I build AI-powered enterprise applications that connect construction data, project controls, financial information, risk, schedules, and operational knowledge into intelligent tools that help people understand what is happening across a project.
My approach to AI is practical: start with the systems and information that already drive the organization, then use AI to make that information easier to understand, search, analyze, and act upon.
In the construction environment, that means combining project controls, financial data, schedules, risk, closeout, commissioning, contacts, documents, and operational updates with modern generative AI and semantic search.
The result is not simply a chatbot. It is an intelligent application layer built around the project's existing data and business processes.
The architecture brings together application services, construction data, semantic search, generative AI, and project-specific business logic.
Project controls, eBuilder data, SQL Server, project milestones, financial information, risk, closeout, commissioning, contacts, weekly updates, and operational records.
ASP.NET Core, C#, MVC, APIs, application services, role-based security, project-specific business rules, and data-processing services.
Google Gemini, generative AI, embeddings, semantic similarity, contextual retrieval, project analysis, and AI-assisted responses.
Intelligent dashboards, AI chat, project analysis, searchable knowledge, data grids, alerts, and workflow-oriented interfaces.
AI services built with Google's Gemini platform and integrated directly into enterprise applications.
Construction information can be searched by meaning, not just by exact keywords.
AI can analyze project information in context rather than treating each database record as an isolated item.
Conversational interfaces allow users to ask questions about projects using natural language.
AI capabilities are integrated into production enterprise applications rather than existing as disconnected experiments.
AI becomes significantly more useful when it is connected to reliable project and enterprise data.
Cloud infrastructure provides the foundation for scalable enterprise applications and AI services.
Technology is most valuable when it improves the way people actually manage and deliver construction projects.
An AI assistant can identify a project from a natural-language question, retrieve relevant project information, analyze milestones and risk, and return the result through a conversational interface.
Instead of forcing a project manager to search through multiple screens and reports, the application can bring the relevant information together and explain what requires attention.
The goal is to make complex construction information understandable, accessible, and actionable — while preserving the systems, data, and workflows that organizations already depend on.