Engineers at heart.Owners by design.

We started Cipher Ranch because AI changes how great software teams work, but not who is accountable for the result. Our founders combine engineering, cybersecurity, software, product, AI governance, intellectual-property, and emerging-technology experience.

Co-Founder / 01

Juan J. Vasquez

Systems thinking across engineering, security, and AI adoption.

Juan is an electrical engineer, former U.S. Air Force cybersecurity officer, patent attorney, and AI governance leader. His career spans network defense, malware reverse engineering, technology development, IP strategy, and responsible AI adoption.

He chairs the State Bar of Texas Emerging Technology Committee, founded 3ITAL, directs 3i BAIRD Lab, and authored Artificial Intelligence (AI) in Patent Practice. At Cipher Ranch, Juan brings product strategy, systems architecture, cybersecurity judgment, and a practical framework for using AI responsibly.

Full profile ↗Professional bio ↗

Co-Founder / 02

Enrique “Rick” Sanchez Jr.

Engineering judgment and pioneering leadership in AI governance.

Rick is an electrical engineer, former software coder, registered patent attorney, technology strategist, and AI governance expert. A pioneer in AI governance, he has been at the forefront of translating AI's technical realities into practical structures for responsible adoption. Before entering law, he designed and commercialized signal-processing and communications systems at Raytheon and SAIC.

He has served in the U.S. Navy Reserve as a cryptologic officer after prior enlisted Army service. His experience spans software, machine learning, blockchain, computer architecture, communications, control systems, open-source technology, and commercialization. At Cipher Ranch, Rick combines deep technical judgment with pioneering experience in how organizations govern, deploy, and scale AI responsibly.

Professional bio ↗LinkedIn ↗

How we think

A studio built around judgment.

The tools will keep changing. These principles should not.

Understand before automating

The team must understand the problem, the context, and the consequences before AI can be useful.

Stay close to the work

The people making architecture and product decisions remain engaged through implementation and release.

Make capability accountable

Every increase in speed or reach is paired with review, evidence, and a human owner.

Your next build

Put the experience to work.

Bring us a meaningful product problem, especially one that needs technical range, domain fluency, and human accountability.

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