The SerpAPI Research Pipeline automates multi-source research by orchestrating queries across SerpAPI Google Search, Google Scholar, and Google News JSON endpoints. For each research topic, it generates query variations using synonym expansion and boolean operators to maximize coverage. Search results are parsed and deduplicated using URL normalization and content fingerprinting. The pipeline extracts named entities from result snippets using spaCy NER models, identifying people, organizations, locations, and technical terms relevant to the research domain. All results are stored in a SQLite database with FTS5 full-text search indexes for rapid retrieval. The agent supports iterative deepening where initial results inform follow-up queries for comprehensive topic coverage. Citation graphs are built by cross-referencing Google Scholar results. Export formats include CSV, JSON, and formatted Markdown research briefs with source attribution and confidence scoring.