About TitanStack AI

01 · About

AI strategy, built around how your business runs.

TitanStack helps companies assess where AI fits, train teams to use it, and implement systems around the work that matters.

02 · Leadership

Operators and engineers, at the same table.

AI strategy breaks when business context and technical delivery live in separate rooms. TitanStack brings both into every decision.

Founder

Ben McCarron

Ben is an operations leader who builds AI around how businesses actually run. Before founding TitanStack AI, he served as Director of Operations at a performance media company, working across reporting, process design, data quality, and day-to-day delivery.

Today, he leads strategy and delivery across custom AI agents, workflow automation, reporting, and data operations. He focuses on production systems that reduce manual work, improve decision-making, and give teams clearer control of their operations.

Email Ben LinkedIn Book a strategy call

Chief Technology Officer

Alan Nguyen

Alan is a full-stack engineer and technical leader with more than 12 years of experience building and scaling products from early-stage startups to enterprise systems. He has served as a fractional CTO, led distributed engineering teams, and owned architecture across application, infrastructure, and data layers.

At TitanStack, Alan leads technical strategy and system architecture across AI agents, workflow automation, data platforms, and production integrations. His work spans cloud infrastructure, distributed systems, APIs, and large-scale SaaS, with an emphasis on reliability, security, and systems teams can maintain.

03 · How we help

From AI interest to practical implementation.

Most companies already have access to AI. What they lack is a clear view of where it fits, what the team should learn, and which workflows are worth changing first.

We start by assessing leadership priorities, team readiness, tools, and day-to-day workflows. That turns broad AI interest into a practical set of opportunities the business can evaluate.

From there, we prioritize the highest-value use cases, train the people who will use them, and build a 90-day roadmap. If the priorities make sense, we help implement the assistants, automations, dashboards, and operating workflows behind it.

Every engagement is tied to an operating outcome: faster decisions, lower cost, cleaner data, stronger internal capability, or less manual work.

04 · How we operate

Built for outcomes. Designed for control.

A disciplined operating model for turning AI opportunities into systems the business can trust, use, and extend.

Security-firstROI-drivenBuilt around you

Outcome-Driven

Every system ties to a real metric: revenue, cost, speed, or risk.

Built to Scale

Standardized frameworks that extend across teams, sites, and workflows.

Structured & Verifiable

Evidence-backed analysis, cross-validated data, no black-box outputs.

Built for Control

Secure, documented systems your team and partners can rely on.

Work with us.

Work with us