Andrew Lawlor is an entrepreneur, AI strategist, and technology leader with more than two decades of experience guiding enterprises and nonprofits through complex digital transformation. As Founder and CEO of Aptaria, he helps organizations design and deploy production-grade AI systems — agentic automation, private model deployment, and AI architected around the systems they already run.
What sets his approach apart is the combination of frontier AI expertise with nearly two decades of hands-on enterprise delivery. Andrew pairs current, technical AI depth — including graduate-level work in agentic systems, natural language processing, and computer vision at Stanford — with a long track record architecting and integrating the mission-critical systems that large organizations depend on. It’s a rare blend: the ability to build AI that is genuinely advanced and that works reliably inside a real business from day one.
Trained as an electrical engineer, Andrew brings an engineer’s rigor to AI — grounding new capabilities in the fundamentals of how systems actually behave. Over his career he has led successful implementations for organizations of every size, bridging strategic vision and real-world execution, from cloud-native architecture to intelligent automation to AI-driven analysis.
Andrew founded Aptaria in 2002 and built it into a trusted Salesforce Partner before leading its pivot into enterprise AI consulting — a move grounded in the conviction that the hardest part of AI isn’t the model, but making it deliver measurable impact inside the enterprise.
Areas of focus: Agentic AI systems, machine learning and deep learning, private/open-weight model deployment, RAG systems, enterprise AI integration, and AI strategy — built on deep expertise in AI, CRM/Salesforce, AWS, Google Cloud, and enterprise architecture.
Education & Certifications
-
Stanford University (In Progress – Expected Autumn 2026): Graduate Certificate in Artificial Intelligence.
-
-
Notable Coursework:
- CS231N: Deep Learning for Computer Vision (Spring 2026, Grade: A), covering visual recognition, Convolutional Neural Nets, Vision Transformers, generative models, and multi-modal models.
-
-
-
- CS224N: Natural Language Processing with Deep Learning (Winter 2026, Grade: A-), covering foundational NLP principles, neural sequence models, transformers, and large-scale language modeling.
-
CS221: Artificial Intelligence: Principles and Techniques (Autumn 2025, Grade: A-), covering foundational AI principles including machine learning, probabilistic graphical models, and logic-based systems.
-
-
Columbia University: Graduate work in Electrical Engineering and Computer Science.
-
University of Maryland, College Park: Bachelor of Science in Electrical Engineering.
Andrew lives in McLean, Virginia, with his wife, daughter, and son. When not working, he enjoys playing and watching basketball and playing poker.
 