ZKOMI · ZERO KNOWLEDGE INTELLIGENCE LAYER
Zkomi is the intelligence layer beneath four platforms — designed to process sensitive health information entirely on your own device. Nothing is transmitted to our servers. Nothing is stored beyond your control.
The system knows everything about your protocol. We know nothing.
WHY THE FOX EXISTS
Zkomi is not a mascot.
Most health platforms create mascots to appear friendly.
Zkomi uses the fox differently.
The fox represents the intelligence layer itself — a system that understands the user’s protocol deeply while revealing nothing about the user to the platform operator.
It is a visual metaphor for Zero Knowledge architecture.
Quiet observation without possession.
Intelligence without surveillance.
Guidance without centralisation.
The fox does not symbolize a brand personality.
It symbolizes a technical position:
the system can process highly sensitive health information without the company ever owning that information.
This distinction matters.
Because once the architecture is understood, the ecosystem stops looking like a wellness brand with a character — and starts looking like privacy-first health infrastructure.
The fox knows everything about your protocol. We know nothing about you.
WHAT ZERO KNOWLEDGE MEANS
Zero Knowledge systems are often described in cryptographic terms — proving something without exposing the underlying data. In practice, for health technology, it means something more human:
the company providing the service genuinely cannot see what the user is doing.
Zkomi is built around device-local computation.
Your body clock calculations, peptide timing adjustments, cold-chain exposure tracking, supplier verification checks, and travel protocol logic all run directly on your own device.
Results stay local.
They are not transmitted to our servers.
They are not stored in a central database.
They are not exposed to advertisers, data brokers, or future breaches.
This is not a setting users need to enable.
It is simply how the system is built.
The fox understands your protocol.
We do not know who you are.
WHERE ZKOMI RUNS
Zkomi processes body clock position, peptide timing, cold-chain exposure, travel adaptation, and compound-specific dosing logic entirely on-device. Nothing identifying the user or their protocol leaves the device. The result is contextual guidance based on biological time, not simply local clock time.
“Take BPC-157 at 14:00 today. Your body clock is still anchored to Miami.”
Zkomi supports community destination intelligence — including clinic discovery, customs guidance, pharmacy preparation, timezone adaptation, storage considerations, and protocol continuity during travel, biohacker and longevity events and conferences, meetups by town and country. Only anonymous destination-level queries are processed externally. No protocol identity is attached to searches.
“Your body clock will take six days to adapt eastbound. Two verified clinics are nearby. A local-language pharmacy card has been prepared.”
Zkomi handles supplier verification queries, trust signals, and anonymised quality intelligence while protecting the identity of the individual user. The user sees verification. The supplier does not see the individual behind the request.
Compound stability intelligence, storage protocol matching, temperature exposure windows, reconstitution workflows, degradation risk factors, transport conditions, handling protocols, compound interaction flags, supplier-linked storage guidance, and personalised research queries. Aggregate intelligence signals only leave your device — such as which compounds are searched, which stability questions are most common, and which storage scenarios users encounter most frequently. Never linked to a personal identity, protocol, or health profile. Locally, Zkomi calculates whether your compounds remain within stability thresholds under your exact storage conditions, which storage protocol applies to your stack, reconstitution timing guidance, cold-chain exposure risk, transport viability during travel, compound-specific handling considerations, and storage compatibility across multi-compound protocols. The result is a continuously evolving compound intelligence system — not just storage instructions. Personalised protocol preservation without creating a centralised health profile on our servers.
THE CORE ENGINE
The body clock engine is the core calculation layer beneath Zkomi.
It runs entirely on-device using pure TypeScript.
No network requests.
No cloud processing.
No server-side dependency.
The engine has been tested across multiple travel routes and timing scenarios, including long eastbound and westbound adaptation cycles.
Four user inputs:
— Home city
— Departure datetime
— Destination city
— Compound timing type
The system calculates:
Biological clock position (T_bio)
Jet lag adaptation score
Dose timing windows
Cold-chain timing continuity
Protocol sync state
T_bio = home offset + hours adaptedT_bio = home offset − hours adaptedJ = 1 − (hours adapted / total shift)Eastbound = 1 hour/dayWestbound = 1.5 hours/dayYou are synced.All processing remains local.
All protocol intelligence remains private.
The calculation is straightforward. The trust is not replicable.
THE DIRECTION OF HEALTH TECHNOLOGY
Health technology is slowly moving toward local-first systems.
Apple Health increasingly processes data on-device.
Wearables are reducing cloud dependence.
Regulators globally are moving toward stronger user ownership of personal health information.
Zkomi was designed around those assumptions from the beginning.
The value of the system is not only the calculations.
It is the trust required for users to provide honest health data in the first place.
Architecture becomes the moat.
PLATFORM POSITIONING
This is not a wellness app. It is health data infrastructure.
Four platforms.
One intelligence layer.
No centralised protocol database.
Revenue comes from subscriptions, verification systems, and infrastructure services — not advertising or data monetisation.
Pre-seed conversations are open.
Email: fox@peptidenomad.com
We are happy to discuss the technical implementation, privacy model, and Zero Knowledge approach with users, partners, investors, and regulatory groups.