Predictor Explorer
The Predictor Ingest pipeline ingests RSS feeds daily, extracts entities and relationships via LLM with quality gates, resolves duplicates, and exports structured graph data. The Predictor Explorer renders that data as interactive Cytoscape.js visualizations that surface emerging patterns early. Each domain brings its own entity types, relation taxonomy, sources, and extraction prompts — the framework handles everything else.
- 100% human-AI collaboration.
- Zero manual coding.
- Zero manual unit tests.
- Zero hardcoded domain logic.
Three weeks to first beta.
RSS Feeds → Ingest → Clean → Extract → Resolve → Export → Cytoscape.js │ │ │ SQLite LLM / Manual 4 graph views (archive) (with quality gates) + trend scoresEach stage documented in detail →
Tracks the film industry landscape — productions, studios, talent, festivals, distribution trends, and emerging formats.
Domain profile configured Explore graph ↗Tracks the AI/ML landscape — models, tools, orgs, papers, benchmarks, and emerging technology trends.
~30 RSS feeds · 15 entity types · 35 relations Explore graph ↗Monitors Federal Select Agent Program, dual-use research, gain-of-function policy, BSL facility oversight, and global health security governance.
13 RSS feeds · 14 entity types · 35 relations Explore graph ↗Supply chain dynamics, fab capacity, export controls, chip architecture evolution, and geopolitical positioning.
Domain profile configured Explore graph ↗Ingest
Domain-configured RSS feeds, archived with full provenance — URL, source, publish date, content hash. Raw HTML and cleaned text stored for re-extraction as schemas evolve.
Extract
LLM-powered entity and relationship extraction using domain-specific prompts and taxonomy. Quality gates enforce evidence fidelity, orphan detection, and confidence calibration.
Visualize
Interactive Cytoscape.js graph with four views — Trending, Claims, Mentions, Dependencies. Nodes maintain stable positions so emerging clusters and cross-domain bridges are visually apparent.