Problem: News readers who worry about filter bubbles have no fast, in-context way to judge how a specific article is slanting them. Existing tools like AllSides rate whole outlets, but bias operates at the sentence level - a single article from a 'center' outlet can contain loaded framing, selective quotes, and emotionally charged word choices. Readers either take the outlet's overall rating on faith or manually cross-check other sources, which almost nobody does.
Named product: LensLine - a Chrome extension that highlights political bias inside the article you are actually reading, sentence by sentence, and surfaces how other outlets are covering the same story.
Solution: LensLine parses the current article, scores each sentence for lean and loaded language, and color-codes the text inline. Clicking a flagged sentence shows why it was flagged (framing, adjective choice, source attribution) and links to how left, center, and right sources described the same event. Instead of a static outlet grade, the reader gets a live annotation layer over the content in front of them.
MVP: A Chrome extension that (1) extracts article text from major news domains, (2) runs sentence-level lean and loaded-language scoring, (3) renders inline highlights with a summary bias meter, and (4) offers a 'compare coverage' panel that pulls headlines on the same topic from a spread of sources. Ship the free version limited to a handful of articles per day.
Revenue: Freemium. Free tier caps daily article scans and source comparisons. Paid tier (a few dollars per month) unlocks unlimited scans, full source-comparison panels, saved history, and export. Sell via a creator-commerce style checkout rather than building heavy billing infrastructure, mirroring how comparable indie tools monetize.
GTM: Launch where media-bias debate already happens - Hacker News (the community has an active thread on Media Bias Fact Check), plus reply-guy presence on YouTube bias-explainer videos and political subreddits. The extension itself is the demo: a screenshot of a familiar article lit up with sentence-level highlights is inherently shareable.
Growth loops: Every highlighted article is a screenshot ready for social sharing during news cycles. A 'share this bias breakdown' button turns any hot political story into distribution. Users who compare coverage naturally send links to friends arguing about the same article.