Problem
What needed to change
Domain experts needed to find specific, high-signal information scattered across many sources. Manual research took days and produced inconsistent results.
Approach
Architecture + execution
- Built an autonomous agentic workflow to plan, crawl, extract, and normalize domain-specific information.
- Implemented a massively scalable crawling pipeline using GCP Cloud Functions for parallel fetch + parse.
- Generated embeddings and metadata-enriched indexes to support semantic retrieval and filtering.
- Added workflow orchestration for scheduling, retries, dedupe, and incremental refresh.
- Shipped a semantic search layer that returned precise matches quickly with relevance tuning and fast ranking.
Results
Outcomes that held up
- Reduced research time from days to minutes through automated collection and semantic retrieval.
- Improved consistency by standardizing extraction, indexing, and refresh pipelines.
- Delivered fast, scalable search with freshness controls and operational visibility.