Acade is an AI research co-scientist who starts with a research question and turns it into a structured, verifiable research loop. It helps researchers map literature, propose traceable hypotheses, plan experiments, interpret results, and turn the full path into an evidence-backed report while keeping the scientist in control. It is built for human-in-the-loop research, supporting users as they search, compare, critique, and document evidence without replacing scientific judgment. Acade begins with research question intake, capturing the domain, goal, constraints, files, assumptions, and expected decision before the agent starts. It can organize relevant papers, claims, methods, debates, and research gaps into a literature-grounded map while preserving source provenance. It also generates hypothesis cards that compare evidence, counter-evidence, novelty, feasibility, and risk, helping researchers review candidate ideas before execution.