Four practices.
One integrated engagement.
Infrastructure Integration
Windows & Linux environments, M365/Azure/AWS, network hardening (TCP/IP, VPNs, VLANs), and cyber-insurance-grade security baselines — IAM, MFA, EDR, RMM, backups.
Automation & Workflows
Python, PowerShell, and Bash pipelines that replace tickets, repeat tasks, and manual reporting. Measurable hour-reductions per sprint.
Data Engineering & Analytics
SQL analytics, dashboards, and ETL pipelines with Python & Pandas that turn scattered business data into one source of truth.
AI Agents & Workflows
Agentic AI built with Claude, Grok, Ollama, Gemma, and open tooling — designed around your process, not a demo script.
How an engagement actually runs.
Discovery
One call. I learn your stack, pain points, and why nothing has changed yet.
Audit
A paid two-week audit. Findings, prioritized risks, sequenced roadmap — yours regardless.
Build
Iterative sprints. Working automation and integrations shipped weekly, not quarterly.
Handoff
Runbooks, architecture diagrams, and a Loom for every system. Your team owns it.
Project Archive
Field logs from years building real IT, data, and AI systems — each linked out to the full write-up.
Mark Marquez
Certified IT professional with a career built across IT infrastructure, cybersecurity, SaaS operations, and emerging AI tooling. Years in the weeds — supporting real users, hardening real networks, shipping automation that saved real hours.
Today I work at the intersection of classical IT and agentic AI — helping teams go from "we should automate that" to running workflows their staff actually trust. Also: neuroscience research assistant, amateur home-lab operator, perpetual tinkerer.
Start with the
AI consultation.
The chat agent in the corner scopes your problem, decides if I'm a fit, and files a lead in Salesforce so I can follow up personally. Prefer email? That works too.