DCL President Mark Gross sat down to discuss the company's evolution over its 45-year history. He delves into the company's first projects, the challenges of early technology, and how DCL adapted to the digital age. Reflecting on the past, he highlights the enduring need for data conversion and the impact of AI on the industry.

Every file you share, post, and publish carries a second, invisible layer of information that you may overlook. When you hit send on a file or post a file to your organizations Sharepoint or CMS, metadata travels with it, including who made it, when, with what software and sometimes a geographic location. But some sensitive information can leak if you don't understand how applications capture metadata.

A situation is unfolding inside AI initiatives at many organizations. Teams invest in AI models, platforms, and workflows and still get outputs they can't trust. The culprit isn't the AI model itself. Rather, it's the content going in.

In 1990, Dr. John Warnock launched his idea for The Camelot Project . The idea was to create a universal way to share documents across computers, operating systems, or networks without losing formatting. The vision was that a document could be created once, then reliably viewed, printed, and exchanged anywhere with the exact appearance preserved. The PDF, Portable Document Format, was sheer elegance in its simplicity yet beneath that simplicity lay a deeply complex codebase

Generative AI systems work best when the information they consume is organized, explicit, and precise. Structured content formats like XML and JSON provide exactly that – content that is machine‑readable, semantically rich, and consistently organized. Document processing is not simply one problem; rather, it comprises three components that must be considered.

DCL and Flatirons help aerospace and defense organizations modernize technical publications and unlock the full value of structured content.