ScoutFox
An alert layer for first-mover intelligence
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Hi HN! We’re building ScoutFox, an alert layer that continuously scouts your interests, filters signals from noise, and reports findings.The ideal user is anyone wanting to monitor something specific to find some alpha before it's obvious. It could a VC looking to invest early on hot startups or a newsroom looking for a breaking story on a niche subject.Google Alerts and RSS feeds could find new changes associated with a keyword but they're bad at determining whether a new piece of information is genuinely significant relative to what the user already knows and cares about. That's the problem we are trying to solve.An example flow in ScoutFox looks like this,Broad discovery - Give a brief on what you want to monitor ( Ex: Track investment opportunities in AI hardware). ScoutFox will drill you to get really specific on the context of your brief (Ex: Monitor LinkedIn status of veterans in hardware AI connecting to any legal entity registrations.)Focused Investigation - Once the rich context is confirmed, it continuously searches the web and other private data sources you've configured, compares new evidence with its existing context, investigates promising changes, verifies them across sources. The goal here is to maximize signal to noise ratio.Synthesis; Results arrive as a short daily brief through the app, email or WhatsApp along with explanations on why they might matter.We’re currently testing it with journalists, angels investors and VC analysts.Would love for any feedback.I’m Arvind, one of the founders. Happy to answer questions or create a sample brief for anyone who wants to test it.
HN · launched Jul 23, 2026 · 6 upvotes (top 71%) · 0 views
Niche: market and business intelligence platforms · 196 launches, 8 in the last 7 days ▼ -56% · Explore this niche →
Category and tags
- Horizontal
- Workflow automation
- B2B
- AI feature
- Commercial product
Visit website ↗ Source listing ↗
More like this: all 196 launches in market and business intelligence platforms →
Could you build this?
Partial Building the user dashboard and LLM summary generation is straightforward, but maintaining continuous multi-source scrapers across corporate registries, GitHub, and patents while filtering noise reliably requires heavy data engineering.
What it would actually take: The stack would need distributed web crawlers and webhook listeners (using Playwright/Temporal/Kafka) continuously monitoring SEC filings, GitHub repos, patent databases, and job postings. An LLM pipeline cleans, deduplicates, and scores changes against specific user thresholds. The hard part is managing anti-scraping countermeasures across hundreds of platforms and building reliable entity-resolution models to link disparate signals to specific companies.
Discussion
1 comment analyzed.
Concerns raised: How false positives are handled, Whether weak signals across sources are explained before surfacing
Feature requests: Explainability for why signals are considered important
Competitors
Other products that read as similar to this one : 185 launches clear the similarity bar, closest 8 shown.
Attention rank: #174 of 186 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 252 days after the earliest competitor.
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