AdvisorListen Reddit Intelligence

Financial subreddits are mostly noise: consumer complaints, career questions, exam spam. The signal an advisor can actually use is a small fraction of the traffic, and it has to be found, classified, and published on a fixed clock. The whole pipeline — scraping roughly 50 communities, classifying every candidate post, composing the brief — runs unattended overnight and must finish before a 6:30 AM Central send gate every weekday. The cost envelope matters too: classification volume is capped per community so that a heavy news day cannot blow the budget or the deadline.

Classification runs inline in the scrapers. Each candidate post is sent to a Claude model during the scrape with a structured-output contract that includes topic, sentiment, and a 0-to-5 high-net-worth relevance score. A title-level pre-filter rejects obvious off-topic posts before paying for classification. PostgreSQL is the single source of truth. This ruled out a background ML service, a message queue, and a vector database on purpose: a daily editorial product does not need realtime infrastructure, and every component removed is a component that cannot fail at 3 AM. Every pipeline stage writes a completion stamp, so an overnight failure resumes from where it stopped instead of re-scraping from zero.

The headline number counts social media comments scanned and categorized: more than 2 million per month across the communities the pipeline monitors. Deduplication is by content hash, so reposts and crossposts are counted once. The brief ships each weekday morning to roughly 3,800 subscribers.