Healthcare Biometrics Market by Biometric Type (Ecg Recognition, Face Recognition, Fingerprint Recognition), Component (Hardware, Services, Software), End User, Application, Deployment - Global Forecast 2025-2032
Description
The Healthcare Biometrics Market was valued at USD 10.89 billion in 2024 and is projected to grow to USD 11.86 billion in 2025, with a CAGR of 9.16%, reaching USD 21.96 billion by 2032.
A concise and authoritative orientation to how biometric technologies are reshaping clinical identity, operational workflows, and patient safety in modern healthcare delivery
Healthcare delivery is undergoing a quiet but profound transformation driven by the need for secure, reliable, and patient-centric identity verification. Biometrics have moved from optional conveniences to foundational elements of clinical workflows, enabling safer patient identification, frictionless access control, and more accurate staff authentication. As electronic health record systems expand and telehealth becomes a persistent channel of care, the role of biometrics in preventing errors, reducing fraud, and enhancing operational efficiency has become increasingly visible.
Moreover, advances in sensor technology, data processing, and machine learning have improved accuracy and reduced latency, making biometric solutions more practical in diverse clinical environments. These developments intersect with rising regulatory focus on privacy and data protection, obliging health systems to balance innovation with patient rights. Consequently, healthcare organizations are prioritizing interoperable solutions that integrate with identity management and clinical systems while complying with evolving policy frameworks. As a result, procurement and implementation decisions now require a cross-functional perspective that weighs clinical impact, IT operability, regulatory adherence, and patient experience.
Emerging technical, regulatory, and interoperability forces that are driving multimodal biometrics, edge processing, and privacy-first architectures across clinical and administrative settings
The landscape of healthcare biometrics is being reshaped by several concurrent shifts that together redefine expectations for performance, privacy, and deployment. First, multimodal approaches that combine physiological and behavioral traits are gaining traction because they substantially improve recognition accuracy under real-world conditions. This technical maturation is reinforced by edge computing, which reduces latency and enables local template storage and matching, thus reducing reliance on continuous cloud connectivity.
At the same time, privacy-preserving techniques such as template protection, differential privacy, and on-device inference are evolving from academic concepts into operational features demanded by healthcare purchasers. Regulators are signaling stricter controls around biometric data, prompting architecture changes that favor encryption, consent management, and auditable access logs. Interoperability is another pivotal shift: interoperability frameworks and standardized APIs are enabling tighter integration between biometric systems and electronic health records, identity management platforms, and workforce management tools. Finally, the convergence of wearable sensors and remote monitoring is expanding biometric use cases beyond static access control toward continuous patient verification and longitudinal monitoring, thereby extending the technology’s clinical relevance.
How tariff-driven supply chain adjustments and sourcing strategies are reshaping procurement, manufacturing footprints, and solution design choices within the healthcare biometrics ecosystem
The introduction of new tariff measures in the United States has created a complex operating environment for suppliers, integrators, and health systems that rely on internationally sourced components. Increased duties on imported hardware and certain electronic assemblies have prompted procurement managers to reassess supplier footprints, prioritize local sourcing where feasible, and consider total cost of ownership rather than unit pricing alone. Consequently, supply chain strategies that once emphasized lowest-cost procurement are shifting toward resiliency, with organizations tolerating higher near-term costs in exchange for reduced lead-time risk and improved compliance visibility.
In parallel, tariff-related frictions have encouraged increased vertical integration by some vendors, who are choosing to internalize manufacturing stages or to shift production to tariff-exempt jurisdictions. For purchasers, this translates into longer vendor qualification cycles and a renewed emphasis on contractual protections around price adjustments and delivery guarantees. Technology decisions are also being affected: organizations are more likely to consider software-centric architectures and cloud-enabled services that decouple costly hardware refresh cycles from feature upgrades. As a result, procurement teams are collaborating more closely with legal and supply-chain functions to design procurement vehicles that mitigate tariff exposure and preserve deployment timelines.
Actionable segmentation insights linking biometric modalities, components, end users, applications, and deployment models to procurement priorities and clinical integration pathways
A granular understanding of segmentation is essential to align product design and go-to-market strategies to clinical needs. When segmenting by biometric type, it is important to account for modality-specific constraints and clinical use-case fit across ECG Recognition, Face Recognition, Fingerprint Recognition, Hand Geometry, Iris Recognition, Palm Recognition, Retina Recognition, Vein Recognition, and Voice Recognition. Each modality brings distinct trade-offs in accuracy, hygiene, user acceptance, and environmental robustness; therefore, solution architects must map modality characteristics to the operational realities of acute care, outpatient clinics, and ambulatory settings.
Component-based differentiation between Hardware, Services, and Software informs partner strategies and margin structures, with hardware vendors increasingly offering managed services and software providers embedding analytics and integration toolkits. End user segmentation that includes Ambulatory Care Centers, Clinics, Diagnostic Centers, and Hospitals reveals divergent procurement cycles, regulatory demands, and integration priorities, so tailored sales motions and pilot designs are essential. Application segmentation across Access Control, Patient Identification, Patient Monitoring, Staff Identification, and Time and Attendance highlights where clinical safety and administrative efficiency intersect, guiding feature prioritization and compliance requirements. Finally, deployment models that span Cloud and On Premises, with the Cloud option further divided into Hybrid Cloud, Private Cloud, and Public Cloud, create distinct operational, security, and integration profiles that influence implementation timelines and total cost considerations.
Strategic regional distinctions and regulatory considerations across the Americas, Europe Middle East & Africa, and Asia-Pacific that influence deployment models and partnership strategies
Regional dynamics shape adoption pathways and regulatory approaches, and understanding geographic nuances is critical for strategic market entry. In the Americas, health systems often prioritize interoperability with extensive electronic records infrastructures and face stringent privacy expectations, driving demand for integrated solutions that support large hospital networks and outpatient systems. Vendor strategies in this region tend to emphasize enterprise-grade integrations, compliance certifications, and partnerships with established IT integrators to navigate complex purchasing processes.
Across Europe, Middle East & Africa, regulatory heterogeneity and diverse infrastructure maturity levels require flexible deployment options and localized compliance expertise. Some countries favor cloud-first strategies, while others mandate local data residency and tailored consent frameworks, which pushes vendors to offer both cloud and on-premises variants and to maintain robust data governance features. The Asia-Pacific region presents a mix of rapid technology adoption in urban centers and constrained resources in lower-income areas, creating opportunities for scalable, cost-effective solutions and strong demand for mobile-first, multilingual interfaces. Taken together, these regional distinctions affect channel strategies, pricing models, and product roadmaps, making geographic adaptation a fundamental element of sustained commercial success.
Competitive landscape dynamics and partnership ecosystems that determine vendor viability through integration readiness, clinical validation, and enterprise supportability
Competitive dynamics in healthcare biometrics are defined by a portfolio of incumbent system integrators, specialized biometric vendors, device manufacturers, and emerging cloud-native entrants. Incumbents benefit from deep relationships with health systems and experience navigating procurement and compliance cycles, while specialized vendors offer modality expertise and faster product iteration. Device manufacturers continue to innovate on sensors and form factors, targeting hygienic designs and ruggedized hardware for clinical settings, whereas software-focused firms differentiate through analytics, interoperability, and identity lifecycle management.
Partnership ecosystems are maturing: technology alliances between biometric specialists and electronic health record integrators or workforce management platforms are becoming common, enabling turnkey offerings that reduce implementation complexity. At the same time, a wave of consolidation among smaller niche players is likely as customers seek vendors that can demonstrate complete security controls, validated clinical workflows, and enterprise-level support. For purchasers, this means vendor selection criteria now emphasize long-term supportability, standards-based integration, and demonstrable clinical outcomes rather than feature lists alone.
Practical and prioritized recommendations for healthcare leaders to accelerate secure, scalable biometric deployments while mitigating supply chain and regulatory risks
Industry leaders must adopt a pragmatic, risk-aware approach that balances innovation with operational resilience. Begin by prioritizing interoperability and standards compliance as primary procurement criteria to ensure seamless integration with electronic health records and identity platforms. Next, invest in privacy-preserving design patterns such as on-device matching and robust encryption protocols so deployments can meet tightening regulatory expectations without sacrificing usability. Organizations should also diversify supply chains by qualifying multiple manufacturing partners or opting for software-centric architectures that reduce hardware dependency and mitigate tariff exposure.
In parallel, establish cross-functional governance that includes clinical, IT, legal, and procurement stakeholders to accelerate adoption and reduce implementation friction. Pilot programs should be structured with measurable clinical and administrative endpoints, and successful pilots should have clear scaling pathways. Finally, cultivate strategic partnerships with vendors that can provide both modality expertise and enterprise integration capabilities, and negotiate contracts with performance SLAs and price adjustment clauses to manage cost volatility. Executed deliberately, these steps will reduce deployment risk while unlocking tangible improvements in patient safety and operational efficiency.
A transparent mixed-methods research approach encompassing primary stakeholder interviews, technical validation, and expert peer review to ensure credible and actionable findings
The research adopted a mixed-methods approach that triangulated qualitative insights with technical validation to produce robust, practitioner-oriented findings. Primary research included interviews with clinical leaders, CIOs, procurement officers, and vendor product managers to surface real-world constraints, decision criteria, and implementation experiences. Secondary research encompassed peer-reviewed literature, standards documentation, regulatory guidance, and product technical specifications to validate modality capabilities and privacy techniques. Technical validation exercises examined system architectures, API compatibility, and data protection mechanisms to assess readiness for clinical integration.
Analytical techniques included thematic synthesis of interview data, cross-case comparison across deployment scenarios, and a modular framework for mapping segmentation to use cases and deployment profiles. To ensure credibility, findings were peer-reviewed by independent subject-matter experts and stress-tested against known regulatory trends and supply-chain developments. The methodology acknowledges limitations related to rapid technological change and regional policy divergence, and it recommends periodic revalidation of assumptions as standards, regulations, and vendor capabilities evolve.
A concise synthesis of how practical governance, modality alignment, and procurement resilience combine to turn biometric potential into clinical and operational value
In sum, biometrics are transitioning from specialized pilot projects to core components of secure, efficient healthcare delivery. The confluence of improved sensors, advanced algorithms, and privacy-enhancing techniques means that biometric solutions can now meet the demanding reliability, compliance, and usability requirements of clinical environments. However, this transition requires deliberate attention to interoperability, procurement resilience, and governance to translate technical potential into sustained clinical benefit.
Organizations that succeed will be those that align modality choice and deployment model with clinical workflows, prioritize privacy and consent management, and construct procurement strategies resilient to supply-chain and policy shocks. By coupling rigorous pilot designs with cross-functional governance and vendor partnerships that emphasize integration and support, health systems can adopt biometric technologies in a way that measurably improves patient safety and operational efficiency. The pathway to meaningful adoption is navigable, but it demands an integrated approach that balances innovation with pragmatic risk management.
Note: PDF & Excel + Online Access - 1 Year
A concise and authoritative orientation to how biometric technologies are reshaping clinical identity, operational workflows, and patient safety in modern healthcare delivery
Healthcare delivery is undergoing a quiet but profound transformation driven by the need for secure, reliable, and patient-centric identity verification. Biometrics have moved from optional conveniences to foundational elements of clinical workflows, enabling safer patient identification, frictionless access control, and more accurate staff authentication. As electronic health record systems expand and telehealth becomes a persistent channel of care, the role of biometrics in preventing errors, reducing fraud, and enhancing operational efficiency has become increasingly visible.
Moreover, advances in sensor technology, data processing, and machine learning have improved accuracy and reduced latency, making biometric solutions more practical in diverse clinical environments. These developments intersect with rising regulatory focus on privacy and data protection, obliging health systems to balance innovation with patient rights. Consequently, healthcare organizations are prioritizing interoperable solutions that integrate with identity management and clinical systems while complying with evolving policy frameworks. As a result, procurement and implementation decisions now require a cross-functional perspective that weighs clinical impact, IT operability, regulatory adherence, and patient experience.
Emerging technical, regulatory, and interoperability forces that are driving multimodal biometrics, edge processing, and privacy-first architectures across clinical and administrative settings
The landscape of healthcare biometrics is being reshaped by several concurrent shifts that together redefine expectations for performance, privacy, and deployment. First, multimodal approaches that combine physiological and behavioral traits are gaining traction because they substantially improve recognition accuracy under real-world conditions. This technical maturation is reinforced by edge computing, which reduces latency and enables local template storage and matching, thus reducing reliance on continuous cloud connectivity.
At the same time, privacy-preserving techniques such as template protection, differential privacy, and on-device inference are evolving from academic concepts into operational features demanded by healthcare purchasers. Regulators are signaling stricter controls around biometric data, prompting architecture changes that favor encryption, consent management, and auditable access logs. Interoperability is another pivotal shift: interoperability frameworks and standardized APIs are enabling tighter integration between biometric systems and electronic health records, identity management platforms, and workforce management tools. Finally, the convergence of wearable sensors and remote monitoring is expanding biometric use cases beyond static access control toward continuous patient verification and longitudinal monitoring, thereby extending the technology’s clinical relevance.
How tariff-driven supply chain adjustments and sourcing strategies are reshaping procurement, manufacturing footprints, and solution design choices within the healthcare biometrics ecosystem
The introduction of new tariff measures in the United States has created a complex operating environment for suppliers, integrators, and health systems that rely on internationally sourced components. Increased duties on imported hardware and certain electronic assemblies have prompted procurement managers to reassess supplier footprints, prioritize local sourcing where feasible, and consider total cost of ownership rather than unit pricing alone. Consequently, supply chain strategies that once emphasized lowest-cost procurement are shifting toward resiliency, with organizations tolerating higher near-term costs in exchange for reduced lead-time risk and improved compliance visibility.
In parallel, tariff-related frictions have encouraged increased vertical integration by some vendors, who are choosing to internalize manufacturing stages or to shift production to tariff-exempt jurisdictions. For purchasers, this translates into longer vendor qualification cycles and a renewed emphasis on contractual protections around price adjustments and delivery guarantees. Technology decisions are also being affected: organizations are more likely to consider software-centric architectures and cloud-enabled services that decouple costly hardware refresh cycles from feature upgrades. As a result, procurement teams are collaborating more closely with legal and supply-chain functions to design procurement vehicles that mitigate tariff exposure and preserve deployment timelines.
Actionable segmentation insights linking biometric modalities, components, end users, applications, and deployment models to procurement priorities and clinical integration pathways
A granular understanding of segmentation is essential to align product design and go-to-market strategies to clinical needs. When segmenting by biometric type, it is important to account for modality-specific constraints and clinical use-case fit across ECG Recognition, Face Recognition, Fingerprint Recognition, Hand Geometry, Iris Recognition, Palm Recognition, Retina Recognition, Vein Recognition, and Voice Recognition. Each modality brings distinct trade-offs in accuracy, hygiene, user acceptance, and environmental robustness; therefore, solution architects must map modality characteristics to the operational realities of acute care, outpatient clinics, and ambulatory settings.
Component-based differentiation between Hardware, Services, and Software informs partner strategies and margin structures, with hardware vendors increasingly offering managed services and software providers embedding analytics and integration toolkits. End user segmentation that includes Ambulatory Care Centers, Clinics, Diagnostic Centers, and Hospitals reveals divergent procurement cycles, regulatory demands, and integration priorities, so tailored sales motions and pilot designs are essential. Application segmentation across Access Control, Patient Identification, Patient Monitoring, Staff Identification, and Time and Attendance highlights where clinical safety and administrative efficiency intersect, guiding feature prioritization and compliance requirements. Finally, deployment models that span Cloud and On Premises, with the Cloud option further divided into Hybrid Cloud, Private Cloud, and Public Cloud, create distinct operational, security, and integration profiles that influence implementation timelines and total cost considerations.
Strategic regional distinctions and regulatory considerations across the Americas, Europe Middle East & Africa, and Asia-Pacific that influence deployment models and partnership strategies
Regional dynamics shape adoption pathways and regulatory approaches, and understanding geographic nuances is critical for strategic market entry. In the Americas, health systems often prioritize interoperability with extensive electronic records infrastructures and face stringent privacy expectations, driving demand for integrated solutions that support large hospital networks and outpatient systems. Vendor strategies in this region tend to emphasize enterprise-grade integrations, compliance certifications, and partnerships with established IT integrators to navigate complex purchasing processes.
Across Europe, Middle East & Africa, regulatory heterogeneity and diverse infrastructure maturity levels require flexible deployment options and localized compliance expertise. Some countries favor cloud-first strategies, while others mandate local data residency and tailored consent frameworks, which pushes vendors to offer both cloud and on-premises variants and to maintain robust data governance features. The Asia-Pacific region presents a mix of rapid technology adoption in urban centers and constrained resources in lower-income areas, creating opportunities for scalable, cost-effective solutions and strong demand for mobile-first, multilingual interfaces. Taken together, these regional distinctions affect channel strategies, pricing models, and product roadmaps, making geographic adaptation a fundamental element of sustained commercial success.
Competitive landscape dynamics and partnership ecosystems that determine vendor viability through integration readiness, clinical validation, and enterprise supportability
Competitive dynamics in healthcare biometrics are defined by a portfolio of incumbent system integrators, specialized biometric vendors, device manufacturers, and emerging cloud-native entrants. Incumbents benefit from deep relationships with health systems and experience navigating procurement and compliance cycles, while specialized vendors offer modality expertise and faster product iteration. Device manufacturers continue to innovate on sensors and form factors, targeting hygienic designs and ruggedized hardware for clinical settings, whereas software-focused firms differentiate through analytics, interoperability, and identity lifecycle management.
Partnership ecosystems are maturing: technology alliances between biometric specialists and electronic health record integrators or workforce management platforms are becoming common, enabling turnkey offerings that reduce implementation complexity. At the same time, a wave of consolidation among smaller niche players is likely as customers seek vendors that can demonstrate complete security controls, validated clinical workflows, and enterprise-level support. For purchasers, this means vendor selection criteria now emphasize long-term supportability, standards-based integration, and demonstrable clinical outcomes rather than feature lists alone.
Practical and prioritized recommendations for healthcare leaders to accelerate secure, scalable biometric deployments while mitigating supply chain and regulatory risks
Industry leaders must adopt a pragmatic, risk-aware approach that balances innovation with operational resilience. Begin by prioritizing interoperability and standards compliance as primary procurement criteria to ensure seamless integration with electronic health records and identity platforms. Next, invest in privacy-preserving design patterns such as on-device matching and robust encryption protocols so deployments can meet tightening regulatory expectations without sacrificing usability. Organizations should also diversify supply chains by qualifying multiple manufacturing partners or opting for software-centric architectures that reduce hardware dependency and mitigate tariff exposure.
In parallel, establish cross-functional governance that includes clinical, IT, legal, and procurement stakeholders to accelerate adoption and reduce implementation friction. Pilot programs should be structured with measurable clinical and administrative endpoints, and successful pilots should have clear scaling pathways. Finally, cultivate strategic partnerships with vendors that can provide both modality expertise and enterprise integration capabilities, and negotiate contracts with performance SLAs and price adjustment clauses to manage cost volatility. Executed deliberately, these steps will reduce deployment risk while unlocking tangible improvements in patient safety and operational efficiency.
A transparent mixed-methods research approach encompassing primary stakeholder interviews, technical validation, and expert peer review to ensure credible and actionable findings
The research adopted a mixed-methods approach that triangulated qualitative insights with technical validation to produce robust, practitioner-oriented findings. Primary research included interviews with clinical leaders, CIOs, procurement officers, and vendor product managers to surface real-world constraints, decision criteria, and implementation experiences. Secondary research encompassed peer-reviewed literature, standards documentation, regulatory guidance, and product technical specifications to validate modality capabilities and privacy techniques. Technical validation exercises examined system architectures, API compatibility, and data protection mechanisms to assess readiness for clinical integration.
Analytical techniques included thematic synthesis of interview data, cross-case comparison across deployment scenarios, and a modular framework for mapping segmentation to use cases and deployment profiles. To ensure credibility, findings were peer-reviewed by independent subject-matter experts and stress-tested against known regulatory trends and supply-chain developments. The methodology acknowledges limitations related to rapid technological change and regional policy divergence, and it recommends periodic revalidation of assumptions as standards, regulations, and vendor capabilities evolve.
A concise synthesis of how practical governance, modality alignment, and procurement resilience combine to turn biometric potential into clinical and operational value
In sum, biometrics are transitioning from specialized pilot projects to core components of secure, efficient healthcare delivery. The confluence of improved sensors, advanced algorithms, and privacy-enhancing techniques means that biometric solutions can now meet the demanding reliability, compliance, and usability requirements of clinical environments. However, this transition requires deliberate attention to interoperability, procurement resilience, and governance to translate technical potential into sustained clinical benefit.
Organizations that succeed will be those that align modality choice and deployment model with clinical workflows, prioritize privacy and consent management, and construct procurement strategies resilient to supply-chain and policy shocks. By coupling rigorous pilot designs with cross-functional governance and vendor partnerships that emphasize integration and support, health systems can adopt biometric technologies in a way that measurably improves patient safety and operational efficiency. The pathway to meaningful adoption is navigable, but it demands an integrated approach that balances innovation with pragmatic risk management.
Note: PDF & Excel + Online Access - 1 Year
Table of Contents
197 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Deployment of AI-powered voice biometrics to verify patient identity during remote consultations
- 5.2. Adoption of multimodal biometric authentication combining fingerprint and palm vein scanning in hospitals
- 5.3. Integration of wearable biometric sensors for continuous vital sign monitoring in chronic disease management
- 5.4. Implementation of blockchain-secured biometric data storage for enhanced patient privacy and compliance
- 5.5. Utilization of gait analysis biometrics for early detection of neurodegenerative disorders in elderly care
- 5.6. Emergence of contactless iris recognition systems to streamline patient check-in workflows in clinics
- 5.7. Regulatory approval pathways evolving for biometric medical devices to ensure interoperability and safety
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Healthcare Biometrics Market, by Biometric Type
- 8.1. Ecg Recognition
- 8.2. Face Recognition
- 8.3. Fingerprint Recognition
- 8.4. Hand Geometry
- 8.5. Iris Recognition
- 8.6. Palm Recognition
- 8.7. Retina Recognition
- 8.8. Vein Recognition
- 8.9. Voice Recognition
- 9. Healthcare Biometrics Market, by Component
- 9.1. Hardware
- 9.2. Services
- 9.3. Software
- 10. Healthcare Biometrics Market, by End User
- 10.1. Ambulatory Care Centers
- 10.2. Clinics
- 10.3. Diagnostic Centers
- 10.4. Hospitals
- 11. Healthcare Biometrics Market, by Application
- 11.1. Access Control
- 11.2. Patient Identification
- 11.3. Patient Monitoring
- 11.4. Staff Identification
- 11.5. Time And Attendance
- 12. Healthcare Biometrics Market, by Deployment
- 12.1. Cloud
- 12.1.1. Hybrid Cloud
- 12.1.2. Private Cloud
- 12.1.3. Public Cloud
- 12.2. On Premises
- 13. Healthcare Biometrics Market, by Region
- 13.1. Americas
- 13.1.1. North America
- 13.1.2. Latin America
- 13.2. Europe, Middle East & Africa
- 13.2.1. Europe
- 13.2.2. Middle East
- 13.2.3. Africa
- 13.3. Asia-Pacific
- 14. Healthcare Biometrics Market, by Group
- 14.1. ASEAN
- 14.2. GCC
- 14.3. European Union
- 14.4. BRICS
- 14.5. G7
- 14.6. NATO
- 15. Healthcare Biometrics Market, by Country
- 15.1. United States
- 15.2. Canada
- 15.3. Mexico
- 15.4. Brazil
- 15.5. United Kingdom
- 15.6. Germany
- 15.7. France
- 15.8. Russia
- 15.9. Italy
- 15.10. Spain
- 15.11. China
- 15.12. India
- 15.13. Japan
- 15.14. Australia
- 15.15. South Korea
- 16. Competitive Landscape
- 16.1. Market Share Analysis, 2024
- 16.2. FPNV Positioning Matrix, 2024
- 16.3. Competitive Analysis
- 16.3.1. 3M Company
- 16.3.2. Apple Inc.
- 16.3.3. Aware, Inc.
- 16.3.4. Bio-key International, Inc.
- 16.3.5. Dermalog Identification Systems GmbH
- 16.3.6. Fujitsu Limited
- 16.3.7. HID Global Corporation
- 16.3.8. Hitachi, Ltd.
- 16.3.9. IDEMIA SAS
- 16.3.10. International Business Machines Corporation
- 16.3.11. Microsoft Corporation
- 16.3.12. NEC Corporation
- 16.3.13. Suprema Inc.
- 16.3.14. Thales Group
- 16.3.15. ZKTeco Co., Ltd.
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