Research Automation
Research automation turns a question into a sourced, structured answer using search, retrieval, extraction and synthesis agents.
/ quick answer
A research automation pipeline has four stages: query expansion (turn one question into many), retrieval (search and fetch), extraction (pull claims with citations), and synthesis (compose an answer that only uses extracted claims). The quality lever is extraction discipline — forcing every statement to carry a source kills most hallucination.
What is Research Automation?
A research automation pipeline has four stages: query expansion (turn one question into many), retrieval (search and fetch), extraction (pull claims with citations), and synthesis (compose an answer that only uses extracted claims). The quality lever is extraction discipline — forcing every statement to carry a source kills most hallucination.
What is an example of Research Automation?
A competitor-monitoring pipeline that runs 40 queries weekly, extracts pricing and feature claims with URLs, and outputs a diff against last week.
Why does Research Automation matter for AI and automation?
Research automation turns a question into a sourced, structured answer using search, retrieval, extraction and synthesis agents. It connects to the workflows, prompts and tool stacks linked on this page, so you can move from definition to execution without leaving Onexial.