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Evidence & safety centre

Useful AI must also be
responsible AI.

NivaCare is designed around declared intended use, qualified human oversight, consent, traceability and validation appropriate to each capability and deployment setting.

Our safety positionAI supports care. People remain accountable.
01
Intended use definedEach capability is scoped to a specific workflow and user.
02
Human review retainedClinical decisions remain with qualified professionals.
03
Limitations disclosedPerformance boundaries and uncertainty are part of deployment.
Responsible by design

Six questions every clinical AI deployment should answer.

These principles guide product design, implementation review and the way NivaCare communicates its capabilities.

Intended use

What is it for?

The user, care setting, task and excluded uses should be explicit before rollout.

Human control

Who reviews it?

Drafts, signals and recommendations stay subject to appropriate professional review.

Evidence

How was it evaluated?

Performance should be assessed using representative data and fit-for-purpose measures.

Equity

For whom does it work?

Language, dialect, age, gender, device and location differences require active evaluation.

Data governance

What information is used?

Consent, purpose, access, retention and traceability must match the workflow.

Escalation

What happens when uncertain?

Low-confidence, unexpected and high-risk situations need a clear human pathway.

Current readiness language

Clear status, without implying certification.

Standards alignment, technical conformance and formal certification are different. NivaCare labels them separately.

Technical architecture

FHIR-native

Designed to exchange structured healthcare information using FHIR-oriented architecture. Integration conformance is verified for each implementation.

Designed for alignment

DPDP, ABDM & NABH-oriented

Product and workflow controls are designed with these Indian requirements and frameworks in view. This does not itself represent accreditation or endorsement.

Privacy safeguards

HIPAA-aware design

Administrative, technical and organisational safeguards are considered for relevant deployments. NivaCare does not claim HIPAA certification.

Certification in progress

ISO 13485

Quality-management certification work is in progress. Certification is not yet complete.

Capability validation

Deployment specific

Clinical and operational validation depends on intended use, specialty, language, population, device and implementation scope.

Regulatory assessment

Use-case specific

Regulatory status is assessed against the intended claims and functions before clinical deployment. No blanket regulatory approval is implied.

Important

NivaCare product pages describe a design direction and illustrative workflows. They do not replace local clinical governance, validation, contracting or regulatory assessment.

High-risk capability boundaries

What the platform does not claim.

Clear exclusions are essential when software may influence health decisions.

Mental wellbeing

Screening support, not diagnosis

Voice and questionnaire analysis can only surface a possible signal for consented, qualified review. It cannot diagnose a mental health condition or manage emergencies.

Digital Twin

Scenario support, not prediction

Illustrative treatment-response scenarios do not prescribe, guarantee an outcome or replace current evidence and clinical judgement.

AI Care Agents

Coordination, not autonomous care

Agents can organise, draft and route information within configured rules. They do not independently diagnose, prescribe or override a clinician.

Evidence roadmap

From useful prototype to trusted workflow.

We favour a staged approach: define, test, pilot, monitor and expand only when the evidence supports it.

01Define

Intended use, users, exclusions and success measures.

02Evaluate

Technical, usability, bias and safety performance.

03Pilot

Prospective use with oversight and documented escalation.

04Monitor

Version, drift, incidents, feedback and real-world performance.

Reference points

Guided by recognised frameworks.

Relevant references are applied according to each capability, claim, geography and deployment scope.

Responsible health AI

WHO ethics & governance

Human autonomy, transparency, accountability, equity and sustainable use inform the governance approach.

WHO guidance ↗
India digital health

ABDM ecosystem

Patient control, consent-aware exchange and interoperable architecture inform connected-care design.

ABDM ↗
Medical software

CDSCO assessment

Regulatory assessment depends on intended claims, functions and risk. It is not inferred from a technology label.

CDSCO ↗

Assess NivaCare against your governance process.

Tell us the intended clinical setting, users and workflow. We will discuss scope, controls, evidence and deployment requirements transparently.

Start a governance conversation ↗