About Blerbz

What is Blerbz?

Blerbz is an AI-powered news intelligence platform that aggregates, ranks, and enriches breaking news from over 500 trusted sources worldwide. Founded in 2024, Blerbz delivers real-time news feeds, algorithmic daily rankings, AI-driven viral detection, and entity extraction — all without editorial commentary or bias.

The platform combines advanced machine learning with multi-source news aggregation to surface the most impactful stories of the day. Every piece of content is AI-enriched with topic tags, source credibility scores, engagement metrics, and trending signals, giving readers a transparent view of what matters and why.

News Intelligence, Not Just Aggregation

Traditional news aggregators collect headlines. Blerbz provides news intelligence — the application of AI and data analysis to understand what's happening, why it matters, and how stories connect across sources.

• BLERBZ100 Rankings — Daily top 100 news stories ranked by a transparent, multi-factor algorithm combining engagement, velocity, viral lift, freshness, and source reputation.
• Viral Detection — Real-time trending detection with multi-factor scoring and time-decay weighting to identify breaking stories as they emerge.
• Entity Extraction — NLP-powered topic tagging (“blerbles”) that identifies people, organizations, products, and events in every story.
• Source Credibility — Reputation scores for every source, from top-tier outlets (NYT, BBC, Reuters) to technology blogs and regional papers.
• AI Summaries — Grokipedia generates instant encyclopedia-style context for any news topic or headline.
• Zero Bias — No editorial commentary, no opinion injection. The algorithm surfaces stories based on data, not editorial judgment.

Platform Features

How the BLERBZ100 Algorithm Works

The BLERBZ100 is a transparent, explainable ranking algorithm that scores news stories across multiple factors:

• Engagement Rate (15%) — Click-through rate, shares, and saves relative to views.
• Velocity (15%) — How quickly a story gains engagement over time.
• Viral Lift (15%) — Cross-source amplification and trending signals.
• Freshness (12%) — Recency with time-decay weighting.
• Source Reputation (7%) — Publisher credibility score (NYT/BBC/Reuters = 1.0, tech blogs = 0.7-0.9).

Diversity rules prevent source clustering (maximum 3 items per source), and scores update hourly to reflect real-time engagement. Rankings are fully auditable with score breakdowns available via the NUCLEUZ API.

Sources & Credibility

Blerbz aggregates from over 500 trusted news sources across multiple tiers:

• Top-tier (1.0) — The New York Times, BBC, Reuters, Associated Press, The Washington Post, The Guardian
• Major outlets (0.8-0.9) — CNN, NPR, Bloomberg, The Wall Street Journal, TechCrunch, Wired
• Regional & specialty (0.6-0.8) — Regional newspapers, industry publications, technology blogs
• Community (0.5-0.6) — Reddit, Hacker News, curated social content

Technology

Blerbz is built on a modern, high-performance stack designed for real-time news intelligence:

• Frontend — Next.js with React, optimized for Core Web Vitals (LCP < 2.5s)
• Backend — NUCLEUZ (Fastify + TypeScript) with multi-tier caching (memory, Redis, PostgreSQL)
• AI — Grok AI for content enrichment, NLP libraries for entity extraction and topic tagging
• Video — FILMZ engine for AI-generated video news broadcasts
• Data — dbt data warehouse for analytics, real-time RSS ingestion from 500+ feeds

Contact

Follow Blerbz on X/Twitter (@blerbznews) for updates and daily highlights.