From a new result to a clear finding, and a check on how well changes are caught.
IngestionHow information enters the system.
HistoryHow results build up over time.
AnalysisHow change and patterns are found.
FindingsHow it becomes understandable.
EvaluationHow accurately changes are caught.
Prototype interface. Not a clinically validated diagnostic system.
Future
Health intelligence, built into everyday life.
ConceptFlagship hardware direction
EDDS aims to connect the signals that shape human health from what we eat and how we live to our surrounding environment, wearable devices, portable diagnostics and smart sanitary systems through one intelligence layer. Our long-term vision is to make health monitoring more continuous, accessible and seamlessly integrated into everyday life, including within the home.
Smart sanitary systems are part of our future product vision and remain at the concept stage. Future monitoring systems must respect privacy, consent and data protection.
Concept illustration of a future home experience. Not a current product.
The problem
Results without context.
Most health assessments are captured as single points in time. Read in isolation, they can miss the trajectory: what is changing, how fast and from what baseline.
The concept
Longitudinal biological intelligence.
Biological understanding improves when information is organised over time, compared against a relevant baseline and interpreted in context.
Normal for everyone, or normal for you?
Move the new result. A value can sit inside the population reference range and still be unusual for one person.
Against the population
Within the population range
Against this person
Within this person's usual band
Try 240: inside the population range, but 20% below this person's baseline.
Under the hood
Statistics first, then AI.
EDDS uses statistical methods to establish a personal baseline and flag meaningful change. The AI layer works on that structured output to help summarise patterns, and medical experts review the findings.
03 · CapClinician reviewFindings are reviewed by medical experts before they mean anything.
02 · InterpretationAI interpretation layerSummarises the statistical output in plain language.
01 · FoundationStatistical foundationPersonal baseline and change detection across results over time.
What EDDS works with
Markers and sources.
The prototype works with laboratory results today. The EDDS Bio-Baseline Engine tracks 21 laboratory biomarkers across six categories. Other sources are on the roadmap, and each one is labelled for where it stands.
Haematology
Prototype
Blood composition and oxygen-carrying capacity. The markers we are working with in the prototype.
Haemoglobin HB
Red blood cell count RBC
Haematocrit HCT
Mean corpuscular volume MCV
Mean corpuscular haemoglobin MCH
Mean corpuscular haemoglobin concentration MCHC
Red cell distribution width RDW
Platelet count PLT
Mean platelet volume MPV
Data sources
Where results come from.
Laboratory reports Today
Portable diagnostics Future
Wearables Future
Smart sanitary systems Concept
21 biomarkers, six categories.
The breadth of laboratory information the Bio-Baseline Engine is designed to organise and interpret.
9 Haematology
Blood composition and oxygen-carrying capacity
4 Inflammatory
Immune and inflammatory activity
2 Renal
Kidney function
2 Metabolic
Glucose regulation
2 Hepatic
Liver function
2 Urinalysis
Markers from urine analysis
Development stage
Where EDDS stands.
What we have, what we're developing and where we're going.
Today
Working prototype
A functional prototype that demonstrates the platform concept. It is not a clinically validated diagnostic system.
Developing
Clinical evaluation
A pathway from prototype toward structured clinical evaluation and, eventually, validation.
Future
Connected monitoring
Hardware that brings new health signals into EDDS, led by smart sanitary systems. See the vision
See EDDS work, step by step.
Follow one sample profile from a new lab result to a reviewed finding.
