Catch the cracks before the collapse.

1. 01 Sampling

   A swab in under a minute.

   The athlete takes the sample themselves, in the changing room, with no needle and no medical staff present. The tube is scanned to the athlete, then shipped to our laboratory.

   SamplingA swab in under a minute, taken by the athlete

   ScanThe tube is bound to the athlete before it leaves the room

   ShipSent to our own laboratory
2. 02 Biomarkers

   Biomarkers become one indicator.

   We measure more than 60 biomarkers by mass spectrometry. Related markers that move together are aggregated into a single indicator, so staff read one status per area rather than 60 numbers.

   MeasureMass spectrometry, in our own laboratory

   Biomarkers60+ per sample

   IndicatorsRelated markers grouped by what they say together

   AggregateOne status per area, not 60 numbers
3. 03 Context

   The stressor behind the signal.

   An indicator on its own says something changed, not why. So we bring the context in alongside it: what the athlete reports and what staff observe, and the objective load data your systems already hold: GPS and tracking, heart rate, movement, force plates. The same swab is then read against the week that produced it.

   Subjective

   • Wellness and readiness questionnaires
   • What staff see day to day

   Objective

   • GPS and tracking
   • Heart rate and movement
   • Force plates and jump testing

   

   

   

   

   

   

   

   CSV & API

   Read togetherThe indicator, and the load that explains it
4. 04 Insights

   Every athlete is their own baseline.

   A value means little against a population average. Each indicator is read against that athlete’s own range, built from their previous samples, so a flag means this athlete has moved away from their normal.

   HistoryEvery previous sample from this athlete

   Own rangeAn individual baseline per indicator

   FlagRaised when the athlete leaves their own normal
5. 05 Action

   A next step, and proof it worked.

   Each flag carries a recommendation, drawn from peer reviewed research and assembled by our multi agent AI against the indicator, its context and the athlete, alongside what has worked for this athlete before. Once staff act, the next samples show whether the indicator came back into range, and that answer feeds the next recommendation.

   Peer reviewed researchAssembled by our multi agent AI

   Your own interventionsWhat has worked for this athlete before

   RecommendDelivered to the person who acts on it, with the reasoning attached

   Re-sampleThe following samples carry the answer

   Back in rangeAnd how fast it got there

   Not yetWhich the next recommendation accounts for

Biomarkers sit next to your staff’s judgement, not instead of it. They work alongside the tools you already use, such as POMS, RESTQ-S, DALDA and sleep diaries.