SenseA health signal enters
Canadian medtech AI R&D
Intelligencethat stayswith the signal.
QualiMed AI develops the Closed-Loop Node—safety-constrained intelligence that connects a health signal to context, an approved response, and verified follow-through. LimbSense AI is its first research application.
QualiMed AIR&D platformClosed-Loop NodeFlagship R&D projectLimbSense AIFirst medtech application
Flagship R&D projectClosed-Loop Node
ValidateVerify signal quality
UnderstandCompare personal context
ActStart approved support
ConfirmVerify follow-through
LearnEvaluate the outcome
Research use only
This website describes research-stage technology—not a diagnostic device, treatment service, replacement for clinical care, or emergency resource.
Technology
One connected intelligence architecture.
The Closed-Loop Node brings wearable sensing, personal context, bounded agent behaviour, and action verification into one observable research system.
Safety-constrained agents
Controlled workflows designed to explain, ask, remind, coordinate, and escalate within explicit boundaries.
Wearable sensing
Hardware-agnostic research across smart textiles, insoles, liners, sensor pods, and connected devices.
Personal-state intelligence
Longitudinal models that compare a new signal with a person’s own recent pattern while keeping uncertainty visible.
Action verification
Research infrastructure that follows a signal beyond the alert and records whether the next step was completed.
Flagship R&D projectThe Closed-Loop Node.
The Closed-Loop Node.
An alert isn't the outcome. Action is.
Traditional monitoring often ends with a notification. The Closed-Loop Node follows what happens next—and whether the intended action was completed.
01→
Sense
Collect longitudinal signals from a wearable, person, or connected workflow.
02→
Validate
Check quality, freshness, provenance, completeness, and confidence.
03→
Understand
Compare the change with personal history, context, and approved rules.
04→
Act
Select a bounded prompt, check-in, reminder, or escalation pathway.
05→
Confirm
Verify that the requested follow-through occurred—or remains unresolved.
06
Learn
Measure the workflow offline and improve future research versions.
Return to the signal. Outcomes become part of the next observable state—without silently changing production behaviour.
Guardian Engine · inside the Node
The intelligence inside every transition.
Inside the Node, the Guardian Engine evaluates signal quality and context, selects only permitted actions, and records follow-through.
Guardian EngineOrchestration coreResearch model
Bounded orchestration
Policy-governed workflows with traceable evidence.
01Inputs02Policy03Workflow04Evidence
Signal Intelligence
Ingests multimodal data and evaluates integrity, freshness, missingness, and signal confidence.
Personal State
Maintains a longitudinal research view of individual patterns, context, and recent change.
Safety-Constrained Agent
Chooses only from approved communication, support, and escalation workflows.
Action Verification
Tracks acknowledgement, consent, follow-through, and unresolved workflow states.
01Research Program 01
LimbSense AI
Closed-loop intelligence for diabetic foot monitoring research.
LimbSense AI applies the Closed-Loop Node to diabetic foot-monitoring research. It studies whether multimodal sensing and personal-state modelling can support timely awareness and safer follow-through between clinical visits.
Research-stage scope
No diagnostic, treatment, or clinical-performance claims. Initial work uses simulated or non-identifiable data and off-the-shelf sensing components.
Hardware-agnostic researchSmart textile · insole · liner · sensor pod · hybrid
01Temperature02Pressure03Moisture04Gait05Wear time
01Wearable / sensor→
02Guardian Engine→
03Patient check→
04Caregiver support→
05Future professional review→
06Confirmed action
Example bounded language
“Your foot pattern looks different from your recent normal. Please check your foot today. If you notice a concerning change, contact your healthcare provider promptly.”
Research focus
What happens after the signal changes?
We study whether a bounded system can turn a reliable signal into an appropriate, traceable next step.
Longitudinal personal-state modelling
Wearable-data confidence
Multimodal pattern analysis
Safety-constrained agent behaviour
Action completion
Explainability and auditability
Agent Lab
A transparent test environment.
Agent Lab uses simulated scenarios to inspect bounded-agent decisions and compare behaviour across approved policy and model versions.
Explore Agent LabAGENT LAB · SCENARIO QL-LS-014SIMULATED RESEARCH DATA
SenseValidateUnderstandActConfirmLearn
Simulated patient profileLS-014 · cohort A
Sensor stream5 channels · active
Baseline stateEstablished · 28 days
Signal confidence0.84 · review
Agent decisionRequest self-check
Selected workflowWF-03 · bounded
Action statusAcknowledged
Caregiver consentNot enabled
Escalation statusNot triggered
Model versionGuardian v0.1.6
Audit trail
- 09:41:04 Signal batch validated · 5 channels
- 09:41:05 Personal-state comparison completed
- 09:41:05 WF-03 selected within policy boundary
- 09:44:18 Patient check acknowledged · outcome pending
Research demonstrator · not for clinical useModel and policy versions recorded
Safety architecture
Clear operating boundaries.
Research workflows use explicit permissions, controlled actions, visible uncertainty, human review, and a complete decision trace.
No autonomous diagnosis
Research outputs are not presented as a clinical diagnosis.
No autonomous treatment
The system does not prescribe, select, or change treatment.
Controlled escalation pathways
Agents operate inside predefined, testable workflow boundaries.
Human review and traceability
Clinical judgment remains with qualified people, while every system decision remains inspectable.
Mission
Keep intelligence connected to the signal, the person, and the outcome.
Without moving clinical judgment out of human hands.
Canadian medtech AI R&D
From sensing to verified follow-through.
QualiMed Inc. is a federally incorporated Canadian health-technology company established in 2019. QualiMed AI is its research initiative, developing the Closed-Loop Node and its first application, LimbSense AI.
PM
Pruthal Merchant, P.Eng., PMP®Founder & CEO · QualiMed Inc.Vision
A future where important health signals do not disappear between devices, people, and care teams.
2019Federal incorporationCanadaCompany baseResearch stageCurrent maturity
Partner with us
Build the evidence with us.
We welcome conversations with clinical, technical, regulatory, academic, and applied-research collaborators.
Start a research conversationCollaboration pathways
Clinical
Research questions, care workflows, safety boundaries, and future evaluation.
Technical
Wearable sensing, multimodal data, modelling, agent evaluation, and human factors.
Institutional
Partner with QualiMed AI Applied research, academic collaboration, incubation, and funding pathways.