Signal Desk
Private investment-research prototype
Signal Desk
Signal Desk began with a useful admission: I did not know enough about investing to trust either my instincts or a confident machine. Instead of building a trading bot, I built a private research desk that makes a hunch pass through sources, an explicit thesis, counterevidence, uncertainty, and time.
The system resolves companies to SEC identities, stores filings and source-linked research, organizes watchlists through thematic lenses, and produces recommendation categories that preserve evidence, risks, confidence, and what still needs human verification. Ghost trades provide a paper-only record of decisions without connecting the product to a brokerage or order flow.
Role
- Designed the research workflow, thesis model, discovery system, skeptical recommendation format, and paper-only decision trail.
- Built a private Docker-based application with a Next.js interface, FastAPI services, local persistence, vector search, SEC ingestion, and swappable model providers.
- Created theme-based discovery scans across filings, ETF holdings, selected institutional reports, news feeds, and curated sources.
- Kept brokerage connections, order placement, financial advice, and certainty theater deliberately outside the system.