We build a trustworthy path for research data

Wearables, phones and clinical records let researchers collect real-world data over long periods. Yet tracing which participant, which study and which permission that data belongs to, and turning it into a reproducible analysis, is often left to spreadsheets, shared folders and manual matching.

We are building EnaResearch for that gap as a five-layer platform: collect raw data with its source; standardize it and make its quality visible; add clinical context from hospital stays, clinical events and manual measurements; produce versioned datasets, variables and pre-approved analyses; and interpret results with an optional AI assistant. Raw data never changes, and every derived value carries the version of its definition.

Statistics are computed deterministically with established open-source libraries; the AI never computes and only interprets approved results. We develop the product step by step and never present an unfinished feature as finished. Our goal is for research teams and organizations to be able to show what came from where, and under which rules, both when collecting and when analyzing data.