering
Production-grade implementation of large language models — RAG architectures, fine-tuning, prompt engineering, and knowledge-grounded agents.
Workflow Transformation
Re-engineering business processes with AI-driven automation — from intake to decision to output — reducing friction and accelerating outcomes.
Case Studies
Real-world AI systems I've designed and deployed — each solving specific business problems with measurable outcomes.
Healthcare AI Referral Decisioning Agent
Automated patient acceptance workflows for Skilled Nursing Facilities — turning complex clinical documents into instant YES/NO decisions.
Problem
Skilled Nursing Facilities received hundreds of patient referral documents daily — each requiring manual extraction of SSN, DOB, clinical data, and cross-referencing against facility criteria. The process was slow, error-prone, and created staffing bottlenecks.
AI Approach
Built an AI agent that automatically ingests referral PDFs, extracts structured patient data using OCR and NLP, matches criteria against configurable facility rules, and produces instant acceptance decisions with clinical summaries.
Business Impact
Reduced manual review time by over 80%. Enabled facilities to process referrals in minutes instead of hours. Eliminated human error in data extraction and improved patient throughput.
Outcome
Deployed across multiple facilities — processing hundreds of referrals daily with consistent accuracy and generating detailed audit trails for compliance.
Voice AI Truck Dispatch Negotiation System
AI voice agents that handle dispatch call negotiations autonomously — scaling logistics coordination without human bottlenecks.
Problem
Logistics companies spent significant human hours on repetitive dispatch call negotiations — coordinating loads, negotiating rates, and confirming schedules. Scaling required proportional headcount growth.
AI Approach
Designed conversational AI voice agents capable of conducting real-time dispatch negotiations. The system understands context, negotiates within predefined parameters, and escalates edge cases to human operators.
Business Impact
Automated 70%+ of routine dispatch calls. Reduced average call handling time and enabled operators to focus on high-value exceptions rather than repetitive coordination.
Outcome
Scalable voice AI infrastructure handling concurrent negotiations — delivering consistent communication quality regardless of volume.
Legal AI Case Intelligence Platform
AI-powered system analyzing historical legal cases to deliver summaries and strategic insights for litigation preparation.
Problem
Lawyers spent extensive time manually reviewing case law databases to find relevant precedents and build arguments. The process was time-intensive and limited by individual research capacity.
AI Approach
Built a RAG-powered intelligence platform that ingests legal case databases, indexes them semantically, and allows lawyers to query for relevant precedents with AI-generated summaries and strategic argument suggestions.
Business Impact
Compressed case research from days to minutes. Lawyers discovered relevant precedents they would have otherwise missed, strengthening case arguments significantly.
Outcome
Active platform serving legal teams — continuously indexing new case law and improving recommendation quality through feedback loops.
NI 43-101 Document Extraction Pipeline
Automated extraction of structured financial intelligence from complex mining investment reports.
Problem
Mining investment analysts manually reviewed dense NI 43-101 technical reports — hundreds of pages each — to extract financial metrics, resource estimates, and risk assessments. The process took weeks per report.
AI Approach
Developed an automated pipeline that processes NI 43-101 PDFs, identifies key sections, extracts structured financial data, resource estimates, and compliance indicators, and outputs investor-ready summaries.
Business Impact
Reduced report analysis time from weeks to hours. Enabled investment teams to evaluate more opportunities with greater accuracy and consistency.
Outcome
Production pipeline processing complex mining reports — delivering structured datasets that feed directly into investment decision workflows.
Enterprise Document Automation Systems
Converting unstructured business documents into structured datasets to automate high-volume operational workflows.
Problem
Enterprises dealt with massive volumes of unstructured documents — invoices, contracts, reports — requiring manual data entry and classification. This created operational drag and escalating labor costs.
AI Approach
Built intelligent document processing systems that classify documents, extract key fields, validate data against business rules, and route structured outputs to downstream systems — all with minimal human intervention.
Business Impact
Eliminated manual data entry for high-volume document flows. Achieved 95%+ extraction accuracy and reduced processing costs by over 60%.
Outcome
Deployed across enterprise operations — handling thousands of documents daily with continuous accuracy monitoring and exception management.
"Reply Agent" – AI Customer Support Agent
Custom knowledge-based AI assistant delivering context-aware responses trained on proprietary business data.
Problem
Customer support teams were overwhelmed with repetitive queries. Response quality was inconsistent, training new agents was costly, and institutional knowledge was siloed across team members.
AI Approach
Built a knowledge-grounded AI assistant that indexes proprietary documentation, FAQs, and historical ticket data to deliver accurate, context-aware responses — with confidence scoring and human escalation for edge cases.
Business Impact
Reduced support ticket volume by 40%+. Improved first-response accuracy and consistency. Freed human agents to focus on complex, high-value interactions.
Outcome
Production AI support agent handling the majority of incoming queries — continuously learning from new data and maintaining response quality above human baseline.
How I Work
A structured approach to deploying AI that delivers production-grade reliability from day one.
Understand Business Bottlenecks
Deep dive into existing workflows to identify where manual decisions, repetitive tasks, and data friction create operational drag.
Map Decision Logic
Document the rules, edge cases, and judgment criteria that drive current decisions — creating a blueprint for AI automation.
Design AI Workflow
Architect an intelligent system that mirrors human decision quality while operating at machine speed and scale.
Deploy Human-in-the-Loop
Launch with smart escalation paths — AI handles the routine, humans manage the exceptions. Builds trust while delivering value immediately.
Optimize for Reliability
Continuously monitor, measure, and improve. Track accuracy, latency, and business outcomes to compound ROI over time.
Technology Stack
Production-grade tools and frameworks I use to build reliable AI systems at scale.
AI & ML
Engineering
Data & Processing
Infrastructure
Specialized
Industries Served
Deploying AI solutions where precision, compliance, and operational efficiency matter most.
Healthcare
Patient referral automation, clinical data extraction, and care coordination intelligence.
Legal
Case law analysis, precedent intelligence, and litigation support powered by AI.
Logistics
Dispatch negotiation automation, route optimization, and operational coordination.
Investment Analysis
Technical document extraction, financial intelligence, and investor decision support.
Enterprise Operations
Document automation, workflow transformation, and process intelligence at scale.
Let's Build AI That Actually Gets Used.
I work with teams that have real operational problems and want production-grade AI solutions — not prototypes that sit on a shelf. If you're ready to automate decision-making, let's talk.