AI Knowledge Hub
AI’s rapid growth brings challenges and opportunities. If you’re a legislative leader, standards developer, audit professional, or standards consumer, Propylon’s AI Knowledge Hub is designed for you. We help you navigate topics like AI inaccuracies, optimizing AI adoption and ensuring that AI is a strategic benefit to your organization.
The AI-ready legislature: Considerations for drafting and legislative processes
In this eBook, we'll navigate the evolving legislative landscape as it approaches a critical turning point. Discover: practical AI use cases, robust security and risk mitigation considerations, essential factors for future planning.
February 2025
Webinar recording: AI in Legislative Drafting: A Digital Intern to Support the Craft
May 2025
Webinar recording: what can SDOs gain from the rise of industry-specific data models?
Watch our recent webinar to learn more about the rapidly changing way data is being structured and shared. At this time, we’re also witnessing a vital trend in an AI-driven future across a range of industries – the rise in the development of industry-specific data models that facilitate information exchange between standards developers and consumers.
In order to gain insight into this trend, we also delved into the case study of XBRL.
Standards and Machines: the Rise of Industry-specific Data Models
In today's AI-first world, developing seamless knowledge exchange between standards makers and consumers isn't just an advantage—it's a necessity. Discover how the PDF can evolve into a vital source of ground truth in an AI-driven landscape; knowledge graphs and RAG (Retrieval Augmented Generation) methods can significantly mitigate AI-related risks; industry-specific data models are emerging as a key opportunity for Standards Development Organizations.
AI for rule-makers and rule-takers: key concepts
What is the concept of ground truth and why does it matter?
Ground truth is the bedrock of reliable AI: it’s the definitive, accurate data that provides a foundation of truth for AI models. Techniques like knowledge graphs and RAG are crucial for feeding AI systems this precise data. By leveraging your own high-quality information as this source of truth, you effectively ground AI.
