Health Intelligence
Can You Trust a Health App? How Enbodie Uses Evidence
Darren Crowder · · 3 min read
If an app is going to tell you something about your health, you deserve to know where that comes from.
Trust is fundamental to Enbodie. We don’t want anyone making decisions about their health based on vague claims, social media trends, or an AI simply guessing what sounds right.
So here is how it works.
Where the data comes from
Our data comes from a combination of scientific, clinical, regulatory and product-level sources. Depending on what Enbodie is looking at, that can include:
- Peer-reviewed scientific and medical research
- Clinical guidance and specialist organisations, including dermatology and eye-health research
- Government and regulatory sources covering ingredients, chemicals, medicines and product safety
- Scientific databases such as PubChem, and toxicology datasets
- Dermatology resources such as DermNet, and large skin-image datasets that help us represent every skin tone
- Eye-health research and guidance, including work from organisations such as TFOS
- Ingredient and formulation information, including INCI ingredient lists and published product information
- Manufacturer and product-label data
- Environmental data, where air quality, water and other exposures may be relevant
- Enbodie’s own structured and validated datasets, which bring all of this together so it can be assessed consistently
Why one source is never enough
A single source can be out of date, incomplete, or written for a different country or a different kind of product.
So we don’t take one source and treat it as the answer. Enbodie brings several pieces of evidence together, looks for agreement or conflict between them, and then applies what it finds to the individual person.
When sources agree, that gives more confidence. When they disagree, that is a reason to look more closely, not to pick whichever answer is most convenient.
You should be able to see why
A score on its own doesn’t help much if you can’t see how it was reached.
Where possible, we want you to understand why something has been highlighted, what the evidence says, and why it may matter to you. An explanation lets you judge it for yourself, and take it to a professional if you want a second opinion.
AI explains, rather than decides
This is the most important design choice we have made.
Enbodie is built so that AI doesn’t invent a health answer. The underlying data, evidence and rules drive the assessment. AI is then used to make that information easier to understand, in plain language.
In other words, the AI is a translator, not the judge. If the evidence isn’t there, the right answer is to say so, not to fill the gap with something that sounds plausible.
Evidence first. Personal context second. AI explains, rather than decides.
The goal
Our goal is simple: to give you information that is understandable, explainable and grounded in evidence, so you can make a better-informed decision.
Enbodie doesn’t diagnose medical conditions, and it isn’t a substitute for professional medical advice. It is there to help you understand more, earlier, and to know when it is worth speaking to a professional.
Trust isn’t something an app can ask for. It has to be earned, one clear answer at a time, and that is exactly how we intend to earn yours.