SFI-01
In Production
Symbology
AI-synthesized equity research from SEC filings
Symbology ingests SEC EDGAR filings and synthesizes structured research with tiered LLM inference — small models summarize individual documents, larger models build the aggregate picture. It began as a rapid prototype and was progressively re-engineered into the flagship of this register.
The interesting machinery is underneath: a scheduler and distributed worker processes coordinate through a PostgreSQL-native job queue. Atomic job claims via SELECT … FOR UPDATE SKIP LOCKED mean there is no external broker to deploy, monitor, or babysit — the database the system already trusts is the queue.
- Postgres-native job queue with atomic claims — no Redis or RabbitMQ in the stack
- Full ingestion → inference pipelines tracked end-to-end, with partial-failure states
- Tiered model strategy keeps inference cost proportional to document value
- Ongoing work: frontend readability and mobile UX iteration, data-quality investigations as first-class engineering