Reyanda combines causal research, statistical modelling and public-interest technology to improve consequential decisions—from the evidence base to the system people actually use.
Complex public problems are not solved by another dashboard or report alone. They require evidence, systems and implementation to be designed together.
Each practice can stand alone. Their greatest value appears when a question moves from research, through system design, into a tested product or programme.
Causal inference, epidemiology, evidence synthesis, statistical modelling and health economics—designed around the decision the evidence must support.
Explore research ›Decision architecture for health information, interoperability, supply planning and institutional workflows—grounded in policy and implementation realities.
See systems work ›Research and public-interest tools built locally, validated honestly and labelled by maturity—without presenting prototypes as finished institutions.
Explore ventures ›Research, systems and ventures are shown together, with maturity and boundaries visible before the detail.
A doctoral research programme studying severe acute malnutrition across evidence, structural risk and longitudinal treatment decisions.
Role Doctoral researcher and quantitative lead
Research collaboration ›An evidence-led policy landscape and interoperability architecture for stronger health-information systems.
Role Researcher and systems architect
Request briefing ›A browser-based intelligence and research workbench spanning discovery, monitoring, analysis and production, with capabilities gated by operating mode.
Role Founder and product architect
Product page and beta access ›A local-first editor for creating scientific figures without sending sensitive work to a remote design service.
Role Founder and lead developer
Discuss access ›A climate-informed planning prototype for health supplies, early warning and antimicrobial-resistance decision support.
Role Founder and systems modeller
Discuss a pilot ›Reyanda keeps analysis, design and authoring in one evidence chain so assumptions do not disappear at the handovers.
Define the decision, estimand, causal structure and uncertainty before selecting a method or interface.
Keep source provenance, limitations and human adjudication visible from retrieval through analysis and communication.
See visual evidence methods ›Turn the evidence into a briefing, system, pilot or product that fits the people and institutions responsible for acting.
See authoring methods ›Reyanda brings together clinical, statistical, policy and engineering practice in one team, across global health, development and scientific technology.
The platform exists to connect work that is usually separated: rigorous research, institutional decision systems and the technology needed to make evidence usable. It runs an advisory practice, an active doctoral research programme, a social-protection and food-policy portfolio, and a set of public-interest ventures.
About Reyanda ›Start an advisory brief, propose a research collaboration, or discuss a venture pilot.