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Enterprise GenAI: To Build or Buy a GenAI LLM?

Your business amasses an enormous, ever-growing amount of market data and internal research. But that data is so often unorganized—uncovered only by endless clicking through folders and an over-reliance on CTRL+F.

As generative AI promises to bring consolidation and findability to your organization’s research and data, leading C-Suites are considering genAI tools and large language models (LLMs) as a solution for this multimillion-dollar problem. But questions remain: Would your data remain secure? Will these systems deliver reliable, relevant information? And crucially, what are the implications of building your own LLM or buying and customizing a third-party genAI solution?

As you look for knowledge management solutions that make sense for your organization, our whitepaper ensures you understand the LLM build vs. buy conversation and key considerations for genAI at an enterprise scale.

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Inside Project Vault and the Global Hunt for Rare Earth Minerals

In this report, we leverage workflows from the AlphaSense platform to dig into Project Vault and assess its trajectory as judged by leading experts in the field.
Inside Project Vault and the Global Hunt for Rare Earth Minerals. Blue line art of a mining dump truck and rocks on a light blue, lined background.

The VC Playbook: How to Spot a Purple Cow in Crowded Pastures

In this playbook, we leverage insights from Harry Stebbings of 20VC to answer this question among others, including: What are the characteristics of successful early stage companies? Which unconventional criteria play an important role in securing deals?
Title slide for 'The Venture Capital Playbook: How to Spot a Purple Cow in Crowded Pastures,' featuring outlined illustrations of a purple cow and a white bull.

Execution in Focus: Tracking Key Healthcare and Biopharma Trends in 2026

This report tackles these issues and other key trends shaping the healthcare landscape in early 2026.
Title slide: Tracking Key Healthcare and Biopharma Trends in 2026 by Sara Mallatt and Sean Carmichael, featuring data graphs and medical icons.

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