Find Where AI Fits.
Build for Impact.
Embedded technical partner for teams in regulated, high-stakes domains. From understanding the problem to shipping production systems.
What I Do
The work starts with your problem. AI can do things that weren't possible before, but the key is knowing what's actually worth building. I embed with teams to figure that out and then build it — agentic workflows, data infrastructure, ML models, dashboards, document generation — in domains like investment research, healthcare regulatory, and logistics.
20+ years building software and a decade focused on ML and AI. I design for the team you actually have and build systems your team can run and extend after I leave.
My Approach
The name PragmaNexus reflects how I work. Two principles shape every engagement:
- Pragmatic: Problem first. Right tool for the job. Integrate with what exists.
- Nexus: Connect AI capabilities to domain knowledge and existing processes. Accelerate the people who already know their domain.
These principles hold from first conversation through production deployment.
How I Work
Ongoing technical partnership
I work as an ongoing technical partner. Sometimes that means working alongside your engineering team. Sometimes it means I'm the one building it. Either way, I stay in the work until it's in production and your team can own it.
Understand
Learn your domain, team, and systems. Identify where AI fits.
Build and Iterate
Working prototypes fast. Iterate based on real feedback until it works in your actual environment.
Ship and Transfer
Deploy to production, document, and ensure your team can maintain and extend the work. I design for your actual team capabilities.
Recent domains: Investment research tools, healthcare regulatory document generation, logistics ML, clinical AI systems
What I Build
Production AI systems as an embedded technical partner. Assessment and training for teams getting started.
Embedded AI Engineering
I work as your technical partner — whether that means joining an existing engineering team or being the builder for a team that has deep domain expertise but no AI capacity. I figure out what to build, build it, and make sure you can own it when I'm done.
- Agentic workflows and multi-step AI pipelines
- Data infrastructure and ML model deployment
- Testing and evaluation infrastructure
- Custom dashboards and internal tools
- AI integration into existing processes
- Team coaching on AI-assisted development
AI Opportunity Assessment
Not sure where AI fits? I evaluate your workflows, identify practical opportunities, and give you an honest assessment of what will and won't work. Standalone engagement or entry point to embedded work.
- Evaluate existing workflows for practical AI applications
- Identify high-impact use cases based on real implementation experience
- Develop pragmatic roadmaps aligned with your team's capabilities
AI Implementation Training
Train your engineers on LLM integration patterns that work in production. Workshops, code review, and ongoing support drawn from 20+ years building production systems.
- Hands-on workshops on reliable LLM integration patterns
- Production lessons from real AI system deployments
- Ongoing guidance on AI technology choices and evaluation strategies
Current Thinking
What I'm learning as I build
Common Questions
What people ask when they're considering working together
How is this different from hiring an AI consulting firm?
I embed with your team. I write code in your codebase, attend your meetings, and ship production systems. I stay until the work is done and your team can own it.
We're not sure if AI is the right solution.
I'll tell you honestly if it's not. I have no incentive to oversell — my reputation depends on building things that actually work. Not every problem needs AI, and I'll say so when that's the case.
What kinds of AI systems do you typically build?
Agentic workflows, research tools, ML models, dashboards, document generation systems, and testing infrastructure. The common thread is production systems in regulated or high-stakes environments where reliability matters.
What does the engagement look like in practice?
Ongoing retainer. I work in your tools, join your meetings when it makes sense, and ship production code. Some teams have engineers I work alongside; others need me to be the builder.
About Me
Matt Stockton — 20+ years building software systems across finance, healthcare, logistics, and consumer brands. I've built quantitative investment algorithms at hedge funds, ML platforms at venture-backed startups, and data systems that handle millions of transactions.
Today I work as an embedded technical partner through PragmaNexus. I help teams figure out where AI fits their work, then I build it — writing code, shipping features, iterating until it works. I work daily at the leading edge of AI tooling and write regularly about what I learn.
I write about the work at mattstockton.com.
Get in Touch
Tell me what you are working on
Prefer to use your own email client? Reach out directly:
[email protected]Tell me what problem you are solving. I'll be direct about whether I can help.