Learn how to design efficient workflows, validate outputs, and ethically deploy AI-powered research assistants in 2026. Includes prompts, checklists, and templates.

Just because public policy text is open source does not mean that it is easy to find or access. Spoiler alert -- a kitchen sink approach to language data acquisition is a fast track to high costs, slow training times, and suboptimal outputs. This post seeks to help global macro strategists structure more effective text acquisition strategies to support their portfolio priorities.

Should we separate out the trade policy data that we generate and provide it to customers in a dedicated, separate feed?

The new Xai Holdings Corporation creates captive (but not golden) training data for Grok from X. It won't be enough; they will need more.

Delve into AI's $15.7 trillion potential, data integrity, and ethical practices in our Q&A session w/Solomon Partners

Highlighting appropriate and inappropriate uses of synthetic data when training AI systems. Raising red flags about synthetic language data.

Your AI is only as good as the data you feed it. This post de-mystifies Derivative/Signal Data for predictive analytics & generative AI.

AI Training Data 101 -- your 2025 guide to the kinds of data available for training generative AI and quantitative AI models.

Discover how PolicyScope data can help global macro investors and investment advisors measure reserve currency policy risk and manage exposu

And so it begins. Japan today continues the global trend of electing to leadership another outsider whose views on a range of issues run...

Transition Risk Data for Climate Week: why & how to use PolicyScope CRRM3 language-derived data to measure transition risk.

This post shows how to apply MACD analysis to the public policy process in order to generate alpha using PolicyScope data.

Monetary policy decisions may be data-dependent, but market reaction functions are driven by words. New patented technology now makes it po