Data foundations
Modernize fragmented analytics estates into governed platforms that teams can operate and extend.
Fabric / Azure / lakehouse / semantic models / deployment
Explore Fabric modernization ↗Paul Murphy / Data & AI Systems
Systems forcomplex work.
I am a Maryland-based data and AI consultant designing Microsoft Fabric analytics platforms, operational forecasting and decision systems, and governed applied AI and MCP tools for complex operations.
Analytics / AI / InfrastructureMaryland, USA
End-to-end
Direct ownership from discovery through operation
Production-first
Useful systems, not disconnected prototypes
Business-aware
Technical choices tied to decisions and economics
Low overhead
Direct collaboration without layers or handoffs
What I build
The useful work usually crosses boundaries. Data foundations, models, interfaces, and operating decisions need to agree.
Data and AI consulting built around the operating decision.
Decision systems
Turn operational complexity into forecasts, schedules, scenarios, and economic decisions.
forecasting / optimization / unit economics / Power BI
See forecasting and unit economics ↗Applied AI
Build useful agent and automation layers on top of governed data, APIs, and business logic.
agents / MCP / FastAPI / Python / identity
See governed AI and MCP ↗Selected work
Real systems I designed, built, and operated in production.
These examples show the work in action: the operating problem, the architecture behind it, my role in delivery, and what changed after it shipped.
01Production system
Commercial analytics / operations
Turning hardware complexity into profitable unit economics
A recursive bill-of-materials and planning system made processing complexity measurable, established five contract pricing tiers, and connected weekly labor to the actual work ahead.
5
agreed complexity tiers
+/-10%
typical weekly target range
4,000+
assets processed daily
300+
floor workforce at scale
02Production system
Data platform / modernization
From fragmented Azure resources to a unified Fabric platform
A full rebuild consolidated years of Azure sprawl into a governed Microsoft Fabric platform with lower cost, faster processing, and hourly operational visibility.
60%+
lower infrastructure cost
20 -> 3m
overnight batch runtime
Hourly
operational refresh
300+
users and leaders supported
03Production system
Applied AI / analytics
Turning analyst requests into governed, self-service answers
A production agent layer gave operations, HR, and sales teams direct access to governed answers and supporting data through the web and Microsoft Teams.
2
user entry points
3
operating functions served
1st pass
ad hoc analysis automated
Live
production deployment
Ask the work
The portfolio is queryable.
Ask about experience, outcomes, architecture, capabilities, or fit for your problem. Answers stay grounded in the published evidence behind this site.
Open the full assistantPortfolio assistant
Grounded / inspectableAssistant
Ask about Paul's experience, capabilities, results, or fit for a problem. I will stay focused on his published work and show the evidence used.
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Independent lab
A private Linux compute cluster, assembled from mixed hardware and driven remotely from a MacBook over Tailscale and SSH. It is a practical place to build containerized local agents outside managed cloud platforms.
Linux / Docker Compose / Ollama / Tailscale / SSH
Start with the problem