OpenAI architecture primer

OpenAI Private Safety Processing

A visual primer on how eligible Zero Data Retention projects support offline automated safety review through customer-controlled storage and protected processing.

  • The PSP control boundary
  • API request and retention
  • Asynchronous safety review
  • Project setup and operating duties
Tom M. Gomez, AI Transformation Architect and Managing Partner at Luminity Digital

About the Author

Tom M. Gomez

AI Transformation Architect
Managing Partner, Luminity Digital

Connect on LinkedIn

Tom M. Gomez is an AI Transformation Architect and Managing Partner leading Luminity Digital’s Applied AI Practice, including its Frontier Capabilities Group. He works at the intersection of business strategy, product management, and technology delivery, architecting applied and Agentic AI systems across multiple platforms. His focus spans security and governance, system reliability, context management, cloud infrastructure, and the full data and application lifecycle.

In that role, he designs systems an enterprise can defend—first to the customers it serves, then to the board, auditors, and risk committee accountable for that trust. By building governance into the architecture during design, he makes AI Assurance a structural property of the system rather than a review applied after deployment.

Tom is Principal Architect of Luminity Digital’s AI Collaboratory, where he works with research scientists on the architectural layers required to operationalize enterprise AI—not as separate products, but as a coordinated system designed for action under constraint. He is also the architect and program lead for the AI Talent Accelerator (AITA).

Tom brings more than 25 years of enterprise architecture and digital transformation experience across Fortune 500 organizations in financial services, healthcare, and manufacturing. His broader experience spans engineering, finance, private-client advisory, nonprofit leadership, scientific research, and academia, including NSF- and NIH-affiliated initiatives. He has served as a founder, practice lead, and CEO.

His work spans Decision Intelligence, Data Intelligence, Hyperscalers, and Agentic AI. He publishes systematic reviews of peer-reviewed research that surface the empirical evidence, then translates that evidence into governed architectures engineered for assurance and measurable business value.

The experience is the foundation. Applied AI is where it now performs. 20× Certified.