One accountable lead
One relationship, one lead engineer, and clear ownership from intake through resolution.
Systems Engineering for Modern Business
IT Total Service designs, secures, and automates the technology your business runs on—from identity, cloud, endpoints, and networks to custom AI agents and workflow automation.
Systems Engineering for Business
IT Total Service helps growing companies modernize the systems behind their work. We connect infrastructure, identity, devices, security, documentation, and automation into one supportable environment.
The result is fewer recurring failures, faster decisions, safer operations, and technology that can scale with the company—instead of a collection of disconnected tools and vendor handoffs.
Every engagement is led by Gary Gray, a systems engineer with more than 25 years of hands-on experience and an Engineer’s Degree in Automation and Control Systems. The work stays practical: understand the dependencies, fix the root cause, document the system, and automate what should not remain manual.
Team & Coverage
IT Total Service is a distributed engineering team led by Gary Gray. Engineers working across time zones can hand off urgent cases, so critical work does not have to wait for the next local business day.
One relationship, one lead engineer, and clear ownership from intake through resolution.
Critical cases can move between assigned engineers across time zones, including nights and weekends.
Work is documented, access is scoped to the assigned task, and escalation rules are agreed with each client.
Response times, supported systems, and escalation rules are defined in each service agreement.
Core Capabilities
Engage IT Total Service for a focused project, ongoing managed operations, or senior engineering support alongside your internal team.
Custom AI agents and AI-assisted workflows built with Claude, ChatGPT, MCP, and the tools your business already uses. Automate email, documents, knowledge work, task routing, reporting, and exception handling—with human control where it matters.
Explore AI use cases →Proactive support and administration across users, endpoints, onboarding and offboarding, Google Workspace, Microsoft 365, vendors, documentation, patching, backup validation, and day-to-day technology operations.
Discuss managed IT →Identity and access, cloud and hybrid systems, Windows and macOS fleets, servers, networks, secure remote access, cybersecurity, backup, recovery, and multi-site infrastructure engineered as one supportable system.
Explore infrastructure →AI Automation & Agents
IT Total Service designs focused agents with Claude, ChatGPT, and MCP-connected tools. They work with the systems your team already uses—email, documents, knowledge bases, calendars, cloud platforms, and service workflows—while keeping sensitive actions under human control.
Turns an overloaded inbox into an organized, reviewable workflow.
Turns scattered files and forms into usable, traceable knowledge.
Adds an intelligent first layer to internal support and operations.
Controlled by design: approved data sources, scoped access, clear review steps, and human approval before sensitive actions. Typical integrations include Claude, ChatGPT, MCP, Google Workspace, Microsoft 365, and existing business systems.
Representative Engineering Work
These solution patterns show the kind of engineering work we perform without inventing client names or unverified outcomes. Detailed case studies will be published only when the implementation and results can be documented accurately.
Design a focused agent around approved knowledge, clear permissions, connected workflow tools, human review, and traceable exceptions—so automation reduces work without creating uncontrolled risk.
Map dependencies, stabilize recurring failures, modernize identity, endpoints, cloud, networks, backup, and recovery, then document the environment so it can be operated confidently.
Standardize access, devices, connectivity, shared systems, security controls, and support procedures across locations—replacing disconnected islands with one manageable operating model.
Engineering Method
Define the business outcome, constraints, risk, urgency, and what success must look like.
Understand the systems, people, data, permissions, dependencies, and root causes involved.
Implement the solution, integrate the required tools, test recovery paths, and document the system.
Monitor what matters, refine the workflow, automate repetitive work, and plan the next priorities.
Start a Project
Describe the business problem, current environment, expected outcome, and urgency. We will recommend the right next step—an assessment, a focused project, managed IT, or an AI automation pilot.
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