I founded Rock Valley Tech with one clear mission: to eliminate the uncertainty that holds businesses back—whether you’re managing a busy home services operation, leading a construction company, or scaling a tech startup. I design streamlined solutions that unify your systems, automate routine tasks, and turn complexity into clarity.
From cloud infrastructure and automation to AI and data engineering, I make sure everything runs smoothly—without the usual headaches, and unlike traditional consulting firms that charge by the hour or delay projects, I offer predictable, subscription-based services. This way, you know exactly what you’re getting: reliable solutions, expert execution, and no surprises.
AI is good at generating work and helping people move faster. It should not be responsible for remembering every rule that keeps the business working. If a decision can be enforced mechanically, move it into the system.
Talk to BrianI’ve spent my career at the intersection of tech, finance, and entrepreneurship. I’ve led cloud transformations, built enterprise-grade data pipelines, and scaled infrastructure for high-growth companies. Before that, I worked in sales, project finance, and investment banking, which means I understand technology and the bottom line.
Over the years, I've helped businesses of all sizes by:
I believe in certainty and commitment. My clients trust me because I don’t just deliver projects—I invest in long-term partnerships. Your customers become my customers, and I approach every engagement as if your business success is my own.
At Rock Valley Tech, I cut through complexity, bring deep expertise, and deliver solutions that just work—whether you’re a tech team in need of advanced cloud architecture or a non-tech business owner looking to streamline operations. This allows you to focus on innovation, not infrastructure.
No. Plenty of work is better handled by a clean workflow, an integration, or a scheduled job. AI belongs where interpretation, drafting, classification, or judgment actually adds value.
No. I work with technical teams on AI engineering controls, DevOps, AWS, and infrastructure, and with small businesses on systems, automation, data, AI training, and practical AI integration.
A concrete weak point: unreliable agent changes, disconnected systems, duplicate entry, weak CI gates, or a process that depends on somebody remembering what to do.
As far outside the model as practical. Branch protections in source control, test requirements in CI, infrastructure rules in policy and code, business rules in workflows and permissions, failures in monitoring.
Yes. AWS infrastructure, Terraform, CI/CD, monitoring, security, data pipelines, automation, and platform engineering are still core parts of the work.
Yes. The work should live inside the repositories, systems, cloud accounts, and operating practices the team already uses instead of creating a separate AI process off to the side.
Both. A focused infrastructure, automation, AI-control, or business-systems problem may have a clear endpoint. Ongoing work makes sense when the systems and workflows continue to change.
When agents are producing meaningful code and the team is relying on review, prompts, documentation, or convention to keep changes safe. At that point the checking should be done by the system, not by the agent.
If AI is outrunning your team, or too much still lives in someone's head, let's talk.
Talk to Brian