Acade

Acade is an application that assists AI research by structuring the whole research cycle. It starts with research question intake, capturing the domain, goals, constraints, relevant documents, and the decisions you expect to make. From there it clusters related papers and maps the claims, debates, and gaps inside them while keeping source information intact. It then generates candidate hypotheses with supporting evidence, counter-evidence, novelty, feasibility, and risk assessments, so you get several directions rather than a single guess. Experiment planning turns a hypothesis into concrete data requirements, baselines, metrics, controls, and risk checks.

- Capture research questions with full context

- Map literature claims, debates, and gaps

- Generate hypotheses with evidence and risk review

- Plan experiments with data and baseline requirements

- Interpret results and produce an editable cited report

- Researchers who need a reproducible workflow

- Students learning how to run a study

- Educators designing research-based courses

A free trial is offered, but paid packages such as Plus, Pro, and Team Lab set credit limits and feature access, so heavy use costs money. Output quality depends on how clearly you frame the question and how good the underlying literature is, since a vague brief produces a vague mapping. The tool assists with evidence handling but does not replace scientific judgment, and it cannot guarantee that a study is valid or novel. Generated reports still need human review before they support a real decision or publication, and citations should be checked against the original papers, since automated mapping can occasionally attach a claim to the wrong source.