At ODSC, Amy Hodler (GraphGeeks) chats with Stamati Liapis, cofounder of Enlay, about using graph AI and network modeling to transform risk management in the construction industry. Stamati explains how he applied his PhD in computational neuroscience (studying brain networks) to solving complex risk networks in construction.

Key Takeaways:

• Around 96% of construction data sits unused. Graph AI and LLMs help structure this messy data for accurate future predictions.
• We can combine graph modeling and LLMs to help contractors analyze financial, commercial, and contractual risk across a project’s entire lifecycle.
• Academic Founder Tip: Shift from perfectionism and ship an 80%-ready product to get real-world user feedback instead of optimizing in a silo.

More Info about Enlaye

https://www.enlaye.com/

In this Graph Chat, Amy Hodler catches up with James Massaquoi at the Glasswing Ventures offices for a candid conversation on where knowledge graphs, AI agents, and enterprise data architectures are heading.

Key Topics Covered:

• Context for Autonomous AI: Why reliable enterprise AI workflows depend on understanding historical context and connected data.
• Cutting Through Buzzwords: Why "context graphs" shouldn't be overhyped and where graph technology actually delivers value in the modern stack.
• Knowledge Graphs - Memory Stores: How the line between graph databases, auxiliary memory models, and agent architectures is blurring.
• Building for Enterprise Scale: What early-stage investors look for in AI and knowledge graph startups today.

🔗 More on Glasswing Ventures: https://glasswing.vc/

In this interview live from the Open Data Science Conference (ODSC) in Boston, Amy Hodler (GraphGeeks) sits down with Dr. Janet Six, Senior Product Manager at Tom Sawyer Software, to discuss the evolving role of data visualization and graph technology in the age of AI.

Dr. Six highlights why data visualization shouldn't just be an afterthought—like sticking a basic pie chart into a slideshow—and advocates for a systems engineering approach to craft interactive, meaningful visual tools. They explore how visualization is essential for monitoring and managing complex AI agent workflows, as well as providing the deep context that simple LLM text responses often miss.