Technology
Commercialization
I turn complex technology into products, narratives, and use cases people can understand, adopt, and buy.
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Common
Questions
Explore the questions people usually ask when technology, product, and commercialization need to come together.
Most organizations
struggle to connect technology to a decision.
Noise
Teams want the latest technology because the market talks about it.
Clarity
Does it solve a problem that matters to a specific user?
Adoption
Use cases need a defendable value story before the category becomes obvious.
"Technology FOMO is not a strategy. AI creates attention, but use cases create adoption."
Carlos Pazos
I combine engineering depth, data science practice, product strategy, and technology commercialization experience across global corporations and startups.
Trained as a mechatronics engineer, I developed a data science specialty and completed a master's in technology commercialization at UT Austin. I have worked at National Instruments, Honeywell, Siemens, SparkCognition, and SAIVA — across Mexico, the United States, Germany, and Spain.
- Technology commercialization and use-case strategy
- AI-enabled product launches and adoption programs
- Technical-to-business translation for complex products
- Building X software at Siemens
Selected
Work
A record of product launches, emerging technology categories, and commercialization.
LabVIEW and developer adoption
I worked across LabVIEW launches at National Instruments, including leading LabVIEW 2014 and contributing heavily to LabVIEW NXG. The work required understanding developer expectations, installed-base behavior, and the challenge of introducing new product experiences without losing trust.
OPC UA and industrial standards
I led the process to secure CXO approval for OPC UA support in LabVIEW and represented National Instruments at the OPC Foundation. The work was about recognizing an emerging industrial standard early and translating its strategic relevance into internal alignment and product action.
Darwin AutoML
At SparkCognition, I led the launch of Darwin as both SDK and app. AutoML was still an emerging category, so the commercialization challenge was positioning it as a productivity accelerator for data scientists and ML engineers, not a replacement for their expertise.
Honeywell Forge and honeywellforge.ai
At Honeywell, I worked on Honeywell Forge launches across Industrials and Buildings and led the end-to-end launch of honeywellforge.ai. That work required coordination across product, IT, executive leadership, vendors, and launch stakeholders, including direct executive reporting on launch status.
AI-enabled player development
At SAIVA, I led a data science team working on an ML-based football product that transforms a single broadcast video into a high-fidelity 3D scene for professional player development. This combined AI, data science, product thinking, and business development in a startup environment.
Building X software launches
At Siemens, I lead product marketing for software launches across Building X applications. The work is about keeping field sellers current, equipped, and confident as product capabilities evolve quickly.
Robotics education startup in Mexico
Earlier in my career, I was part of a Mexico-based startup focused on teaching robotics to kids. That experience reinforced my interest in technology education, entrepreneurship, and making technical concepts accessible to new audiences.
How I Work
The principles that guide how I translate technology into adoption.
Start with the pain
I try to understand the user's reality before shaping the product story. If the pain is not clear, the value will not be clear either.
Separate buzzword from value
I do not treat AI, platforms, automation, or analytics as value by themselves. I look for the use case that makes the technology worth adopting.
Make ROI explainable
Emerging technology needs a value story that leaders can understand, defend, and act on, even before the category is fully mature.
Build adoption paths
A strong launch is not just an announcement. It is the alignment of product, marketing, sales, field readiness, and customer understanding.
Stay hands-on
I stay close to the technology by coding, experimenting, and learning directly. That makes the business translation more credible.
Lead with controlled chaos
I enjoy fast innovation cycles, but they work best when they converge toward a milestone that matters.
Mentor through building
I enjoy mentoring when the learning is practical. Through Technovation Girls, I helped a junior team learn to code, build an app, and think about commercialization and entrepreneurship.
Credentials and Signals
A technical and business foundation shaped by engineering, data science, commercialization, international work, corporate scale, and startup execution.
- Mechatronics Engineering — ITESM CCM
- Data Science specialty — Georgia Tech
- Master's in Technology Commercialization — The University of Texas at Austin
- National Instruments, Honeywell, Siemens, SparkCognition / Avathon, SAIVA, and robotics education
- Work across Mexico, the United States, Germany, and Spain
- Older publications and writing on AI, IoT, and production operations
- Mentorship through Technovation Girls
- Hands-on coding and data science practice
- Leadership across digital marketing, AI/data science, and product marketing teams
Start a Useful Conversation
Build or commercialize a technology-enabled product
For founders, builders, or teams trying to connect a technical capability to a market problem.
Translate technical complexity into a market story
For teams that need sharper positioning, launch narratives, field enablement, or executive alignment.
Mentor, brainstorm, or exchange ideas
For conversations around technology commercialization, AI-enabled products, product strategy, or entrepreneurship.