Life Sciences Research Agent

Life Sciences Research Agent is a multi-agent system for research teams in Healthcare & Life Sciences. It helps address this problem: Researchers need to connect literature, trials, internal findings and structured scientific knowledge.

The workflow starts when scientific question is submitted. It uses literature, trial, knowledge graph and evidence agents to complete these steps: Search approved literature; Retrieve relevant trial data; Connect internal research; Evaluate evidence quality; Generate hypotheses for researcher review.

A typical implementation can connect to approved systems such as Research repository, Clinical trial data, Knowledge graph, Document store, Approved external sources. The exact integration depends on the organization's architecture, access policies, and data boundaries.

Human involvement should remain where the workflow requires judgment, exceptions, or a sensitive business action. For this use case, Evaluate findings, validate hypotheses and make scientific decisions.

Important controls include Approved sources, Citation provenance, Researcher access, Evidence scoring, Review workflow. These controls help define what the AI system can see, recommend, or do and when a person must review the outcome.

This workflow is marked advanced in the CodeCrux use-case library. Production readiness still depends on data quality, system access, evaluation, observability, security, and a clear human review design.