Architecting the Future of Generative AI
Advanced consulting in Natural Language Processing, Computer Vision, and Large Language Models. Led by William Foland, PhD.
About
Innovative AI and Machine Learning expert with over 20 years of experience developing cutting-edge solutions for healthcare, finance, and technology sectors.
Specializing in Natural Language Processing, Computer Vision, and GenAI applications. Skilled in rapid prototyping (PoC) and data visualization of advanced techniques.
Capabilities
Agentic AI & Orchestration
Building autonomous systems that plan and execute. Custom MCP Servers and Claude Skills for complex workflows.
- LangGraph
- MCP Servers
- Claude Skills
- LangFuse
Interactive AI Experiences
Creating low-latency, immersive learning environments using real-time video avatars and responsive voice AI.
- Video Avatars
- Real-time Audio
- Low Latency
- HeyGen / D-ID
Generative AI & LLMs
Architecting advanced RAG accelerators, fine-tuning open source foundational models, and deploying production LLM services.
- RAG
- PEFT Fine-tuning
- Synthetic Data
- Model Eval
Computer Vision & Multimodal
Real-time video analytics and object detection. Integrating vision with language models for holistic understanding.
- YOLO
- OpenCV
- PyTorch
- Multimodal RAG
Full Stack & Cloud Architecture
End-to-end system design. From modern responsive frontends to scalable backends and cloud infrastructure.
- React / Vite
- FastAPI / Node
- AWS / Azure
- Docker / K8s
Domain Expertise
Deep experience in regulatory-heavy industries (Healthcare, Finance) and complex hardware systems.
- Clinical Support
- FinTech Analysis
- Semiconductors
Track Record
Gen AI Data Scientist
Harvard Business School, Cambridge, MA
- Using realtime agents with tool calling to create new interactive experiences.
- Created Model Context Protocol (MCP) servers to provide customized tools for foundational models such as GPT5 and Claude.
- Architected cutting-edge multimodal AI teaching platform with real-time speech recognition and avatar technology for entrepreneurship education.
- Building robust technical infrastructure with WebRTC, NextJS, and FastAPI to support seamless real-time interaction.
- Leveraging Claude Code and Cursor AI to enhance development workflow and rapidly iterate on AI application implementations.
Gen AI Consultant
IsoGrab.com, Houston, TX
- Created a specialized computer vision and NLP web application that significantly reduced costs while improving technical diagram parsing accuracy.
- Architected and developed innovative multi-model agentive algorithm that autonomously adapts to diagram complexity for electrical and construction piping schematics.
- Engineered self-optimizing system with autonomous accuracy enhancement capabilities, dramatically reducing conversion time from weeks to hours.
- Implemented adaptive complexity handling for varying types of industrial diagrams, enabling scalable document processing.
Chief GenAI Data Scientist
BigRio LLC, Cambridge, MA
- Architected advanced RAG GenAI accelerator in Azure for clinical decision accuracy.
- Developed AWS GenAI service for healthcare production applications, streamlining care plan generation.
- Implemented synthetic data-based LLM performance evaluation systems.
Founder and Chief Consultant
Itinitek Ltd, Golden, CO
- Enhanced open source foundational models for legal domain using PEFT fine-tuning and RAG.
- Engineered scalable AWS pipelines utilizing LLM models and SQL for financial options analysis.
Chief Scientist
Lilac Cloud Inc, Cupertino, CA
- Embedded YOLO model in C for real-time video analytics using low-level NVIDIA GPU communication.
- Developed custom AI models using PyTorch for computer vision tasks.
- Researched and developed GAN neural networks for robust video watermarking.
Cofounder and Chief Scientist
Bolt Analytics Corp, Santa Clara, CA
- Architected time series anomaly detection using CNN, RNN, transformer, and gradient boost algorithms.
- Led team in developing automated diabetes detection from retina scans using TensorFlow.
Research & Education
Education
PhD in Computer Science
University of Colorado, Boulder, CO (2017)
Dissertation: 'Natural Language Understanding: Deep Learning for Abstract Meaning Representation'
Emphasized state-of-the-art recurrent neural networks, utilizing hardware background and the latest research approaches for AI.
MS Computer Science
University of Colorado
BS Electrical Engineering
University of Colorado
Selected Publications
- Abstract Meaning Representation Parsing using LSTM Recurrent Neural Networks, ACL Conference, 2017, Vancouver
- CU-NLP at SemEval-2016 Task 8: AMR Parsing using LSTM-based Recurrent Neural Networks, NACL Conference, 2016, San Diego
- Dependency-Based Semantic Role Labeling using Convolutional Neural Networks, NACL Conference, 2015, Denver
Foundational Engineering
Deep roots in semiconductor design and complex system architecture provide a unique advantage in optimizing modern AI workloads.
Before pioneering GenAI solutions, I spent years architecting mixed-signal integrated circuits and read channels for data storage. This foundational experience in low-level signal processing, error correction, and hardware constraints directly informs my approach to building efficient, scalable, and robust AI systems today. Understanding the "metal" makes the software faster.
U.S. Patents
...and 12 other patents in signal processing, timing recovery, and sequence detection.
Ready to Accelerate Your AI Strategy?
Available for consulting and development projects.