Overview
Northbound is an experiment in modeling the financial world as a structured ontology rather than a collection of disconnected datasets. It combines companies, products, technologies, industries, economic drivers, and market data into a connected knowledge graph that both humans and AI systems can explore and reason over.
Why It Exists
Financial research often requires stitching together information from filings, earnings calls, market data, industry reports, and news sources. While modern AI can retrieve information, it still struggles to maintain consistent understanding of relationships between entities and explain how conclusions were formed.
Northbound explores whether explicit knowledge representation can improve financial reasoning, transparency, and agent-driven research workflows.
What I Built
- ontology and knowledge graph architecture
- entity and relationship modeling for financial systems
- time-series integration across companies and economic indicators
- structured evidence and claim representation
- AI-oriented retrieval and reasoning workflows
- data ingestion and normalization framework
- early exploration interfaces for connected financial knowledge
Current Status
Northbound is in active development. Current work focuses on building the core ontology, ingesting financial and economic datasets, and establishing a foundation for AI-assisted analysis and exploration.
Explore
Northbound is not publicly available yet. Public demos, visualizations, and interactive exploration tools will be added as the ontology and underlying data platform mature.