We build AI systems for a living. In production today, that means LangGraph wired into Belvedere: governed pipelines, human approvals, audit trails, provenance, etc.

But for this project, I wanted to kick the tires on something new: Flue, the agent framework from the Astro team. I’ve long been a fan of Astro for web development, so when they released Flue, I wanted to take it for a spin.

Initially I went down the path of adding Flue to background tasks (bug ticket sync, feedback triage, opportunity discovery, etc), but then decided to build something a little more fun, an 'agentic analyst org' powered by Flue.

It's completely free to use if you want to head to https://www.belvederelabs.ai/ and try it out with your data.

Flue Analyst Org | Belvedere Labs: drop a CSV and get an analyst's answer in a couple of minutes.

The data: 3,759 international matches assembled by Belvedere

We did not hand-roll the dataset. We built it in Belvedere, the same governed pipeline system we use in production.

The pipeline ("World Cup International Match Dataset") is eight nodes and seven edges in the canvas that was assembled by connecting our source API and using the following prompt:

"Pull senior men's international football fixtures and per-match statistics from the API-Football REST API, then computes leak-free pre-match features with all available statistics"