Robot End Effector Market by Type (Cutting Tool, Gripper, Magnetic), Actuation Type (Electric, Hydraulic, Pneumatic), Automation Level, End User Industry - Global Forecast 2025-2032
Description
The Robo Advisor Market was valued at USD 42.33 million in 2024 and is projected to grow to USD 46.58 million in 2025, with a CAGR of 10.80%, reaching USD 96.20 million by 2032.
An executive introduction that frames the current robo-advisor environment, technological drivers, and the strategic priorities shaping sustainable client adoption
A concise introduction that frames the modern robo-advisor environment and highlights the strategic forces driving rapid evolution
The robo-advisor landscape has matured from experimental automation to a critical channel for wealth management distribution and client engagement. Technological advancements such as advanced portfolio construction algorithms, improved user interfaces, and scalable backend systems have converged with changing investor expectations, prompting firms to rethink how advice is delivered at scale. Consequently, firms now treat robo-advisory capabilities as strategic assets rather than tactical products, integrating them into broader omnichannel wealth propositions to maintain relevance with digitally native cohorts while retaining trust with legacy clients.
Furthermore, the interplay between regulation, cybersecurity expectations, and competitive fee pressure has elevated operational resilience and transparency as core differentiators. As platforms integrate richer data sets and behavioral insights, they are better positioned to deliver contextualized advice while preserving compliance and auditability. Therefore, stakeholders who prioritize agile product governance and a clear path for incremental innovation will be better placed to capture long-term client relationships and operational leverage.
A perspective on how hybrid advice models, advanced personalization, regulatory focus, and partnership-driven distribution are redefining value creation in robo-advisory
Transformative shifts in the robo-advisor ecosystem that are reshaping product design, distribution, and value capture
The past several years have seen a pronounced shift toward hybridization of advisory models, where algorithmic automation coexists with human-led guidance to address complex client needs. This hybrid trajectory enhances client trust and expands addressable segments beyond simple, rules-driven portfolios. Simultaneously, advances in machine learning and natural language processing have enabled more personalized investment experiences, dynamic tax-aware rebalancing, and sentiment-aware engagement, which collectively raise client lifetime value through better retention and deeper wallet share.
In parallel, regulatory emphasis on transparency, suitability, and operational resilience is redirecting investment toward governance, explainable models, and audit-ready workflows. Open finance initiatives and standard APIs are accelerating partnerships between fintechs and incumbent institutions, thereby widening distribution paths while increasing interoperability demands. Layered on these changes, competitive pressure on fees necessitates greater focus on operational efficiency and ancillary service monetization such as financial planning, data-driven insights, and premium advisory tiers. Together, these structural shifts are forcing firms to balance scale economics with differentiated client experiences to preserve margins and loyalty.
How changes in trade policy and tariff regimes reverberate through technology sourcing, vendor relationships, and strategic operating model decisions for digital wealth platforms
The cumulative impacts of United States tariff changes on the robo-advisor value chain and operational cost structures
Tariff changes instituted through trade policy can produce ripples across the technology and services ecosystem that supports digital wealth platforms. In practical terms, increased duties on imported hardware, networking equipment, or specialized compute components raise the cost base for firms that rely on owned data center infrastructure or on-premise deployments. As a result, organizations may accelerate migration to cloud providers or renegotiate vendor contracts to mitigate capital expenditure shocks. This migration trend in turn reshapes vendor relationships and contractual models, leading to a greater preference for consumption-based agreements and managed services.
Moreover, tariffs can indirectly affect the global talent and service supply chain. When cross-border vendor costs rise, partnership models with foreign technology providers become more expensive, prompting in-sourcing or regionalization of key services. Consequently, firms face a trade-off between higher near-term operating expenses and longer-term strategic benefits such as data residency, improved compliance alignment, and reduced exposure to tariff volatility. Finally, the chain reaction from cost pressure often forces product teams to prioritize modular architectures and API-driven integration to preserve flexibility, thereby enabling faster vendor substitution and reducing lock-in risk.
A deep dive into segmentation dynamics showing how service type choices, end user distinctions, and deployment models shape product, sales, and operational priorities
Segmentation insights that highlight strategic implications across service type, end user profiles, and deployment models
Differentiation across service type-particularly the contrast between fully automated offerings and hybrid models-drives divergent product roadmaps. Fully automated solutions emphasize scale, low friction onboarding, and algorithmic cost leadership, which suits cost-sensitive retail segments. In contrast, hybrid services layer human expertise and advisory workflows around algorithmic cores, enabling higher-touch propositions for clients with complex needs or larger investable assets. Thus, product teams must decide whether to optimize around scale efficiencies or to invest in human-assisted workflows that support richer advice and bespoke client outcomes.
End-user segmentation reveals distinct demand signals between individual investors and institutional investors. Individual investors prioritize ease of use, straightforward fee structures, and integrated digital experiences, whereas institutional investors focus on customization, integration with existing treasury or custody systems, and robust compliance and reporting capabilities. Consequently, go-to-market approaches, sales cycles, and product capabilities must be tailored to address these differing evaluation criteria and procurement rhythms.
Deployment choices between cloud and on premise have profound operational and commercial consequences. Cloud deployments accelerate time-to-market, support continuous delivery, and reduce upfront capital commitments, enabling firms to iterate rapidly and scale globally. Conversely, on-premise deployments offer greater control over data residency and customization, which may be required by certain institutional clients or specific regulatory regimes. Therefore, platform architecture decisions should balance agility and control, supported by clear migration and interoperability strategies to serve diverse client requirements.
A regionally nuanced analysis of adoption drivers, regulatory complexity, and partnership strategies spanning the Americas, Europe Middle East and Africa, and Asia Pacific
Regional insights that expose the geographic nuances influencing adoption, regulation, and partnership opportunity across global markets
The Americas continue to be a focal point for innovation and scale, driven by high digital adoption among retail investors, robust wealth accumulation, and a dynamic startup ecosystem that accelerates product experimentation. In North America, regulatory expectations emphasize investor protection and model transparency, which incentivizes investments in compliance tooling and auditability. As a result, partnerships between fintechs and incumbent banks often center on distribution and brand credibility to reach broader retail segments.
Europe, Middle East & Africa present a more heterogeneous operating environment, where varied regulatory frameworks and differing levels of digital maturity create both opportunities and complexity. In parts of Europe, open banking standards and strong privacy frameworks compel providers to build privacy-first data architectures and clear consent mechanisms. Meanwhile, markets in the Middle East and Africa show growing appetite for digital wealth solutions, but success depends on localization, trust-building, and tailored distribution strategies that respect local financial literacy and infrastructure dynamics.
Asia-Pacific demonstrates rapid diversification, with pockets of high digital penetration, significant wealth creation, and strong demand for hybrid advisory services. In many APAC markets, partnerships with local financial institutions and payment ecosystems accelerate adoption, whereas regulatory bodies are increasingly focused on conduct risk and cross-border data governance. Accordingly, market entrants must combine regional partnerships, localized product features, and adaptable compliance frameworks to capitalize on growth while managing regulatory exposure.
An examination of competitive dynamics, partnership strategies, and product specialization that determine long term differentiation and resilience among providers
Company-level insights that illuminate competitive positioning, strategic differentiation, and the sources of sustainable advantage among leading providers
Competitive dynamics in the space reflect a blend of legacy incumbents, specialized fintech challengers, and cloud-native technology vendors that enable rapid productization. Firms that succeed sustain advantage by integrating high-quality data, explainable investment models, and seamless client journeys while maintaining strict operational controls. Strategic differentiation often emerges through specialization-targeting niche segments such as tax-optimized planning, retirement decumulation strategies, or ESG-aligned portfolios-rather than competing solely on price.
Partnership strategies also play a pivotal role in shaping competitive advantage. Alliances with custodians, broker-dealers, and wealth platforms expand distribution reach and credibility, whereas technology partnerships can shorten time-to-market for advanced features like automated rebalancing, alternative data ingestion, and compliance automation. Finally, acquisition and talent aggregation remain viable paths to acquire capabilities quickly, but integrating acquired teams and systems requires disciplined change management to realize intended synergies and avoid operational disruption.
Practical and prioritized actions that leaders can implement to enhance product agility, strengthen governance, and expand commercial reach with controlled risk
Actionable recommendations for industry leaders seeking to strengthen market position, accelerate adoption, and de-risk scaling initiatives
Leaders should prioritize modular architectures that enable rapid feature experimentation while preserving rigorous governance and explainability. By decoupling core portfolio engines from customer experience layers, teams can iterate on engagement models without jeopardizing regulatory compliance. Additionally, firms must invest in data quality and lineage capabilities to support model validation and to demonstrate suitability in client interactions.
Commercially, organizations should calibrate pricing and packaging to reflect differentiated value tiers, offering a base automated product for scale while reserving higher-margin hybrid services for complex client segments. Strategic partnerships are essential to expand distribution and access new customer cohorts quickly; therefore, firms should craft partner-friendly APIs and co-branding models to accelerate adoption. From an operational perspective, embedding continuous monitoring for model drift, cybersecurity posture, and third-party risk management will mitigate business continuity exposures as products scale across geographies.
A transparent description of the analytic approach, primary and secondary validation techniques, and the structured framework used to synthesize actionable insights
Research methodology describing the analytical approach, validation techniques, and data synthesis used to derive the report’s insights
The research approach integrates qualitative interviews with practitioners across advisory, technology, regulation, and operations, combined with systematic secondary analysis of public disclosures, regulatory guidance, and technology roadmaps. Primary engagement involved structured conversations with product leaders, compliance officers, and distribution partners to surface operational constraints and strategic priorities. In parallel, thematic analysis of documented case studies and vendor whitepapers provided contextual nuance and supported triangulation of observed trends.
Data synthesis emphasized cross-validation and scenario-based reasoning rather than single-source conclusions. Analysts applied a reproducible framework that maps drivers to outcomes across product, commercial, and operational dimensions while stress-testing assumptions against diverse regional regulatory environments. Finally, findings were reviewed with independent industry experts to ensure interpretive rigor and to refine actionable recommendations for executives considering product evolution, partnership strategies, or technology investments.
A clear synthesis of strategic imperatives and operational priorities that executives must address to realize sustainable growth and competitive resilience
Conclusion summarizing the strategic implications and the critical choices facing executives in the evolving robo-advisor landscape
The trajectory of robo-advisory services is defined by an imperative to reconcile scale economics with meaningful client personalization. Organizations that successfully combine algorithmic efficiency with human-led advisory where necessary will unlock broader customer segments while improving retention. In addition, resilient operational models that prioritize modularity, data governance, and vendor flexibility will be essential as geopolitical, regulatory, and commercial headwinds create periodic disruption.
Looking ahead, the winners will be those that treat product architecture, partner strategy, and compliance as interconnected levers rather than compartmentalized functions. By doing so, firms can adapt rapidly to local regulatory requirements, capture emergent customer behaviors, and sustain a defensible commercial advantage through continuous innovation and disciplined execution.
Note: PDF & Excel + Online Access - 1 Year
An executive introduction that frames the current robo-advisor environment, technological drivers, and the strategic priorities shaping sustainable client adoption
A concise introduction that frames the modern robo-advisor environment and highlights the strategic forces driving rapid evolution
The robo-advisor landscape has matured from experimental automation to a critical channel for wealth management distribution and client engagement. Technological advancements such as advanced portfolio construction algorithms, improved user interfaces, and scalable backend systems have converged with changing investor expectations, prompting firms to rethink how advice is delivered at scale. Consequently, firms now treat robo-advisory capabilities as strategic assets rather than tactical products, integrating them into broader omnichannel wealth propositions to maintain relevance with digitally native cohorts while retaining trust with legacy clients.
Furthermore, the interplay between regulation, cybersecurity expectations, and competitive fee pressure has elevated operational resilience and transparency as core differentiators. As platforms integrate richer data sets and behavioral insights, they are better positioned to deliver contextualized advice while preserving compliance and auditability. Therefore, stakeholders who prioritize agile product governance and a clear path for incremental innovation will be better placed to capture long-term client relationships and operational leverage.
A perspective on how hybrid advice models, advanced personalization, regulatory focus, and partnership-driven distribution are redefining value creation in robo-advisory
Transformative shifts in the robo-advisor ecosystem that are reshaping product design, distribution, and value capture
The past several years have seen a pronounced shift toward hybridization of advisory models, where algorithmic automation coexists with human-led guidance to address complex client needs. This hybrid trajectory enhances client trust and expands addressable segments beyond simple, rules-driven portfolios. Simultaneously, advances in machine learning and natural language processing have enabled more personalized investment experiences, dynamic tax-aware rebalancing, and sentiment-aware engagement, which collectively raise client lifetime value through better retention and deeper wallet share.
In parallel, regulatory emphasis on transparency, suitability, and operational resilience is redirecting investment toward governance, explainable models, and audit-ready workflows. Open finance initiatives and standard APIs are accelerating partnerships between fintechs and incumbent institutions, thereby widening distribution paths while increasing interoperability demands. Layered on these changes, competitive pressure on fees necessitates greater focus on operational efficiency and ancillary service monetization such as financial planning, data-driven insights, and premium advisory tiers. Together, these structural shifts are forcing firms to balance scale economics with differentiated client experiences to preserve margins and loyalty.
How changes in trade policy and tariff regimes reverberate through technology sourcing, vendor relationships, and strategic operating model decisions for digital wealth platforms
The cumulative impacts of United States tariff changes on the robo-advisor value chain and operational cost structures
Tariff changes instituted through trade policy can produce ripples across the technology and services ecosystem that supports digital wealth platforms. In practical terms, increased duties on imported hardware, networking equipment, or specialized compute components raise the cost base for firms that rely on owned data center infrastructure or on-premise deployments. As a result, organizations may accelerate migration to cloud providers or renegotiate vendor contracts to mitigate capital expenditure shocks. This migration trend in turn reshapes vendor relationships and contractual models, leading to a greater preference for consumption-based agreements and managed services.
Moreover, tariffs can indirectly affect the global talent and service supply chain. When cross-border vendor costs rise, partnership models with foreign technology providers become more expensive, prompting in-sourcing or regionalization of key services. Consequently, firms face a trade-off between higher near-term operating expenses and longer-term strategic benefits such as data residency, improved compliance alignment, and reduced exposure to tariff volatility. Finally, the chain reaction from cost pressure often forces product teams to prioritize modular architectures and API-driven integration to preserve flexibility, thereby enabling faster vendor substitution and reducing lock-in risk.
A deep dive into segmentation dynamics showing how service type choices, end user distinctions, and deployment models shape product, sales, and operational priorities
Segmentation insights that highlight strategic implications across service type, end user profiles, and deployment models
Differentiation across service type-particularly the contrast between fully automated offerings and hybrid models-drives divergent product roadmaps. Fully automated solutions emphasize scale, low friction onboarding, and algorithmic cost leadership, which suits cost-sensitive retail segments. In contrast, hybrid services layer human expertise and advisory workflows around algorithmic cores, enabling higher-touch propositions for clients with complex needs or larger investable assets. Thus, product teams must decide whether to optimize around scale efficiencies or to invest in human-assisted workflows that support richer advice and bespoke client outcomes.
End-user segmentation reveals distinct demand signals between individual investors and institutional investors. Individual investors prioritize ease of use, straightforward fee structures, and integrated digital experiences, whereas institutional investors focus on customization, integration with existing treasury or custody systems, and robust compliance and reporting capabilities. Consequently, go-to-market approaches, sales cycles, and product capabilities must be tailored to address these differing evaluation criteria and procurement rhythms.
Deployment choices between cloud and on premise have profound operational and commercial consequences. Cloud deployments accelerate time-to-market, support continuous delivery, and reduce upfront capital commitments, enabling firms to iterate rapidly and scale globally. Conversely, on-premise deployments offer greater control over data residency and customization, which may be required by certain institutional clients or specific regulatory regimes. Therefore, platform architecture decisions should balance agility and control, supported by clear migration and interoperability strategies to serve diverse client requirements.
A regionally nuanced analysis of adoption drivers, regulatory complexity, and partnership strategies spanning the Americas, Europe Middle East and Africa, and Asia Pacific
Regional insights that expose the geographic nuances influencing adoption, regulation, and partnership opportunity across global markets
The Americas continue to be a focal point for innovation and scale, driven by high digital adoption among retail investors, robust wealth accumulation, and a dynamic startup ecosystem that accelerates product experimentation. In North America, regulatory expectations emphasize investor protection and model transparency, which incentivizes investments in compliance tooling and auditability. As a result, partnerships between fintechs and incumbent banks often center on distribution and brand credibility to reach broader retail segments.
Europe, Middle East & Africa present a more heterogeneous operating environment, where varied regulatory frameworks and differing levels of digital maturity create both opportunities and complexity. In parts of Europe, open banking standards and strong privacy frameworks compel providers to build privacy-first data architectures and clear consent mechanisms. Meanwhile, markets in the Middle East and Africa show growing appetite for digital wealth solutions, but success depends on localization, trust-building, and tailored distribution strategies that respect local financial literacy and infrastructure dynamics.
Asia-Pacific demonstrates rapid diversification, with pockets of high digital penetration, significant wealth creation, and strong demand for hybrid advisory services. In many APAC markets, partnerships with local financial institutions and payment ecosystems accelerate adoption, whereas regulatory bodies are increasingly focused on conduct risk and cross-border data governance. Accordingly, market entrants must combine regional partnerships, localized product features, and adaptable compliance frameworks to capitalize on growth while managing regulatory exposure.
An examination of competitive dynamics, partnership strategies, and product specialization that determine long term differentiation and resilience among providers
Company-level insights that illuminate competitive positioning, strategic differentiation, and the sources of sustainable advantage among leading providers
Competitive dynamics in the space reflect a blend of legacy incumbents, specialized fintech challengers, and cloud-native technology vendors that enable rapid productization. Firms that succeed sustain advantage by integrating high-quality data, explainable investment models, and seamless client journeys while maintaining strict operational controls. Strategic differentiation often emerges through specialization-targeting niche segments such as tax-optimized planning, retirement decumulation strategies, or ESG-aligned portfolios-rather than competing solely on price.
Partnership strategies also play a pivotal role in shaping competitive advantage. Alliances with custodians, broker-dealers, and wealth platforms expand distribution reach and credibility, whereas technology partnerships can shorten time-to-market for advanced features like automated rebalancing, alternative data ingestion, and compliance automation. Finally, acquisition and talent aggregation remain viable paths to acquire capabilities quickly, but integrating acquired teams and systems requires disciplined change management to realize intended synergies and avoid operational disruption.
Practical and prioritized actions that leaders can implement to enhance product agility, strengthen governance, and expand commercial reach with controlled risk
Actionable recommendations for industry leaders seeking to strengthen market position, accelerate adoption, and de-risk scaling initiatives
Leaders should prioritize modular architectures that enable rapid feature experimentation while preserving rigorous governance and explainability. By decoupling core portfolio engines from customer experience layers, teams can iterate on engagement models without jeopardizing regulatory compliance. Additionally, firms must invest in data quality and lineage capabilities to support model validation and to demonstrate suitability in client interactions.
Commercially, organizations should calibrate pricing and packaging to reflect differentiated value tiers, offering a base automated product for scale while reserving higher-margin hybrid services for complex client segments. Strategic partnerships are essential to expand distribution and access new customer cohorts quickly; therefore, firms should craft partner-friendly APIs and co-branding models to accelerate adoption. From an operational perspective, embedding continuous monitoring for model drift, cybersecurity posture, and third-party risk management will mitigate business continuity exposures as products scale across geographies.
A transparent description of the analytic approach, primary and secondary validation techniques, and the structured framework used to synthesize actionable insights
Research methodology describing the analytical approach, validation techniques, and data synthesis used to derive the report’s insights
The research approach integrates qualitative interviews with practitioners across advisory, technology, regulation, and operations, combined with systematic secondary analysis of public disclosures, regulatory guidance, and technology roadmaps. Primary engagement involved structured conversations with product leaders, compliance officers, and distribution partners to surface operational constraints and strategic priorities. In parallel, thematic analysis of documented case studies and vendor whitepapers provided contextual nuance and supported triangulation of observed trends.
Data synthesis emphasized cross-validation and scenario-based reasoning rather than single-source conclusions. Analysts applied a reproducible framework that maps drivers to outcomes across product, commercial, and operational dimensions while stress-testing assumptions against diverse regional regulatory environments. Finally, findings were reviewed with independent industry experts to ensure interpretive rigor and to refine actionable recommendations for executives considering product evolution, partnership strategies, or technology investments.
A clear synthesis of strategic imperatives and operational priorities that executives must address to realize sustainable growth and competitive resilience
Conclusion summarizing the strategic implications and the critical choices facing executives in the evolving robo-advisor landscape
The trajectory of robo-advisory services is defined by an imperative to reconcile scale economics with meaningful client personalization. Organizations that successfully combine algorithmic efficiency with human-led advisory where necessary will unlock broader customer segments while improving retention. In addition, resilient operational models that prioritize modularity, data governance, and vendor flexibility will be essential as geopolitical, regulatory, and commercial headwinds create periodic disruption.
Looking ahead, the winners will be those that treat product architecture, partner strategy, and compliance as interconnected levers rather than compartmentalized functions. By doing so, firms can adapt rapidly to local regulatory requirements, capture emergent customer behaviors, and sustain a defensible commercial advantage through continuous innovation and disciplined execution.
Note: PDF & Excel + Online Access - 1 Year
Table of Contents
195 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. Adoption of adaptive robotic grippers with machine learning for real-time grasp adjustments in e-commerce warehouses
- 5.2. Development of multi-functional modular end effectors for rapid tool change in flexible manufacturing environments
- 5.3. Implementation of force-torque sensing end effectors to improve delicate assembly in electronics production lines
- 5.4. Rise of soft robotic gripper technologies using bioinspired materials for safe handling of irregular agricultural produce
- 5.5. Increased demand for hygienic stainless steel vacuum end effectors in pharmaceutical and food processing automation
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Robot End Effector Market, by Type
- 8.1. Cutting Tool
- 8.2. Gripper
- 8.2.1. Electric
- 8.2.2. Hydraulic
- 8.2.3. Pneumatic
- 8.3. Magnetic
- 8.4. Painting Tool
- 8.5. Screw Driving Tool
- 8.6. Suction Cup
- 8.7. Welding Torch
- 9. Robot End Effector Market, by Actuation Type
- 9.1. Electric
- 9.1.1. Brushless Dc Motor
- 9.1.2. Servo Motor
- 9.1.3. Stepper Motor
- 9.2. Hydraulic
- 9.3. Pneumatic
- 10. Robot End Effector Market, by Automation Level
- 10.1. Collaborative Robots
- 10.1.1. Heavy Payload
- 10.1.2. Light Payload
- 10.1.3. Medium Payload
- 10.2. Fully Automatic
- 10.3. Manual
- 10.4. Semi Automatic
- 11. Robot End Effector Market, by End User Industry
- 11.1. Automotive
- 11.2. Consumer Goods
- 11.3. Electronics
- 11.4. Food And Beverage
- 11.5. Logistics And Warehousing
- 11.6. Metal And Machinery
- 11.7. Packaging
- 11.8. Pharmaceuticals
- 12. Robot End Effector Market, by Region
- 12.1. Americas
- 12.1.1. North America
- 12.1.2. Latin America
- 12.2. Europe, Middle East & Africa
- 12.2.1. Europe
- 12.2.2. Middle East
- 12.2.3. Africa
- 12.3. Asia-Pacific
- 13. Robot End Effector Market, by Group
- 13.1. ASEAN
- 13.2. GCC
- 13.3. European Union
- 13.4. BRICS
- 13.5. G7
- 13.6. NATO
- 14. Robot End Effector Market, by Country
- 14.1. United States
- 14.2. Canada
- 14.3. Mexico
- 14.4. Brazil
- 14.5. United Kingdom
- 14.6. Germany
- 14.7. France
- 14.8. Russia
- 14.9. Italy
- 14.10. Spain
- 14.11. China
- 14.12. India
- 14.13. Japan
- 14.14. Australia
- 14.15. South Korea
- 15. Competitive Landscape
- 15.1. Market Share Analysis, 2024
- 15.2. FPNV Positioning Matrix, 2024
- 15.3. Competitive Analysis
- 15.3.1. Schunk GmbH & Co. KG
- 15.3.2. Zimmer GmbH
- 15.3.3. Festo SE & Co. KG
- 15.3.4. Piab AB
- 15.3.5. OnRobot ApS
- 15.3.6. SMC Corporation
- 15.3.7. Destaco, LLC
- 15.3.8. ATI Industrial Automation, Inc.
- 15.3.9. J. Schmalz GmbH
- 15.3.10. Weiss Robotics Holding GmbH
- 15.3.11. Applied Robotics Inc.
- 15.3.12. Soft Robotics Inc.
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