ZEITLIGHT

zeitlight.com ↗Live Prototype

News became hard to orient around — high-attention stories felt urgent even when their actual impact was low, while more meaningful developments got buried. Zeitlight is a proprietary pipeline that scores articles across Attention, Impact, and Source Context — surfacing what actually matters and explaining why, rather than leaving users with a raw headline and no frame of reference.

Built With

React

Firebase

Claude

OpenAI

Wink

WordNet

01 / 05 — Real-time signal feed

Track incoming stories as they enter the system, each scored for Attention Gravity and Systemic Impact.

In Action

System Flow

Autonomous pipeline for signal attribution

Ingest & Normalize

Raw article content is pulled and normalized for analysis.

Filter & Categorize

Arbitration removes low-quality content and assigns categories.

Score & Analyze

Hybrid deterministic and LLM scoring assigns Attention and Impact values.

Render Output

Processed data delivered modularly across each interface layer.

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Next Layer

Scoop Mode

Most aggregators ask: What happened?
Scoop Mode asks: What changed?

Scoop Mode is the narrative-state layer of Zeitlight — designed to compare incoming articles against existing story context and identify whether a development meaningfully changes the narrative, not just whether it adds another headline.

In Development