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CASE STUDY · [07]
Distributed Product Intelligence Engine
Edge-node scraping fleet, document ingestion, rate-limit handling, clustering, and recurring market signal detection. Live at dashboard.eternalconquests.com.
Outcomes
0+Documents ingested
0Edge boards
MEDIA SLOT
BRIEF
A rig I could point at a market question and let run overnight, without watching a token counter or a rate-limit graph.
[01]
Distributed collection across 4 physical edge boards: Raspberry Pis, a Jetson Nano, and Windows To Go nodes. Together they've ingested 40,000+ public documents.
[02]
Managed rate limits through OAuth failure traps. Deployed clustering pipelines using Jaccard matrices and TF-IDF vectors to group recurring industry indicators.
[03]
Output is public at dashboard.eternalconquests.com. Click the LIVE link in the header to see it now.
STACK