AI and Data Consulting Services
After 20+ years building data systems and leading engineering teams, I founded PragmaNexus to help organizations make practical use of their data. My experience spans both traditional machine learning and newer large language models, allowing me to recommend the right approach for each specific business problem.
Practical Experience with Both Approaches
What guides my work is a straightforward principle: use the right tool for the job. Sometimes that's a traditional ML model with clear, interpretable outputs. Other times it's an LLM that can process unstructured data or natural language. Often, it's a combination of both approaches working together to solve different parts of a complex problem.
I've built production machine learning systems for predictive modeling, classification, and recommendation engines. My experience includes designing data pipelines, feature engineering, and developing models that deliver reliable, transparent results at scale.
I build effective LLM systems that integrate with existing infrastructure, focus on accuracy, and deliver reliable results. My implementations address common challenges like data security, reducing hallucinations, and optimizing for both performance and cost.
Services I Offer
- Practical AI Strategy — Developing roadmaps that use both traditional ML and LLMs to address your specific business challenges
- LLM Engineering — Building reliable AI systems that deliver accurate results, integrate with your existing tools, and address practical concerns like security and cost
- Data Infrastructure — Building scalable data platforms that provide the foundation for both analytics and AI applications
- Technical Evaluation — Assessing which approaches will work best for your specific requirements and constraints
- Team Development — Helping your team build the skills to maintain and extend these systems
My background spans different industries—from quantitative finance to consumer analytics to small business operations. This breadth of experience helps me quickly understand your domain and business objectives when designing technical solutions.
I believe the most important question isn't "Which AI technology should we use?" but rather "What actual business problems are we trying to solve?" This product-first mindset means I start by understanding the real issues affecting your business, your users, and your bottom line.
Only after clarifying the core problems do we discuss potential solutions—whether that involves machine learning, LLMs, or simpler approaches. The technologies are just tools; what matters is addressing the problems that genuinely impact your business outcomes.
This approach has consistently led to more focused, practical solutions that deliver real value rather than chasing the latest technology trends. It's about building something that works for your specific context, solves actual problems, and creates measurable business impact.