Regulations Compliance And Governance
Factory AI Regulatory Sandbox
The Factory AI Regulatory Sandbox represents an innovative framework designed to facilitate the safe experimentation and implementation of artificial intelligence technologies within the Manufacturing (Non-Automotive) sector. This concept allows organizations to explore AI applications while navigating regulatory landscapes, ensuring compliance and mitigating risks. As industries increasingly pivot towards AI-driven solutions, this sandbox approach addresses critical operational and strategic priorities, fostering an environment conducive to technological advancement and collaboration among stakeholders. In the context of the Manufacturing (Non-Automotive) ecosystem, the Factory AI Regulatory Sandbox plays a pivotal role in reshaping competitive dynamics and driving innovation cycles. AI-driven practices enhance efficiency, refine decision-making processes, and cultivate deeper stakeholder engagement. While the potential for growth through AI adoption is substantial, challenges such as integration complexities and evolving expectations must be acknowledged. Navigating these realities will determine the success of organizations striving to harness AI's transformative power while balancing optimism with pragmatic approaches to implementation.
{"page_num":4,"introduction":{"title":"Factory AI Regulatory Sandbox","content":"The Factory AI Regulatory <\/a> Sandbox represents an innovative framework designed to facilitate the safe experimentation and implementation of artificial intelligence technologies within the Manufacturing (Non-Automotive) sector. This concept allows organizations to explore AI applications while navigating regulatory landscapes, ensuring compliance and mitigating risks. As industries increasingly pivot towards AI-driven solutions, this sandbox approach addresses critical operational and strategic priorities, fostering an environment conducive to technological advancement and collaboration among stakeholders.\n\nIn the context of the Manufacturing (Non-Automotive) ecosystem, the Factory AI Regulatory Sandbox <\/a> plays a pivotal role in reshaping competitive dynamics and driving innovation cycles. AI-driven practices enhance efficiency, refine decision-making processes, and cultivate deeper stakeholder engagement. While the potential for growth through AI adoption <\/a> is substantial, challenges such as integration complexities and evolving expectations must be acknowledged. Navigating these realities will determine the success of organizations striving to harness AI's transformative power while balancing optimism with pragmatic approaches to implementation.","search_term":"Factory AI Sandbox Manufacturing"},"description":{"title":"How is the Factory AI Regulatory Sandbox Transforming Non-Automotive Manufacturing?","content":"The Factory AI Regulatory Sandbox <\/a> is pivotal in the manufacturing sector, fostering innovation in AI integration and compliance <\/a> within production processes. Key growth drivers include enhanced operational efficiency, improved quality control, and the development of AI-driven solutions tailored to meet stringent regulatory standards."},"action_to_take":{"title":"Accelerate AI Integration in Manufacturing with a Regulatory Sandbox","content":"Manufacturing (Non-Automotive) companies should strategically invest in the Factory AI Regulatory Sandbox <\/a>, forming partnerships with leading AI technology firms <\/a> to drive innovation and compliance. By implementing AI-driven solutions, companies can achieve operational efficiencies, enhance product quality, and secure a competitive edge in a rapidly evolving market.","primary_action":"Download Compliance Checklist for Automotive AI","secondary_action":"Book a Governance Consultation"},"implementation_framework":[{"title":"Assess AI Readiness","subtitle":"Evaluate current capabilities and needs","descriptive_text":"Conduct a thorough assessment of existing manufacturing processes to identify AI readiness <\/a>, infrastructure, and specific needs. This step ensures alignment with regulatory standards and paves the way for effective AI integration <\/a>.","source":"Internal R&D","type":"dynamic","url":"https:\/\/www.mckinsey.com\/business-functions\/operations\/our-insights\/the-future-of-manufacturing","reason":"Understanding AI readiness is crucial for effective implementation and enhances the overall operational efficiency of manufacturing processes."},{"title":"Develop AI Strategy","subtitle":"Craft a comprehensive AI implementation plan","descriptive_text":"Create a tailored AI strategy <\/a> that outlines objectives, key performance indicators, and timelines. This strategy should align with business goals, ensuring a focused approach to integrating AI into manufacturing <\/a> workflows.","source":"Technology Partners","type":"dynamic","url":"https:\/\/www.bain.com\/insights\/how-to-develop-an-ai-strategy\/","reason":"A well-defined AI strategy aligns technology with business objectives, fostering innovation and maintaining competitiveness in the manufacturing sector."},{"title":"Implement Pilot Projects","subtitle":"Test AI solutions in controlled environments","descriptive_text":"Launch pilot projects to test selected AI applications within a controlled environment. This allows for real-time monitoring and adjustments, ensuring that AI solutions meet operational needs and regulatory requirements effectively.","source":"Industry Standards","type":"dynamic","url":"https:\/\/www.forbes.com\/sites\/bernardmarr\/2020\/11\/30\/how-to-run-an-ai-pilot-project\/?sh=4c6e3a6e59d0","reason":"Pilot projects offer practical insights, minimizing risks and allowing for iterative improvements before full-scale implementation, ensuring successful AI integration."},{"title":"Monitor and Optimize","subtitle":"Continuously assess AI performance","descriptive_text":"Regularly monitor the performance of AI solutions and optimize them based on data-driven insights. Continuous improvement ensures that AI applications remain effective, efficient, and compliant with evolving regulations in manufacturing <\/a>.","source":"Cloud Platform","type":"dynamic","url":"https:\/\/www.ibm.com\/cloud\/architecture\/architecture\/ai-optimization.html","reason":"Ongoing monitoring and optimization are essential for maintaining AI effectiveness, driving continuous improvement, and ensuring compliance with regulatory standards in manufacturing."},{"title":"Scale AI Solutions","subtitle":"Expand successful AI implementations","descriptive_text":"Once pilot projects demonstrate success, scale AI solutions <\/a> across the organization. This step maximizes the benefits of AI by integrating successful applications into broader manufacturing operations, enhancing productivity and compliance.","source":"Internal R&D","type":"dynamic","url":"https:\/\/www.gartner.com\/en\/information-technology\/insights\/scaling-ai","reason":"Scaling successful AI solutions amplifies their impact, driving innovation and operational excellence throughout the manufacturing sector, crucial for achieving Factory AI Regulatory Sandbox objectives."}],"primary_functions":{"question":"What's my primary function in the company?","functions":[{"title":"Engineering","content":"I design and develop AI-driven solutions for the Factory AI Regulatory Sandbox, ensuring they align with industry standards. My role involves selecting the right AI models, integrating them with existing systems, and tackling technical challenges to drive innovation and efficiency in manufacturing."},{"title":"Quality Assurance","content":"I ensure that AI systems in the Factory AI Regulatory Sandbox deliver accurate and reliable outputs. I conduct rigorous testing and validation processes, analyze performance data, and identify areas for improvement, directly enhancing quality control and boosting customer satisfaction across our manufacturing operations."},{"title":"Operations","content":"I manage the implementation and daily operations of AI systems within the Factory AI Regulatory Sandbox. By optimizing workflows and leveraging real-time AI insights, I enhance efficiency and productivity on the production floor, ensuring that operations run smoothly and effectively support our business objectives."},{"title":"Compliance","content":"I oversee regulatory compliance related to AI implementations in the Factory AI Regulatory Sandbox. My responsibilities include ensuring adherence to industry standards, conducting risk assessments, and collaborating with legal teams to navigate the complexities of AI regulations, thereby safeguarding our company's interests."}]},"best_practices":null,"case_studies":[{"company":"Siemens","subtitle":"Implemented AI models using production data to selectively perform x-ray tests on printed circuit boards in factory lines.","benefits":"Increased production line throughput by reducing x-ray tests by 30%.","url":"https:\/\/www.controleng.com\/four-ai-case-study-successes-in-industrial-manufacturing\/","reason":"Demonstrates AI's role in optimizing inspection processes, providing a controlled testing approach akin to regulatory sandboxes for factory efficiency.","search_term":"Siemens AI factory x-ray inspection","case_study_image":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/factory_ai_regulatory_sandbox\/case_studies\/siemens_case_study.png"},{"company":"Bosch","subtitle":"Piloted generative AI to create synthetic images for training defect detection models and predictive maintenance in plants.","benefits":"Reduced AI inspection system ramp-up from 12 months to weeks.","url":"https:\/\/verysell.ai\/ai-in-manufacturing-5-inspiring-real-world-success\/","reason":"Highlights synthetic data use to overcome training challenges, showcasing sandbox-like piloting for robust AI deployment in manufacturing.","search_term":"Bosch generative AI factory inspection","case_study_image":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/factory_ai_regulatory_sandbox\/case_studies\/bosch_case_study.png"},{"company":"FREYR","subtitle":"Developed virtual battery factory digital twin with 3D simulations of infrastructure, machinery, and production processes.","benefits":"Enabled agile simulation of new factories and process changes.","url":"https:\/\/www.controleng.com\/four-ai-case-study-successes-in-industrial-manufacturing\/","reason":"Illustrates digital twins for risk-reduced factory planning, exemplifying controlled AI testing environments similar to regulatory sandboxes.","search_term":"FREYR virtual battery factory simulation","case_study_image":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/factory_ai_regulatory_sandbox\/case_studies\/freyr_case_study.png"},{"company":"Siemens","subtitle":"Utilized AI for predictive maintenance and process automation in manufacturing factory operations.","benefits":"Achieved improvements in equipment reliability and process efficiency.","url":"https:\/\/verysell.ai\/ai-in-manufacturing-5-inspiring-real-world-success\/","reason":"Shows effective AI integration in factories, serving as a model for regulatory sandbox initiatives in predictive technologies.","search_term":"Siemens AI predictive maintenance factory","case_study_image":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/factory_ai_regulatory_sandbox\/case_studies\/siemens_case_study.png"}],"call_to_action":{"title":"Ignite Your AI Transformation Today","call_to_action_text":"Seize the Factory AI Regulatory Sandbox <\/a> opportunity to revolutionize your manufacturing processes. Stay ahead of competitors and unlock unparalleled efficiency and innovation now.","call_to_action_button":"Take Test"},"challenges":null,"ai_initiatives":{"values":[{"question":"How are you aligning AI compliance with industry regulations in manufacturing?","choices":["Not started","In development","Pilot phase","Fully integrated"]},{"question":"What strategies are you using to mitigate AI risks in your factory operations?","choices":["No strategy","Basic guidelines","Risk assessment","Proactive measures"]},{"question":"How are you measuring AI's impact on production efficiency and quality control?","choices":["No metrics","Basic KPIs","Advanced analytics","Continuous improvement"]},{"question":"What level of employee training is in place for AI technologies in your factories?","choices":["None","Basic training","Regular workshops","Comprehensive programs"]},{"question":"How are you integrating AI insights into your supply chain decision-making processes?","choices":["Not applicable","Manual integration","Semi-automated","Fully automated"]}],"action_to_take_ai_initiatives":"Next"},"left_side_quote":[{"text":"Factory is among the first organizations worldwide to adopt ISO 42001.","company":"Factory","url":"https:\/\/factory.ai\/security","reason":"Factory's adoption of ISO 42001 establishes secure AI standards for enterprise coding agents, akin to a regulatory sandbox by sandboxing environments and enforcing compliance in manufacturing software development."},{"text":"AI Factories built with NetApp can address enterprise AI security challenges.","company":"NetApp","url":"https:\/\/www.netapp.com\/blog\/enterprise-ai-security-zero-trust-ai-factory\/","reason":"NetApp's zero-trust AI Factory exceeds basic sandboxes, providing governance and security for production-scale AI in manufacturing, enabling compliant innovation across hybrid environments."},{"text":"The plan's emphasis on regulatory sandboxes presents a unique opportunity.","company":"General Catalyst","url":"https:\/\/www.generalcatalyst.com\/stories\/americas-ai-action-plan","reason":"General Catalyst highlights regulatory sandboxes for AI deployment, supporting manufacturing firms in testing bounded AI use cases compliantly, bridging to factory AI implementation."},{"text":"AI adoption and anticipated regulatory challenges will affect manufacturing.","company":"Snowflake","url":"https:\/\/www.snowflake.com\/en\/blog\/ai-manufacturing-2025-predictions\/","reason":"Snowflake predicts measured AI strategies in manufacturing amid regulations, paralleling Factory AI Regulatory Sandbox by emphasizing proven value and compliance for industrial applications."}],"quote_1":null,"quote_2":{"text":"The regulatory environment is becoming a challenge for AI adoption in manufacturing operations, and industry groups are advocating for a moratorium on new state-level AI regulations to provide clarity for innovation.","author":"Michael Richards, Executive Director, Policy, U.S. Chamber of Commerce Technology Engagement Center","url":"https:\/\/flexpackvoice.com\/2025\/09\/02\/business-groups-highlight-concerns-of-ai-in-manufacturing\/","base_url":"https:\/\/www.uschamber.com","reason":"Highlights regulatory challenges as a barrier to AI implementation, akin to needing a sandbox for safe testing without fragmented rules in non-automotive manufacturing."},"quote_3":null,"quote_4":{"text":"Every industry and company that has factories will have two factories in the future: one for what they build and one for the mathematicsthe factory for the AI.","author":"Jensen Huang, CEO of Nvidia","url":"https:\/\/fortune.com\/2025\/03\/20\/nvidia-ceo-jensen-huang-general-motors-tesla-waymo-toyota-mercedes-benz-volvo-hyundai-artificial-intelligence-gtc\/","base_url":"https:\/\/www.nvidia.com","reason":"Predicts transformative AI infrastructure needs, relating to regulatory sandboxes enabling dedicated AI factory testing for optimized non-automotive manufacturing."},"quote_5":{"text":"Applying generative AI to our operations has enabled software to handle 80 percent of equipment setup for new production runs faster than humans, with AI-robotics combos resolving issues more quickly.","author":"Young Liu, Chairman of Foxconn","url":"https:\/\/www.theregister.com\/2025\/05\/20\/foxconn_chair_ai_manufacturing_predictions\/","base_url":"https:\/\/www.foxconn.com","reason":"Demonstrates tangible AI benefits in efficiency and problem-solving, supporting sandboxes for safe experimentation in scaling AI across manufacturing factories."},"quote_insight":{"description":"56% of global manufacturers now use AI in maintenance or production operations, marking a shift from pilots to scaled deployment","source":"f7i.ai Industrial AI Statistics","percentage":56,"url":"https:\/\/f7i.ai\/blog\/industrial-ai-statistics-2026-the-hard-data-behind-manufacturings-transformation","reason":"This rise from 18% in 2023 highlights Factory AI Regulatory Sandbox enabling safe scaling in non-automotive manufacturing, reducing pilot failure from 70% to 30% for efficiency and competitiveness."},"faq":[{"question":"What is Factory AI Regulatory Sandbox and its role in manufacturing?","answer":["Factory AI Regulatory Sandbox provides a controlled environment for testing AI technologies.","It helps manufacturers innovate while ensuring compliance with industry regulations.","Companies can simulate real-world scenarios without risking operational disruptions.","The sandbox encourages collaboration between regulators and industry stakeholders.","Ultimately, it accelerates the adoption of AI solutions tailored for manufacturing needs."]},{"question":"How do I start implementing Factory AI Regulatory Sandbox in my organization?","answer":["Begin by assessing your current AI capabilities and infrastructure readiness.","Engage stakeholders to define objectives and expected outcomes for the sandbox.","Develop a pilot project that aligns with your strategic goals and resource availability.","Utilize expert guidance to navigate regulatory frameworks and compliance requirements.","Monitor progress and adjust strategies based on feedback and performance metrics."]},{"question":"What measurable benefits can AI bring to manufacturing processes?","answer":["AI enhances production efficiency by optimizing workflows and reducing waste.","It enables predictive maintenance, minimizing downtime and saving costs.","Data-driven insights lead to better decision-making and strategic planning.","Companies gain a competitive edge through faster product development cycles.","Improved quality control processes result in higher customer satisfaction rates."]},{"question":"What challenges may arise when adopting AI in manufacturing?","answer":["Common challenges include data quality issues and integration complexities.","Resistance to change from employees can hinder successful implementation.","Regulatory compliance can pose obstacles during the adoption phase.","Limited understanding of AI's capabilities affects strategic deployment.","Establishing a robust change management strategy can mitigate these risks."]},{"question":"When should a manufacturing firm consider using the Factory AI Regulatory Sandbox?","answer":["Consider the sandbox when exploring innovative AI solutions for existing processes.","Its ideal for organizations seeking to mitigate regulatory risks in AI adoption.","Timing is crucial when launching new products requiring compliance validation.","Use the sandbox during early-stage development to refine AI models.","Evaluate your organization's readiness to embrace AI-driven transformations."]},{"question":"What are some sector-specific applications of Factory AI Regulatory Sandbox?","answer":["The sandbox can facilitate testing AI for quality assurance processes in manufacturing.","It supports the optimization of supply chain management through predictive analytics.","Companies can experiment with AI-driven inventory management solutions effectively.","Testing automated inspection systems for defect detection enhances production quality.","Sandbox environments foster innovation in developing sustainable manufacturing practices."]},{"question":"Why should manufacturers invest in AI-driven solutions through a regulatory sandbox?","answer":["Investing in AI solutions can significantly reduce operational costs over time.","The regulatory sandbox minimizes risks associated with compliance while innovating.","It fosters a culture of experimentation and continuous improvement within teams.","Manufacturers can quickly adapt to market changes through agile AI implementations.","AI technologies can lead to enhanced product quality and customer satisfaction."]}],"ai_use_cases":null,"roi_use_cases_list":null,"leadership_objective_list":null,"keywords":{"tag":"Factory AI Regulatory Sandbox - Manufacturing","values":[{"term":"Predictive Maintenance","description":"A proactive approach to maintenance that uses AI to predict equipment failures before they occur, reducing downtime and maintenance costs.","subkeywords":null},{"term":"Digital Twins","description":"Virtual replicas of physical assets or processes that use real-time data to simulate and analyze performance for optimization.","subkeywords":[{"term":"Simulation Models"},{"term":"Real-time Data"},{"term":"Predictive Analytics"}]},{"term":"Quality Control Automation","description":"The use of AI technologies to automate inspection and quality assurance processes, ensuring products meet predefined standards.","subkeywords":null},{"term":"Data Governance","description":"Frameworks and processes that ensure data integrity, security, and compliance in AI applications within the manufacturing sector.","subkeywords":[{"term":"Regulatory Compliance"},{"term":"Data Privacy"},{"term":"Quality Standards"}]},{"term":"Smart Manufacturing","description":"Integration of advanced technologies, including AI, IoT, and robotics, to enhance production efficiency and flexibility.","subkeywords":null},{"term":"Machine Learning Algorithms","description":"Statistical methods that enable machines to improve their performance on tasks by learning from data inputs over time.","subkeywords":[{"term":"Supervised Learning"},{"term":"Unsupervised Learning"},{"term":"Reinforcement Learning"}]},{"term":"Operational Efficiency","description":"The capability to deliver products or services in the most cost-effective manner while maintaining high quality and minimizing waste.","subkeywords":null},{"term":"Supply Chain Optimization","description":"AI-driven techniques to improve supply chain processes, enhancing responsiveness to market demand and reducing costs.","subkeywords":[{"term":"Inventory Management"},{"term":"Demand Forecasting"},{"term":"Logistics Automation"}]},{"term":"Human-Machine Collaboration","description":"Innovative interactions between human workers and AI systems to enhance productivity and decision-making in factories.","subkeywords":null},{"term":"Regulatory Compliance Frameworks","description":"Structured guidelines and processes that ensure adherence to local and international regulations regarding AI technologies in manufacturing.","subkeywords":[{"term":"Safety Standards"},{"term":"Environmental Regulations"},{"term":"Ethical Guidelines"}]},{"term":"Process Optimization","description":"Application of AI to refine manufacturing processes, leading to increased throughput, reduced cycle times, and improved quality.","subkeywords":null},{"term":"AI-Driven Analytics","description":"Utilization of AI tools to analyze data for insights that drive decision-making and strategic planning in manufacturing operations.","subkeywords":[{"term":"Predictive Insights"},{"term":"Data Visualization"},{"term":"Performance Metrics"}]},{"term":"Cybersecurity in AI","description":"Strategies and technologies designed to protect AI systems and data from cyber threats, ensuring operational continuity.","subkeywords":null},{"term":"Emerging Technologies","description":"Innovations such as AI, machine learning, and IoT that are reshaping manufacturing processes and business models.","subkeywords":[{"term":"Blockchain"},{"term":"Augmented Reality"},{"term":"Smart Sensors"}]}]},"call_to_action_3":{"description":"Work with Atomic Loops to architect your AI implementation roadmap from PoC to enterprise scale.","action_button":"Contact Now"},"description_memo":null,"description_frameworks":null,"description_essay":null,"pyramid_values":{"title":"AI Governance Pyramid","values":[{"title":"Technical Compliance","subtitle":"Focus on algorithmic fairness and data privacy."},{"title":"Manage Operational Risks","subtitle":"Implement processes and assess potential risks."},{"title":"Direct Strategic Oversight","subtitle":"Set policies and ensure accountability."}]},"risk_analysis":{"title":"Risk Senarios & Mitigation","values":[{"title":"Failing Compliance with Regulations","subtitle":"Legal repercussions; regularly review compliance frameworks."},{"title":"Data Breach Exposing Sensitive Information","subtitle":"Privacy violations; enhance cybersecurity measures proactively."},{"title":"AI Bias Affecting Decision-Making","subtitle":"Inequitable outcomes; conduct regular bias audits."},{"title":"Operational Failures from AI Misalignment","subtitle":"Production downtime; establish continuous monitoring systems."}]},"checklist":["Establish an AI ethics committee for oversight and governance.","Conduct regular audits of AI algorithms for compliance and transparency.","Define clear data usage policies and ensure stakeholder adherence.","Verify AI model performance through continuous monitoring and evaluation.","Implement training programs for staff on AI ethics and governance."],"readiness_framework":null,"domain_data":null,"table_values":null,"graph_data_values":null,"key_innovations":null,"ai_roi_calculator":null,"roi_graph":null,"downtime_graph":null,"qa_yield_graph":null,"ai_adoption_graph":null,"maturity_graph":null,"global_graph":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/graphs\/global_map_factory_ai_regulatory_sandbox_manufacturing_(non-automotive)\/factory_ai_regulatory_sandbox_manufacturing_(non-automotive).png","yt_video":null,"webpage_images":null,"ai_assessment":null,"metadata":{"market_title":"Factory AI Regulatory Sandbox","industry":"Manufacturing (Non-Automotive)","tag_name":"Regulations, Compliance & Governance","meta_description":"Explore how the Factory AI Regulatory Sandbox empowers manufacturers to navigate compliance with AI solutions, ensuring innovation while adhering to regulations.","meta_keywords":"Factory AI Regulatory Sandbox, AI compliance solutions, manufacturing regulations, governance in manufacturing, AI-driven compliance, regulatory frameworks, manufacturing innovation"},"case_study_images":["https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/factory_ai_regulatory_sandbox\/case_studies\/siemens_case_study.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/factory_ai_regulatory_sandbox\/case_studies\/bosch_case_study.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/factory_ai_regulatory_sandbox\/case_studies\/freyr_case_study.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/factory_ai_regulatory_sandbox\/case_studies\/siemens_case_study.png"],"introduction_images":["https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/factory_ai_regulatory_sandbox\/factory_ai_regulatory_sandbox_generated_image.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/factory_ai_regulatory_sandbox\/factory_ai_regulatory_sandbox_generated_image_1.png"],"s3_urls":["https:\/\/atomicloops-website.s3.amazonaws.com\/graphs\/global_map_factory_ai_regulatory_sandbox_manufacturing_(non-automotive","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/factory_ai_regulatory_sandbox\/case_studies\/bosch_case_study.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/factory_ai_regulatory_sandbox\/case_studies\/freyr_case_study.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/factory_ai_regulatory_sandbox\/case_studies\/siemens_case_study.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/factory_ai_regulatory_sandbox\/factory_ai_regulatory_sandbox_generated_image.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/factory_ai_regulatory_sandbox\/factory_ai_regulatory_sandbox_generated_image_1.png"]}