Privacy-first Clinical Intelligence · Chainlink Convergence

Symptoms happen
continuously.
Care still sees snapshots.

MedGuardian turns symptom logs and wearable-style vitals into structured clinical timelines, consent-gated access, AI-supported doctor briefs, and auditable workflow receipts.

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Consent-Gated Access
Clinician in Control
Auditable Workflow
Verifiable Receipts
Cost Telemetry
Privacy-First by Design
Presentation

See the MedGuardian system in motion.

This is the full product presentation from the actual repo build: clinical timeline, consent flow, AI-supported review, and receipt-backed workflow coordination in one continuous walkthrough.

Full walkthrough 154 sec 1080p
Longitudinal patient timeline

Structured symptom history, drift, and context brought into one usable clinical view.

Consent-gated clinician access

Approval gates and redaction rules stay visible in the workflow instead of hiding behind claims.

Receipts and proof metadata

Chainlink-linked workflow evidence, cost telemetry, and traceable actions shown in-context.

The Problem

Healthcare loses signal between appointments.

Patients experience symptoms over days, weeks, and months. Clinicians often must make decisions from short visits, partial recollection, scattered messages, and isolated readings. That gap is where risk gets missed.

MedGuardian closes that gap by turning ongoing patient input into structured clinical context without giving up privacy or accountability.

What patients live
Continuous symptom drift
Worsening vitals over time
Medication adherence issues
Follow-up tasks and concerns
Red-flag language signals
Daily pattern shifts
What care usually sees
A short appointment window
An isolated clinical note
Fragmented patient memory
Delayed follow-up loops
Incomplete context
No longitudinal picture
The System

One system. Four layers of trust-aware care intelligence.

01 / PATIENT
Patient Layer
Log symptoms through chat or manual input. Track trends, reminders, and ongoing care tasks in a patient-first flow that never exposes raw data without consent.
02 / INTELLIGENCE
Clinical Intelligence
Extract symptom events, maintain longitudinal memory, detect worsening patterns, flag red-alert language, and prepare structured doctor briefs ready for review.
03 / REVIEW
Clinician Review
Doctors request access, patients approve or deny it. Clinicians review evidence inside a controlled workflow that keeps them, not the model, in charge of decisions.
04 / PROOF
Proof + Workflow
Chainlink-backed workflows generate auditable receipts, track important actions, and support verifiable coordination across every step of the care operation.
How It Works

From symptom log to accountable care action.

01
Patient logs symptoms or new vitals enter the system.
Input via chat interface or passive sensor feed. Timestamps recorded. Raw readings isolated from the presentation layer immediately on ingestion.
Patient Layer
02
Raw data is secured. Redacted summaries are prepared.
Sensitive readings are stored with commitment-backed references. Redacted summaries surface first. Deeper access requires explicit approval.
Consent Gate
03
Intelligence layer structures events and detects risk drift.
Symptom events are extracted, memory is maintained longitudinally, worsening patterns are flagged, and a structured doctor brief is composed for review.
Intelligence
04
Clinician requests access. Patient approves or denies.
No access is granted without an explicit consent transaction. The approval event is recorded and linked into the audit chain before the timeline is revealed.
Consent Gate
05
Clinician reviews timeline and validates a care plan.
AI-supported context is surfaced alongside the longitudinal record. The clinician reviews, decides, and validates. The model assists but does not act unilaterally.
Clinician Review
06
Chainlink CRE orchestrates steps and generates receipts.
Each workflow step is executed through Chainlink CRE. Receipts are generated with cost metadata, proof hashes, and timestamp records for every action.
Chainlink CRE
07
Every important action becomes traceable.
Audit data and receipt metadata persist. The system can be inspected, not just trusted. Cases requiring broader support escalate into the professional task network.
Proof Chain
Trust Architecture

Privacy here is not a feature.
It is the architecture.

MedGuardian separates raw vitals from what the interface reveals, introduces consent before exposure, links sensitive events into an audit chain, and produces receipts for workflow accountability.

Raw Data Stays Protected
Underlying vitals and sensitive inputs are never surfaced without an explicit consent transaction first clearing the access gate.
Redacted Summaries Come First
The default view is always a redacted representation. Access to underlying detail requires a recorded approval that becomes part of the audit trail.
Consent Controls Deeper Access
Every access request and approval is a discrete event, timestamped, linked, and verifiable independently of the platform's own records.
Important Events Are Hash-Linked
Key events in the symptom timeline and care workflow are linked into a commitment chain, making after-the-fact alteration detectable.
Workflow Receipts Provide Provenance
Every Chainlink-executed workflow step generates a receipt containing gas cost, latency, proof hash, and provider attribution, readable by any party.
Onchain and Simulated Modes Marked
The system clearly distinguishes between fully onchain execution and simulated demo modes. There is no ambiguity about what is verified and what is staged.
Live System

The receipt model, in detail.

Every workflow action surfaces cost metadata, proof hashes, and consent records. Inspectable, not just stated.

Workflow Receipt · CRE-2847
step clinician_access_granted
timestamp 2025-03-11T09:14:38Z
patient_consent APPROVED
consent_tx 0x4a8f...c3d1
timeline_hash sha256:9c3b...f01e
gas_used 0.000412 ETH
latency_ms 847
mode sepolia_testnet
Risk Signal · Patient-0039
condition Brittle T1 Diabetes
risk_level ELEVATED
events_7d 14 logged events
flag_trigger hypoglycemia_drift
brief_ready TRUE
clinician_notified TRUE
memory_span 28 days
last_review 2025-03-09T14:22:00Z
Clinical Complexity

Tested against hard-to-track patient realities.

MedGuardian is designed for longitudinal complexity, not idealized single-event demos.

CASE-001
Brittle Type 1 Diabetes
hypoglycemiaglucose driftwearable
CASE-002
Resistant Hypertension + Sleep-Apnea Signals
multi-conditionbp trackingovernight
CASE-003
Long COVID with Dysautonomia
chroniclongitudinalfatigue signals
CASE-004
Paroxysmal Atrial Fibrillation
cardiacevent detectionecg correlation
Mission

Better care needs more than intelligence. It needs trust.

Healthcare AI often fails in predictable ways: patients do not trust where their data goes, clinicians do not trust opaque recommendations, and teams cannot prove what happened inside the workflow.

MedGuardian is built to make the flow inspectable, consent-aware, and accountable. Not just intelligent, verifiably trustworthy.

Ready

See a privacy-preserving clinical workflow,
not just another AI demo.

Explore how MedGuardian turns symptom timelines, clinician review, Chainlink-audited workflows, and verifiable receipts into one accountable care coordination system.

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