syncThesis
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Health Intelligence Platform

Every device, one timeline.

Your medical devices record in silos — each one, its own report. syncThesis brings them onto one timeline and cross-references them, to show what no single device can on its own.

Live · access by invitation Enter the HIP →
The modules
One platform, every signal.

Each device family is a plug-in: a decoder that reads its raw format and a normalizer that maps it to one shared schema. Adding a model is a row, not a rewrite.

M1
Therapy machines
CPAP · BiPAP · APAP — pressure, flow, leaks, AHI.
AEONMEDPhilipsLöwenstein
M2
Sleep studies
Polysomnography — multi-channel, OSA vs CSA, position.
VentMed
M3
Oximetry
SpO₂ · pulse — ODI, nadir, time below 90%.
CONTEC
M4
Wearables
Continuous 24/7 — heart rate, sleep, recovery.
Fitbitany BLE
How it works
Raw signal, cross-referenced insight.
01
Ingest
Any device, format-aware. The proprietary binary is read, never guessed.
02
Normalize
Every signal maps to one shared schema — the common layer across brands.
03
Cross-reference
All sources on one absolute timeline — the combined study no single device can show.
04
Insight
Our own metrics, validated against the device's own — and honestly caveated.
Partner Connect
Your data. Your consent.

A third-party app reads a consenting patient's signals through an OAuth2 gateway — de-identified at the boundary, scoped to the exact data granted, every read audited. Consent is the token; withdraw it and the door closes.

Partner appConsent gatewayPatient signal
token ∧ scope ∧ consent ∧ patient-scope · de-identified · audited
Combined study · one nightsyncThesis
M1
M2
M3
M4
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