Original Summary

I'm a political science student. I kept running into the same problem with geopolitical risk material: it is all adjectives. "Rising tensions", "elevated risk", "uncertain outlook". Nothing you can put in a spreadsheet or defend in a committee meeting. So I built GeoDecrypt to try to turn geopolitical exposure into something closer to a number. What is in it: 196 country sheets and 278 multinational profiles A sentinel that polls live sources on a schedule and watches specific chokepoints (Red Sea, Hormuz and others) rather than "the news" in general Shock propagation: when a corridor degrades, what it does to downstream suppliers, and with what delay Scenario and timeline modes for structured analysis A REST API, because the target user has an ERP or a TMS, not a browser tab It is in production: 428 tests, Stripe live, country and company coverage built out. The part that actually cost me the most time, and the only real reason for this post The analyses are LLM-generated, and LLMs are extremely good at producing plausible-looking citations that do not exist. I built prompt instructions that effectively guaranteed a source for every claim, which is a recipe for fabricated ones whenever retrieval came back thin. Two invented citations in a risk note are worse than no citations at all, because the note looks more credible for having them. Fixing it meant inverting the pipeline: retrieve first from real sources, generate only from what was retrieved, and treat "no source found" as an acceptable outcome instead of something to paper over. Less impressive output, considerably more useful. There is a free tier if you want to poke at it, no card required: https://geodecrypt.fr I would rather get feedback on the data model than on the landing page, especially from anyone who has tried to quantify supply-chain exposure without a Bloomberg terminal.   submitted by   /u/BedSad7491 [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/16 22:47:49