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NimbusFeed — Case Study

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Case Study

NimbusFeed

AI Noise Reduction for RSS Power Users — "Read Less. Know More."

Overview

NimbusFeed applies AI where RSS readers fall short: filtering, deduplication, and summarization. It delivers Morning Brew-style daily digests, Google News-style story grouping, and syncs highlights directly to Obsidian.

The Challenge

RSS power users follow 200+ feeds and face an overwhelming firehose of content. Existing readers offer chronological lists with no intelligence. The same story appears 15 times from different sources, burying the content that actually matters.

Key Features
  • AI-generated daily digest emails (Morning Brew-style)
  • Semantic deduplication — groups related articles automatically
  • PKM sync with Obsidian (bidirectional knowledge links)
  • Smart muting and topic prioritization
  • Subscription management with Stripe
  • Comparison positioning vs Feedly, Inoreader, Readwise
Tech Stack
  • Next.js
  • Docker Compose
  • Miniflux (RSS engine)
  • OpenRouter LLMs
  • Stripe
  • Marketing site with pricing
Status

Product with marketing site, pricing, and checkout flow

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