Automating public record scraping, document extraction, and normalizing real estate assets data for investment analysis.
Investment researchers analyze thousands of land title sheets, corporate earnings reports, and regional tax assessments daily. Manually extracting property metrics, ex-dividend calendars, and transaction records creates significant data processing latencies. Below is an overview of how Quasar's automated extractors capture and normalize unstructured documents into investment databases.
PDF Land Records, Public Tax Feeds, HTML Dividend Schedules
Private Llama-3-70b-instruct NIM parsing algorithms
Relational Postgres database structured as JSON files
By migrating financial and land record extraction onto local private NIM setups, coverage margins are scaled without data leaks.