A Docker-related footgun led to a vandal deleting NewsBlur’s MongoDB database; the incident was documented publicly by the company.
SourceNewsBlur is a personalized news reader
Public company, workplace, funding, and market signals
Updated Jul 30, 2026
NewsBlur is an independent, open-source personal news reader and social RSS aggregator that helps users train what they read, follow websites and newsletters, and use AI-powered filtering, summaries, and story analysis.
Primary product
Personal news reader / RSS feed reader with intelligence training, AI features, and native web, iOS, Android, and Mac apps.
Founded
2009
Headquarters
San Francisco, California, United States
Team size
1
Industry
Software Development
Sub-industry
RSS feed reader / news aggregation
Offices
0 jobs at NewsBlur
Check back later for new openings
Business model
Stage
Seed
Total raised
$20K
Latest round
Seed · Aug 2012
Latest amount
$20K
Aug 2012 · Y Combinator
Leadership
Founder / CEO
David Sinclair
iOS Developer
Andrei Dan
Android Developer
Lyric
Chief Morale Officer
Investors
Product-led, indie, open-source, community-driven, and shipping-focused; the company emphasizes no ads, no tracking, self-hosting, and frequent feature releases informed by forum feedback.
Pricing
Freemium with a free tier, annual premium plans, a monthly premium-pro tier, and a self-hosted open-source option.
Differentiators
Technology
Customers
Competitors
A Docker-related footgun led to a vandal deleting NewsBlur’s MongoDB database; the incident was documented publicly by the company.
SourceNewsBlur Blog · Jul 2026
Introduced a redesigned Global Shared Stories feed and a new Good Reads feed, both using AI-assisted ranking and reading-based signals.
NewsBlur Blog · May 2026
Added premium custom app icons with multiple colors and light/dark variants across major platforms.
NewsBlur Blog · Apr 2026
Announced the Premium Pro tier with higher-frequency fetching for professional monitoring use cases.
NewsBlur Blog · Apr 2026
Launched usage-based AI classifiers that let users train feeds with plain English descriptions for text and images.