Overview
Trend Weaver ingests content from RSS and news feeds, detects trends in near real-time with full explainability, and surfaces deep relationship insights via a knowledge graph.
The Problem
Understanding what's trending, why it's trending, and how stories relate. Information overload, no explainable trends, disconnected content signals.
Built for:
Analysts, product teams, editors, researchers
Architecture Overview
Architecture diagram coming soon
Core Capabilities
Trend explainability with attribution
Entity co-occurrence analysis
Narrative evolution tracking
Full-text search via Elasticsearch
User preference modeling
Key Features
- 01RSS/Atom feed ingestion with health tracking
- 02Content enrichment (entity extraction, sentiment, moderation)
- 03Story clustering across sources
- 04Multi-window trend detection (15min to 7 days)
- 05Neo4j knowledge graph for relationship analysis
- 06Alert subscriptions (webhook, email, Slack)
Status & Roadmap
This platform is currently in active development. Core functionality is being built with production deployment planned soon.
Interested in this platform?
This platform demonstrates production-grade engineering. Let's discuss how it might fit your needs.
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