What makes EMET different

Most AI assistants answer biomedical questions from their training data alone. EMET's architecture is different in several ways that matter for scientific work.

Live database queries

EMET retrieves data from primary sources in real time. When you ask about a variant, it queries ClinVar now — not a cached snapshot from training.

Mandatory citations

Every specific claim comes with a hyperlinked source. If EMET cannot cite a claim, it will say so explicitly rather than presenting it as fact.

Multi-database synthesis

A single research question often draws from five or more databases. EMET integrates evidence across sources into a single, coherent answer.

Honest about uncertainty

EMET distinguishes between what the data shows and what it does not. It flags data gaps, contradictions, and the limits of the available evidence.

Scientific rigour

EMET applies domain knowledge to interpret results — selecting the right statistical thresholds, contextualizing findings, and flagging methodological considerations.

Reproducible reasoning

EMET explains which databases it queried, which parameters it used, and why — giving you a transparent audit trail for every analysis.