System Architecture
The Newsreader is composed of three modules:Scraper Pipeline
The scraper runs as a scheduled process via PM2. Each cycle executes the following pipeline:Phase 1: Aggregation
- NewsAPI queries for neuroscience, psychiatry, BCI, DeSci, and related keywords
- Web scraper fetches from 400+ curated sources: journals, preprint servers, pharma outlets, neurotech companies, regulatory agencies, and community platforms
Phase 2: Analysis
- GPT processor evaluates each article against the Elata mission and assigns a relevance score (0-1)
- GPT validator filters out low-quality or irrelevant content
- Tag assignment applies from a controlled vocabulary of 86 domain-specific tags across categories: neuroscience, hardware, AI/ML, pharmacology, biohacking, biomarkers, DeSci, and industry
Phase 3: Enrichment and Output
- Content scraper extracts full text, word count, and reading time
- Embedding generation via OpenAI for semantic search
- Podcast generation produces AI-narrated audio summaries using ElevenLabs with two narrator personas (Nova and Dr. Renn)
- Discord notifications alert the community to high-relevance articles
- Results are written to
current.jsonand served via the REST API