GaitAI PrivacyGuard
Movement intelligence — with task-relevant movement representations.
PrivacyGuard is the architectural privacy-control layer for SecureVision, designed to support skeleton-only analytics, face blur, privacy-aware aggregated heatmaps, role-based access, audit logs, retention controls and consent/policy logging. What a given site enables is a deployment decision.
Problem
Useful spatial intelligence should not require unrestricted retention of identifiable video.
What GaitAI does
PrivacyGuard enforces movement-first processing: optional face blur and skeleton extraction happen before analytics, access is role-based and audited, and retention is configurable per policy.
Who uses it
- Every SecureVision customer
- Public-sector deployments
- Privacy-sensitive enterprises
- Compliance and legal teams
What they receive
Example report values — illustrative, not measured performance claims.
PrivacyGuard is described accurately as privacy-aware, privacy-first architecture — it minimises identifiable data and governs access. It is not a claim of guaranteed anonymity.
Why it matters
Privacy controls applied at the pipeline level — before analytics — make SecureVision deployable in environments where raw-video surveillance would be unacceptable or unlawful.
Example workflow
- 01Streams enter the pipeline
- 02Optional face blur is applied
- 03Skeleton / movement extraction replaces identifiable video for analytics
- 04Role-based dashboards expose only permitted views
- 05Every access and policy change is logged
Deployment
- Policy configuration per site and per role
- Retention schedules per data class
- Audit-log export for compliance review
- Applies across all SecureVision products
Research basis
Published work is the research foundation for the capabilities this product is built on. That record covers the movement-analysis methods themselves — it is not a validation of this product's outputs, and there is no clinical validation study, accuracy benchmark or trial result behind them.
- Privacy-aware analytics
- Privacy-preserving gait data
Evidence status
GaitAI Evidence Index
2 categories documented
What is documented for this module, and what is not. Research foundation is not product validation — the two are listed separately on purpose.
- Research foundationAvailable
- 1 published record directly addresses a capability this module is built on (Privacy-preserving gait data).
View evidence for Research foundation
Claim / capability: 1 published record directly addresses a capability this module is built on (Privacy-preserving gait data).
Status: Available
Applicability: The cited work is specifically about a method or movement signal this module draws on.
Limitation: Research relevance is not evidence that this product's outputs have been validated.
Inventory reviewed .
- Architectural research relationshipNot yet published
- No further shared-platform research relationship is recorded beyond the research foundation above.
View evidence for Architectural research relationship
Claim / capability: No further shared-platform research relationship is recorded beyond the research foundation above.
Status: Not yet published
Applicability: Shared capabilities such as pose estimation or temporal modelling are used by many modules.
Limitation: A shared-platform relationship is the weakest research link and must not be read as validating this module.
No supporting source is published for this status.
Inventory reviewed .
- Product specificationAvailable
- The module has a documented specification: inputs, pipeline, outputs and stated limitations.
View evidence for Product specification
Claim / capability: The module has a documented specification: inputs, pipeline, outputs and stated limitations.
Status: Available
Applicability: Documented inputs, intended workflow and output design.
Limitation: Documentation does not establish a released implementation or deployment readiness.
- specificationProduct documentation
Inventory reviewed .
- Product implementation evidenceNot yet published
- No module-specific release or deployment record is published here.
View evidence for Product implementation evidence
Claim / capability: No module-specific release or deployment record is published here.
Status: Not yet published
Applicability: Production implementation is distinct from this website's interactive prototypes.
Limitation: The browser pose explorer is not the full clinical or operational product pipeline.
- Context · not validation evidenceProduct and deployment context
Inventory reviewed .
- Interactive demoNot yet published
- No sample output has been built for this module yet.
View evidence for Interactive demo
Claim / capability: No sample output has been built for this module yet.
Status: Not yet published
Applicability: An interactive explanation of the intended output and workflow.
Limitation: Sample outputs contain illustrative values and are not measurements of a visitor or product performance.
No supporting source is published for this status.
Inventory reviewed .
- Benchmark validationNot yet published
- Validation pending publication. No product benchmark numbers are supplied.
View evidence for Benchmark validation
Claim / capability: Validation pending publication. No product benchmark numbers are supplied.
Status: Not yet published
Applicability: A benchmark needs a defined dataset, sample count, environment, hardware and evaluation method.
Limitation: Accuracy, sensitivity, specificity, latency and FPS cannot be inferred from a demonstration.
- Context · not validation evidenceResearch evidence inventory
Inventory reviewed .
- Product-specific validationNot yet published
- No study in the published record evaluates this module's output for a particular intended use.
View evidence for Product-specific validation
Claim / capability: No study in the published record evaluates this module's output for a particular intended use.
Status: Not yet published
Applicability: Validation must match the module, population and intended decision.
Limitation: A product description or related research paper does not establish validated performance.
- Context · not validation evidencePublished evidence inventory
Inventory reviewed .
- Pilot & deployment evidenceNot yet published
- No named pilot, deployment result or customer outcome is documented.
View evidence for Pilot & deployment evidence
Claim / capability: No named pilot, deployment result or customer outcome is documented.
Status: Not yet published
Applicability: Pilot and deployment evidence is assessed separately from research.
Limitation: Use-case journeys describe intended workflows, not customer results.
- Context · not validation evidenceTrust Center
Inventory reviewed .
- Product-specific clinical validationNot yet published
- No product-specific clinical validation study is published in this library.
View evidence for Product-specific clinical validation
Claim / capability: No product-specific clinical validation study is published in this library.
Status: Not yet published
Applicability: Clinical applicability depends on the intended use; safety modules are not presented as clinical tools.
Limitation: No output replaces clinician judgement or establishes a diagnosis.
- Context · not validation evidenceResponsible use and intended context
Inventory reviewed .
- Regulatory clearanceNot claimed
- No medical-device clearance, regulatory approval or compliance status is claimed.
View evidence for Regulatory clearance
Claim / capability: No medical-device clearance, regulatory approval or compliance status is claimed.
Status: Not claimed
Applicability: Regulatory applicability depends on the intended use and deployment jurisdiction.
Limitation: Research publications, patents and prototypes are not regulatory clearances.
- Context · not validation evidenceWhat GaitAI does not claim
Inventory reviewed .
Inventory reviewed How GaitAI states evidence →
Privacy & responsible use
Designed to support consent-based capture, encrypted transfer, configurable retention and role-based access, with activity logging and skeleton-only processing modes. Deployment requirements depend on the applicable environment, organization and jurisdiction. Privacy-aware architecture does not automatically mean anonymity: pose, gait and trajectories may still carry identifying information. Movement analytics are designed to run without identifying individuals unless a deployment lawfully and explicitly requires it, and identity-related capabilities are intended only for lawful, authorized deployments with appropriate governance, access control and auditability. Outputs are decision support for trained operators — not autonomous enforcement.
Context & limitations
- Privacy-aware architecture, not a guarantee of anonymity
- Lawful-basis and policy decisions remain with the deploying organisation
- Controls govern the GaitAI pipeline, not external systems
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