A banner image showing the Statue of Liberty advertising the Semantic Data conference with Factor as lead sponsor

Factor Sponsoring Semantic Data New York Conference

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We’re excited to share that Factor is a sponsor of this fall’s Semantic Data New York: Taxonomy, Ontology, and Knowledge Graphs conference on Oct. 14. Featuring information architects and experts from a variety of fields including tech, academia, and education—including Factor co-founder Gary Carlson— this intensive one-day event will offer attendees practical, business-focused education and guidance on how …

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A promotional image for the webinar Introduction to Knowledge Graphs with Bob Kasenchak and John Tulinksy

An Introduction to Knowledge Graphs

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Knowledge graphs are becoming an increasingly sought-after data management tool among enterprises, especially for those employing AI models. So how do enterprises get started with knowledge graphs? How can they be used to further business goals? In this webinar, Factor’s Bob Kasenchak and John Tulinsky covered the basics of KGs. Guests learned foundational principles, the …

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A long-range view of Notre Dame cathedral with flying buttresses and trees on either side.

Stability: The Solid Ground for AI Development

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During a recent webinar, I discussed AI and its dependence on data foundations, emphasizing how successful AI projects—those that move beyond pilot phases, mitigate risks, and deliver measurable value—hinge on trustworthy and reliable data.  We pinpointed four crucial areas for data infrastructure:  • User Focus – Aligning the AI products, data, and goals with the …

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overhead view of old-fashioned slides and projector, indicating an archive

Taxonomies at Any Scale: Three Lessons for Archives, Corporations, and Anyone in Between

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This article is a collaboration between the newest members of the Factor team, Jake Fatooh and Sam Stringer, who come from backgrounds in e-commerce and community archives, respectively. What could a community archive  and a global tech corporation possibly have in common? When it comes to taxonomy, more than you might think. Community archives focus …

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Are Your Taxonomies Costing You? 5 Smart Questions to Ask

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You’ve probably noticed that here at Factor we talk with people a lot about their taxonomies. Once we establish that we’re not talking about stuffed insects or animal heads, questions still remain. Questions such as, what do our taxonomies have to do with our business? We think it’s always helpful to go back and answer …

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Humans in the Loop - Taking a Human Approach to Enterprise AI

AI First, Humans Always: Insights from Shopify’s AI Transformation

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When Shopify CEO Tobi Lütke told employees that “everyone means everyone” in the company’s AI rollout, he wasn’t being provocative for the sake of it. He was setting a new standard for how technology adoption should work–bold, all-in, and deeply human. In a company-wide memo, Lütke laid out a mandate that repositions AI from a …

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deploying generative ai in enterprise applications poses ethical risks

Navigating the Ethical Minefield of GenAI

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What are the implications of deploying GenAI at scale? While ethics are an emerging consideration, organizations are still moving full speed ahead with Generative AI, facing real and immediate risks related to misinformation, bias, environmental impact, and reputational damage. How do we make sense of these challenges in a way that drives responsible, scalable AI …

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Implementing Enterprise AI Like a Librarian

4 Tips for Implementing AI Like a Librarian

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Libraries have spent millennia refining the art of organizing, retrieving, and safeguarding information. Their systems prioritize clarity, accountability, and ethical stewardship, qualities businesses now find indispensable as they integrate AI into their operations. While AI promises efficiency, its success depends on structured implementation, thoughtful governance, and human oversight. Look no further than the example set …

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Enhancing AI Effectiveness with Taxonomies and Knowledge Graphs

Enhancing AI Effectiveness with Taxonomies and Knowledge Graphs

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Modern AI systems are only as effective as the information they consume. Unfortunately, much of that information is messy. Taxonomies and other structured knowledge models have long helped organizations make sense of complex data. When paired with data management tools, they support everything from content discovery and analytics to personalization, integration, and lifecycle governance of …

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