Integration & platform services for mechanical engineering
I build platforms that help engineering teams deploy custom applications, connect systems and automate workflows — without rebuilding infrastructure and integrations for every project.
What I build
I connect the systems, data and software your teams rely on so applications are easier to deploy, information flows automatically, and workflows can run across tools and AI.
Replace exports and manual handoffs with direct integrations, so engineering data is available where it is needed and downstream processes can react automatically.
Coordinate tools, services and AI with scheduling, state and orchestration, so multi-step engineering workflows run reliably without people moving every step forward.
Give teams a repeatable, secure way to move custom applications into production without solving authentication, networking, databases and deployment from scratch every time.
About Kevin
My background spans mechanical engineering, industrial product development, cloud platforms, data systems and AI. I work across the engineering workflow and the software architecture required to connect it.
More about my backgroundInsights
Engineering Data
Most industrial companies have vast amounts of engineering data, yet AI initiatives still struggle to use it. The problem is not a lack of data. It is that essential product information remains trapped in systems, files and departmental workflows.
AI Agents in Product Engineering
Many agentic AI initiatives become brittle because agents are asked to infer business rules, move information between documents and hold incomplete workflows together. Reliable agents need dependable software capabilities beneath them.
AI-Ready Product Engineering
AI readiness is not a question of how many tools an engineering organization has adopted. It is the ability to connect people, workflows, systems and data so that AI can improve how products are developed at scale.
Engineering Operating Model
Central IT cannot build every specialized engineering solution, but unmanaged local development creates more fragmentation. AI-ready organizations replace this false choice with shared platforms, clear guardrails and ownership inside engineering domains.
AI Transformation in Product Engineering
Product engineering organizations can have more copilots, agents and successful pilots without achieving faster development or lasting operational change. The gap is created by missing foundations, not insufficient AI activity.
AI Transformation in Product Engineering
AI initiatives in product engineering rarely fail because of the technology. They fail because engineering organizations weren't designed for humans and AI to work together. This article explores the root causes and the organizational capabilities required to scale AI successfully.
If engineering data, tools or applications aren't working together the way they should, tell me what you're trying to connect.