The way healthcare professionals learn is changing rapidly. Across the Asia-Pacific (APAC) region, medical schools, hospitals, and healthcare organizations are increasingly turning to AI and AR to modernize medical education.Traditional medical training, while foundational, often faces limitations in scalability, accessibility, and hands-on practice opportunities. AI and AR technologies are helping bridge these gaps by creating immersive, personalized, and data-driven learning experiences that better prepare clinicians for real-world practice.As healthcare systems across APAC continue to digitize, AI and AR-powered education is emerging as a strategic investment for institutions seeking to develop a future-ready workforce.<h2>Why Medical Education Needs Transformation</h2>Medical knowledge is expanding at an unprecedented pace. New treatments, technologies, and clinical guidelines are continuously introduced, requiring healthcare professionals to engage in lifelong learning.At the same time, healthcare organizations face several challenges:<ul><li>Limited access to clinical training opportunities.</li><li>Growing shortages of healthcare professionals.</li><li>Variations in training quality across regions.</li><li>Increasing complexity of procedures and technologies.</li><li>Rising demand for remote and flexible learning models.</li></ul>Conventional classroom-based approaches alone are no longer sufficient. Digital learning technologies are enabling institutions to provide more standardized, scalable, and engaging educational experiences.<h2>The Rise of AI in Medical Education</h2>AI is transforming medical education by making learning more adaptive, personalized, and efficient.<h3>Personalized Learning Pathways</h3>Every learner progresses differently. AI-powered learning platforms can analyze individual performance, identify knowledge gaps, and automatically tailor educational content to each student's needs.<h3>Intelligent Assessment and Feedback</h3>Traditional assessments often provide delayed feedback. AI systems can evaluate learner performance in real time and deliver immediate insights.Examples include:<ul><li>Automated scoring of clinical simulations.</li><li>AI-based assessment of procedural skills.</li><li>Speech and communication analysis during patient interactions.</li><li>Objective evaluation of surgical techniques.</li></ul>Instant feedback allows learners to continuously refine their skills and accelerate competency development.<h3>Virtual Patients and Clinical Decision Support</h3>AI-powered virtual patients simulate realistic clinical scenarios, enabling learners to practice diagnosis and treatment planning in a safe environment.Students can interact with virtual patients, review symptoms, order tests, and make treatment decisions while receiving guidance throughout the learning process.<h2>How AR Is Reshaping Hands-On Medical Training</h2>Augmented Reality overlays digital information onto the physical world, creating highly immersive educational experiences.Unlike traditional textbooks or videos, AR enables learners to visualize anatomy and procedures in three dimensions.<h3>Immersive Anatomy Education</h3>Understanding human anatomy is fundamental but often challenging.AR applications allow students to:<ul><li>Explore interactive 3D anatomical models.</li><li>Visualize organs from multiple angles.</li><li>Observe physiological processes dynamically.</li><li>Study complex structures without cadavers.</li></ul>Students can interact with holographic organs and systems, leading to deeper comprehension and improved engagement.<h3>Procedure and Surgical Simulation</h3>AR-based simulation platforms are increasingly used to train clinicians on complex procedures before they enter operating rooms.Examples include:<ul><li>Minimally invasive surgery training.</li><li>Catheter insertion practice.</li><li>Orthopedic procedure simulation.</li><li>Ultrasound-guided intervention training.</li></ul>By overlaying digital guidance onto physical models, AR enables repeated practice without risk to patients.<h3>Remote Collaboration and Mentoring</h3>Geographical barriers remain a significant challenge across APAC, particularly in rural and underserved areas.AR-enabled remote collaboration allows experts to guide trainees from different locations in real time.Specialists can:<ul><li>Annotate directly on the trainee's field of view.</li><li>Demonstrate procedures remotely.</li><li>Provide step-by-step guidance during simulations.</li><li>Support continuing medical education programs.</li></ul>This capability is particularly valuable in regions where specialist resources are limited.<h2>Innovation Trends Across Asia-Pacific</h2>The APAC region is becoming a global hub for digital health innovation, with governments, universities, and healthcare providers actively investing in advanced learning technologies.<h3>Singapore: Building Smart Healthcare Talent</h3>Singapore continues to lead digital healthcare adoption in Southeast Asia. Academic institutions and healthcare organizations are increasingly incorporating AI-driven simulations, virtual learning environments, and immersive technologies into medical training programs.The country's strong digital infrastructure and commitment to healthcare innovation make it a key market for next-generation medical education solutions.<h3>Australia: Expanding Simulation-Based Learning</h3>Australia has long been recognized for its advanced simulation centers. Universities and teaching hospitals are increasingly adopting AR and AI technologies to enhance clinical skills training, improve patient safety, and support remote education initiatives.The growing use of virtual patients and immersive procedural training reflects a broader shift toward competency-based education.<h3>Japan: Integrating Robotics, AI, and AR</h3>Japan's aging population and healthcare workforce challenges are accelerating investments in advanced training technologies.Medical institutions are exploring combinations of AI, robotics, AR, and mixed reality to train clinicians more efficiently while supporting continuous professional development.<h3>South Korea: Accelerating Digital Medical Innovation</h3>South Korea's strong technology ecosystem has fueled the rapid adoption of digital learning solutions.Medical schools and hospitals are leveraging AI-powered educational platforms and immersive visualization tools to enhance surgical education and precision medicine training.<h3>Emerging Opportunities in Southeast Asia</h3>Countries such as Vietnam, Thailand, Malaysia, and Indonesia are increasingly investing in digital health ecosystems.As healthcare demand rises, scalable and cost-effective training technologies offer significant potential to:<ul><li>Expand healthcare workforce capacity.</li><li>Improve training accessibility in remote regions.</li><li>Standardize clinical education.</li><li>Support continuing medical education initiatives.</li></ul><h2>Challenges to Adoption</h2>Despite strong momentum, organizations must address several challenges when implementing AI and AR in medical education.<h3>Data Privacy and Security</h3>Educational platforms handling learner and clinical data must comply with local regulatory requirements and maintain robust cybersecurity measures.<h3>Integration with Existing Systems</h3>Many institutions operate legacy learning management systems and hospital infrastructures that may require modernization or interoperability enhancements.<h3>Content Development Complexity</h3>Developing clinically accurate, high-quality immersive content requires close collaboration among healthcare professionals, educators, designers, and technology teams.<h3>Technology Accessibility</h3>Institutions must ensure that advanced learning technologies remain accessible, scalable, and cost-effective, particularly in resource-constrained settings.<h2>The Future of Medical Education in APAC</h2>The convergence of AI and AR is reshaping how healthcare professionals are educated across Asia-Pacific.Future learning environments are expected to become increasingly intelligent, immersive, and data-driven. Adaptive learning platforms, mixed reality simulations, digital twins, and automated competency assessments will likely become standard components of medical education ecosystems.As healthcare continues to evolve, organizations that invest in these technologies today will be better positioned to build highly skilled, future-ready workforces capable of delivering better patient outcomes.

AI + AR in Medical Education: Innovation Trends Across Asia-Pacific

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<h2>How Organizations Can Innovate with AI While Meeting Compliance, Security, and Trust Requirements</h2>AI is rapidly transforming industries worldwide. From automating clinical documentation in healthcare to accelerating risk assessment in financial services and improving quality control in manufacturing, AI is becoming a critical business capability.However, organizations operating in regulated industries face a unique challenge: how to harness the power of AI while maintaining strict security, compliance, privacy, and governance standards.For sectors such as healthcare, banking, insurance, life sciences, telecommunications, and government services, AI adoption cannot come at the expense of regulatory obligations. Security must be built into the foundation of every AI application, not added as an afterthought.This is why organizations are increasingly shifting their focus from simply deploying AI models to building secure, enterprise-grade AI solutions that are designed for compliance from day one.<h2>AI Introduces New Security Challenges</h2>Unlike traditional software, AI systems often process large volumes of sensitive data and generate dynamic outputs. This creates new risks, including data leakage, unauthorized access, model manipulation, and compliance violations.For example, healthcare AI applications may handle patient records, while financial AI systems analyze customer transactions and personal information. Any security failure can lead to regulatory penalties, reputational damage, and loss of customer trust.This makes security a fundamental requirement rather than an afterthought.<h2>Strong Data Governance Comes First</h2>Secure AI starts with strong data governance. Organizations need clear policies for how data is collected, stored, accessed, and used throughout the AI lifecycle.In regulated environments, maintaining control over sensitive information is critical. Effective governance helps ensure compliance, improves transparency, and reduces the risk of data misuse.Many AI initiatives succeed or fail based on the quality and governance of their data rather than the sophistication of the model itself.<h2>Embedding Security Throughout the AI Lifecycle</h2>Security should be integrated into every stage of AI development, from design and training to deployment and ongoing operations.Modern MLOps and LLMOps practices help organizations automate security checks, monitor model behavior, and maintain compliance without slowing innovation. By adopting a security-by-design approach, teams can identify risks early and build more resilient AI solutions.<h2>Transparency Builds Trust</h2>In regulated industries, organizations often need to explain how AI-driven decisions are made. Whether supporting clinical recommendations or fraud detection, AI systems must be transparent and auditable.Monitoring, logging, and governance mechanisms help organizations maintain visibility into model behavior while meeting regulatory expectations. Transparency not only supports compliance but also increases confidence among users, customers, and regulators.<h2>The Future of Enterprise AI</h2>As AI adoption grows, security and governance are becoming key differentiators. Organizations are moving beyond isolated AI experiments and investing in enterprise-grade platforms that combine data protection, access controls, model governance, and continuous monitoring.At the same time, responsible AI principles such as fairness, accountability, and explainability are becoming essential components of AI strategies.<h2>Conclusion</h2>Building AI applications for regulated industries requires far more than selecting the right model or technology stack. Success depends on creating secure, compliant, and governable systems that protect sensitive data, meet regulatory requirements, and maintain stakeholder trust.By adopting security-by-design principles, implementing robust governance frameworks, and integrating secure MLOps practices, organizations can confidently deploy AI solutions that drive business value without compromising compliance or security.As AI continues to reshape industries, the organizations that prioritize trust, security, and responsible innovation will be the ones that unlock its full potential.

Building Secure AI Applications for Regulated Industries

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Pharma 5.0: How ALTEN accelerates digital transformation to cut time to market?The pharmaceutical industry faces a critical challenge: bringing life-saving treatments to market faster without compromising quality. Digital transformation powered by AI is reshaping how pharma companies operate, from clinical trials to quality control.&nbsp; &nbsp; For François Portier, Digital Transformation and Industrial Excellence Expert at ALTEN, the shift is clear: “Today, AI isn’t just an option; it’s the key to unlocking efficiency and innovation in pharma.”But how can AI bridge the gap between data overload and actionable insights and what role does ALTEN play in this transition?The pharma industry’s digital dilemmaPharma’s traditional processes reliant on manual documentation, siloed data, and human monitoring are no longer sustainable. 75% of pharma companies are small enterprises, many still using pen-and-paper systems. Meanwhile, larger firms struggle to integrate AI into existing workflows.Key pain points:Time-consuming compliance: Certification and deviation report often start from scratch, delaying critical decisions.Inefficient quality control: Manual inspections (e.g., visual checks for bottle defects) are slow and prone to error.Data underutilisation: Historically, 70% of pharma data went unused until AI made it actionable."Five years ago, we focused on automation, today, we’re deploying customised and flexible processes with AI solutions", notes François Portier.ALTEN’s approach: AI as a Business acceleratorALTEN collaborates with partners and customers to deploy AI where it matters most, reducing time to market while ensuring compliance and quality.Generative AI is reshaping how pharmaceutical engineers handle documentation. By auto-filling templates with historical data, it cuts report drafting time from two hours to just 20 minutes, while automating compliance checks and flagging regulatory gaps instantly.&nbsp;"AI doesn't replace expertise, it enhances it", notes François Portier: engineers stay focused on high-value decisions while AI handles the rest.On the production floor, computer vision detects defects in real time with greater accuracy than manual inspection. Predictive analytics then simulates clinical trial parameters to reduce failure risks before testing begins.&nbsp;“With only 14% of trials reaching success, AI helps prioritise the most promising paths," François Portier emphasises.ALTEN tailors its approach to each organisation's level of digital maturity. Smaller firms begin with data digitisation using no-code tools, while larger enterprises deploy agentic AI to unify operational and IT data. There is no single model: the right solution depends on where a company stands today and where it needs to go.The human-AI partnership: skills for the futureAI’s rise doesn’t diminish human roles, it redefines them. ALTEN emphasises upskilling teams to:Combine hard skills (e.g., IoT/robotics programming) with industry knowledge.Develop soft skills like problem-solving and project ownership. "The future engineer is strategic, not just technical", François Portier asserts."For pharma, the message is clear: AI isn’t a threat, it’s the tool to deliver treatments faster, more safely, and more effectively, with greater personalisation for patients."&nbsp;About our expertFrançois PortierDigital Transformation &amp; Industrial Excellence Expert at ALTEN FranceFrançois Portier drives AI-powered innovation in pharma, helping companies reduce time to market while ensuring quality and compliance. With expertise in generative AI, computer vision, and predictive analytics, he tailors solutions to each organisation’s digital maturity, from low-code tools for small firms to agentic AI for large enterprises.A firm believer in human-AI collaboration, François focuses on upskilling teams to blend technical skills with strategic thinking.Connect with François Portier: <a href="https://fr.linkedin.com/in/francoisportier/fr">LinkedIn Profile</a>&nbsp;

The pharmaceutical industry faces a critical challenge: bringing life-saving treatments to market faster without compromising quality. Digital transformation powered by AI is reshaping how pharma companies operate, from clinical trials to quality control. 
 
For François Portier, Digital Transformation and Industrial Excellence Expert at ALTEN, the shift is clear: "Today, AI isn’t just an option; it’s the key to unlocking efficiency and innovation in pharma."

Pharma 5.0: How digital transformation cuts time to market

The pharmaceutical industry faces a critical challenge: bringing life-saving treatments to market faster without compromising quality..

How ALTEN accelerates digital transformation to cut time to market?

how-alten-accelerates-digital-transformation-to-cut-time-to-market

FROM READING TEXT TO UNDERSTANDING THE WORLD: THE RISE OF MULTIMODAL AIIn the era of digital transformation, humans consume information through multiple channels concurrently speech, text, images, videos, and sensor data. As a result, traditional AI systems designed to process only a single type of data are gradually losing their competitive edge. By 2026, Multimodal AI is no longer an experimental concept, it has become a foundational technology for modern enterprises, enabling machines to perceive and understand the world in a far more comprehensive way. The Multimodal AI market is experiencing rapid growth and is projected to reach a value of USD 10.89 billion by 2030 (Emerline, 2026).1. Definition of Multimodal AIMultimodal AI refers to artificial intelligence systems designed to process and integrate multiple forms of data simultaneously, including text, images, audio, video, and sensor inputs. Its operating mechanism mirrors how humans perceive the world and consists of three key stages:<ul><li>Encoding: Specialized models analyze each type of data independently (e.g., computer vision for images, natural language processing for text…).</li><li>Fusion: This is the most critical stage, where information from different modalities is combined into a shared representation, allowing AI to understand relationships across data sources.</li><li>Generation/Inference:&nbsp;The AI generates outputs in various formats based on the integrated information (e.g., providing a text-based response to an uploaded image).</li></ul>2. Key benefits of Multimodal AIThe shift from single-modal AI to multimodal AI offers significant advantages, bringing machine intelligence closer to human-level perception.Comprehensive context understandingBy simultaneously processing text, images, audio, and sensor data, AI gains a richer and more holistic understanding of situations and tasks. This enables systems to interpret subtle non-verbal signals and contextual information that would otherwise be missed.Higher accuracy and resilienceMultimodal systems can achieve over 40% higher accuracy in complex tasks compared to traditional AI approaches (Stanford's AI Index Report, 2024). They are also more resilient to incomplete or noisy data. For example, if an image is blurry, the AI can rely on accompanying text or audio to maintain accurate performance. Faster decision-makingOrganizations adopting multimodal AI solutions report up to 40% faster decision-making cycles (Vyzer Solutions, 2026). By synthesizing insights from multiple data sources, businesses can detect market changes earlier, respond more effectively, and achieve stronger returns on AI investments.3. Leading Multimodal AI models in 2026By 2026, the market will no longer be dominated by a single model. Instead, it is shaped by specialized systems designed for different use cases:&nbsp;<ul><li>GPT-4o &amp; GPT-5 (OpenAI):&nbsp;GPT-4o ("omni") processes text, images, and audio in real time with extremely low latency, enabling natural voice-based interactions. GPT-5 introduces a layered architecture designed to balance speed and expert-level reasoning capabilities.</li><li>Gemini 3.5 Pro &amp; Flash (Google):&nbsp;Gemini stands out for its native multimodal architecture and massive context window of up to one million tokens, allowing users to analyze lengthy videos or large document collections within a single query.</li><li>Claude 4.5 Sonnet (Anthropic):&nbsp;Built with a strong focus on safety, Claude is optimized for autonomous software engineering tasks and is capable of resolving more than 70% of real-world technical issues.</li><li>Llama 4 Scout (Meta):&nbsp;An open-source model featuring a context window of up to 10 million tokens, enabling organizations to deploy and operate AI on private infrastructure while maintaining full control over their data.</li><li>Moonshot Kimi K2:&nbsp;A Mixture-of-Experts (MoE) model with one trillion parameters, designed for customer service automation and highly natural conversational experiences.</li></ul>3. Global use cases of Multimodal AICustomer Support &amp; SalesTechnical support teams can analyze screenshots alongside customer descriptions to diagnose issues much faster and more accurately. Sarah SDR by Ruh AI is an example of an autonomous sales agent capable of analyzing a prospect's website (images), social media presence (text), and communication history to create personalized outreach strategies without step-by-step human intervention.HealthcareMultimodal AI systems have been shown to improve diagnostic accuracy by 6% to 33% when assisting radiologists and medical professionals compared to single-modal approaches (Nature Medicine, 2025). IBM Watson Health combines Electronic Health Records, medical imaging data such as X-rays and MRIs, and clinical notes to predict treatment outcomes with enhanced accuracy.Retail &amp; E-CommerceConsumers can simply take a photo of a product they like and instantly discover similar items online. The system combines visual information with browsing behavior and personal preferences to generate highly relevant recommendations. Retailers are leveraging web activity, purchase history, and product images to improve recommendation quality, boost conversion rates, and strengthen customer loyalty.Transportation &amp; LogisticsMultimodal AI is transforming supply chain operations by simultaneously analyzing real-time GPS data, warehouse sensors, weather conditions, and demand forecasts to optimize routing decisions and minimize delays. Toyota provides a compelling example through its AI-powered digital vehicle manuals, which combine text, images, and real-world vehicle context to deliver more intuitive user support.Financial Services &amp; BankingBanks have reduced document processing times from contracts and signatures to official forms, from hours to just minutes, while improving accuracy from 92% to 98% (Deloitte's Banking and Capital Markets Report, 2025). By analyzing transaction history, customer behavior, and device signals simultaneously, AI can identify anomalies and fraudulent activities that traditional systems often overlook. JPMorgan's DocLLM combines textual information, metadata, and contextual signals from complex financial documents to enhance risk assessment and decision-making accuracy.4. Opportunities for VietnamVietnam is rapidly emerging as one of Southeast Asia's most promising AI development hubs, supported by several strategic advantages.Talent and Cost competitivenessVietnam's AI engineering workforce offers competitive expertise at approximately 87% lower cost than Silicon Valley. The country aims to develop a talent pool of 15,000 AI specialists by 2035. (VietNam Net, 2026)National AI strategyThe Vietnamese government has approved a National AI Strategy through 2030, with the goal of positioning Vietnam among the top four AI nations in ASEAN and the top 50 globally.Real-world Multimodal AI applications in Vietnam<ul><li>TPBank has introduced VoicePay, enabling customers to transfer money through voice commands.</li><li>VinBrain provides AI-powered diagnostic solutions that support medical professionals.</li><li>VinFast is investing in AI-enabled robotics to optimize manufacturing and assembly operations.</li></ul>Growing Interest from Global Technology LeadersGlobal technology companies such as NVIDIA and Google are actively partnering with Vietnamese firms to develop AI talent and accelerate AI adoption across industries.5. VMO's competitive advantages in the Multimodal AI era&nbsp;As Multimodal AI moves from experimentation to large-scale enterprise adoption, competitive advantage no longer belongs solely to organizations with access to advanced AI models. Instead, it belongs to those that can integrate AI into complex business environments, connect fragmented data sources, and transform technological capabilities into measurable business outcomes.With strong expertise across AI, Data, Cloud, IoT, and enterprise software development, VMO is well-positioned to capitalize on the rise of Multimodal AI. These capabilities are particularly valuable in multimodal environments, where success depends not only on model performance but also on scalable infrastructure, data integration, domain knowledge, and effective execution.Over the years, VMO has delivered AI-driven and digital transformation solutions for organizations across global markets. Supported by a global delivery model, a talented engineering workforce, and extensive experience serving international clients, VMO is well positioned to help enterprises accelerate Multimodal AI adoption and unlock fully business value from this transformation.6. ConclusionMultimodal AI is more than just another technological advancement, it represents a fundamental shift in how organizations process and extract value from data. By combining vision, language, audio, and sensor intelligence, AI is evolving into the eyes, ears, and brain of modern enterprises. By 2026, AI has moved well beyond the experimentation phase and is becoming deeply embedded in mission-critical business operations. Organizations that invest early in robust data infrastructure and develop teams capable of leveraging multimodal AI will be best positioned to maintain a competitive advantage throughout the next decade.

In the era of digital transformation, humans consume information through multiple channels concurrently speech, text, images, videos, and sensor data. As a result, traditional AI systems designed to process only a single type of data are gradually losing their competitive edge. By 2026, Multimodal AI is no longer an experimental concept, it has become a foundational technology for modern enterprises, enabling machines to perceive and understand the world in a far more comprehensive way. The Multimodal AI market is experiencing rapid growth and is projected to reach a value of USD 10.89 billion by 2030 (Emerline, 2026).

THE RISE OF MULTIMODAL AI: UNDERSTANDING THE WORLD

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Quantum AI: Vietnam's Next Strategic OpportunityThe period 2026 - 2030 is expected to be a pivotal phase as quantum technologies move beyond research laboratories and into real-world commercial applications. At the center of this transition lies Quantum AI (the convergence of quantum computing and AI), which promises computational capabilities far beyond the limits of today’s most powerful classical supercomputers. The world is approaching a major technological inflection point beyond the era of artificial intelligence. As the AI race becomes increasingly competitive and mature, global powers including the United States, China, Japan, and the European Union are investing billions of dollars into the next transformative wave:&nbsp;quantum technology.<h3>1. Definition of Quantum AI</h3>Quantum AI combines quantum computing and artificial intelligence to accelerate and enhance the way machines learn from data.Unlike classical computers, which process information using bits that represent either 0 or 1, quantum computers operate with quantum bits, or qubits. Through the principle of superposition, a qubit can represent multiple states simultaneously, allowing quantum systems to explore vast numbers of possible solutions at once.Today, Quantum AI is primarily deployed through hybrid architectures. Quantum processors handle highly complex optimization and feature-extraction tasks, while classical GPUs perform model training and deployment.The Quantum AI landscape can generally be divided into three levels:<ul><li>Quantum-enhanced classical AI</li><li>Quantum Machine Learning&nbsp;</li><li>Fully quantum-native AI systems, which remain largely theoretical at this stage</li></ul><h3>2. The potential impact of Quantum AI</h3><h4>Accelerating model training and optimization</h4>Quantum optimization algorithms and hybrid computing architectures have the potential to significantly reduce AI training workloads, with some studies suggesting processing speed improvements of up to 20 times without requiring additional hardware investments.Development cycles that traditionally take months could potentially be reduced to days, enabling organizations to bring products to market faster and gain competitive advantages.<h4>Solving high-dimensional problems</h4>Quantum AI can process datasets containing billions of variables problems where classical computing often encounters performance congestion. In aerospace and defense applications, quantum-inspired solvers have demonstrated computational fluid dynamics (CFD) simulations up to 25 times faster while achieving processing efficiencies as high as 100 times compared to conventional approaches.<h4>Improving accuracy and reducing errors</h4>Quantum-based feature extraction can uncover hidden patterns within highly complex datasets, improving forecasting accuracy and reducing false-positive rates in critical monitoring and surveillance systems<h4>Optimizing R&amp;D process and costs</h4>Quantum AI-driven simulation platforms have the potential to shorten research and development cycles by a factor of 10 to 20 while significantly lowering computational costs and improving resource efficiency across innovation projects.<h3>3. Breakthrough Applications Across Industries</h3>Quantum AI is particularly valuable for solving highly complex, multidimensional challenges that conventional computing struggles to address effectively.<h4>Financial Services&nbsp;</h4>Major financial institutions such as JPMorgan Chase, Goldman Sachs, and HSBC are exploring quantum algorithms for portfolio optimization, Monte Carlo risk simulations, and fraud detection.One notable example is Quantinuum's H-Series systems, which support certified quantum randomness and enhanced security solutions for digital assets.<h4>Healthcare and Drug Discovery</h4>Quantum AI can simulate complex molecular interactions, accelerating drug discovery and enabling more personalized diagnostics based on genetic data.<h4>Manufacturing and Logistics</h4>Applications include predictive maintenance, large-scale supply chain optimization involving thousands of variables, and route planning for global transportation networks.<h4>Energy</h4>Quantum AI can help balance smart power grids and optimize the performance of critical infrastructure assets such as wind turbines and energy distribution systems.<h4>Cybersecurity</h4>Companies such as SandboxAQ are developing solutions like AQtive Guard to help organizations assess and migrate toward post-quantum cryptography (PQC). At the same time, Cloudflare has begun integrating quantum-resistant cryptographic algorithms into its global network infrastructure to better protect internet traffic against future quantum threats.<h3>4. Risks of applying Quantum AI</h3>Cryptographic vulnerabilities:&nbsp;Future quantum computers could potentially break widely used encryption standards such as RSA and ECC. One growing concern is the "harvest now, decrypt later" strategy, where attackers collect encrypted data today with the expectation of decrypting it once sufficiently powerful quantum computers become available.Hardware limitations:&nbsp;Current qubits remain highly sensitive to environmental interference, resulting in computational errors and requiring sophisticated ultra-low-temperature cooling systems.Talent and Cost barriers:&nbsp;Quantum computing development requires expertise across quantum mechanics, mathematics, computer science, and AI, creating a global shortage of qualified talent.<h3>5. Five strategic opportunities for Vietnam</h3>Vietnam is well-positioned to participate in the next wave of technological transformation, supported by several structural advantages like a young workforce and a strong STEM talent pipeline. Here are five major opportunities in the emerging Quantum AI era.Becoming part of the Post-AI technology value chain:&nbsp;Vietnam can position itself as a critical node within the next-generation technology ecosystem, similar to its growing role in semiconductors and traditional AI development.Developing specialized hardware capabilities:&nbsp;Rather than competing across the entire value chain, Vietnam could focus on high-value supporting segments such as advanced materials, superconducting components, precision manufacturing, and specialized quantum hardware subsystems.Attracting global R&amp;D investment:&nbsp;By leveraging partnerships with technology leaders such as IBM and NVIDIA, Vietnam can strengthen its domestic quantum ecosystem and attract high-value research and development initiatives.Building a Quantum-Native startup ecosystemStartups can leverage quantum simulation capabilities to create solutions for strategic sectors such as agriculture, materials science, and logistics optimization.Establishing Quantum-Safe digital infrastructureProactively adopting post-quantum cryptography standards will help safeguard financial systems, critical infrastructure, and national data assets against future quantum threats.<h3>6. A Strategic Roadmap for 2026–2030</h3><h3>Phase 1: Awareness &amp; Action</h3>The priority is to move beyond theoretical discussions and begin practical implementation. Key initiatives include auditing national cryptographic infrastructure and launching pilot post-quantum security across critical systems.<h3>Phase 2: Hybrid integration &amp; Software infrastructure</h3>Organizations should invest in data centers capable of integrating quantum co-processors while expanding AI-powered simulation platforms that reduce R&amp;D costs and shorten product development cycles.<h3>Phase 3: Industrialization &amp; Technological Sovereignty</h3>The final stage involves scaling Quantum AI applications across domestic enterprises and embedding them into critical sectors of the economy, creating long-term technological capabilities and competitive advantages.<h3>Conclusion</h3>Quantum AI is no longer a futuristic concept. It is rapidly emerging as a strategic driver of industrial competitiveness, economic growth, and national security. For Vietnam, the coming years represent a unique window of opportunity. Early investment in talent development, digital infrastructure, and practical adoption strategies will not only help the country keep pace with global technological shifts but may also position it to lead in selected high-value niches..“The decisions made today could determine Vietnam’s role in the next technological revolution.”

Quantum AI: Vietnam's Next Strategic Opportunity

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Healthcare is undergoing one of the largest digital transformations in its history. From AI-assisted diagnostics and remote patient monitoring to digital therapeutics and connected medical devices, HealthTech companies are under increasing pressure to innovate faster while maintaining strict compliance, security, and reliability standards.To meet these demands, many HealthTech organizations are rethinking where and how they build engineering teams. Increasingly, Vietnam is emerging as a strategic destination for expanding technology capabilities - not simply as an outsourcing location, but as a long-term engineering hub.<h2>The Growing Talent Challenge in HealthTech</h2>Across North America, Europe, and parts of the Asia-Pacific, HealthTech companies face a common challenge: finding specialized engineering talent at scale.The demand for software engineers, cloud architects, AI specialists, cybersecurity professionals, and healthcare data experts continues to outpace supply. Competition from fintech, big tech, and AI startups further intensifies the talent shortage.For many HealthTech organizations, building internal teams exclusively in high-cost markets has become increasingly difficult due to:<ul><li>Rising engineering salaries</li><li>Lengthy recruitment cycles</li><li>High employee turnover</li><li>Limited access to niche technical skills</li></ul>As a result, global HealthTech leaders are adopting distributed engineering models that combine local domain expertise with global development capabilities.<h2>Why Vietnam Is Gaining Attention</h2>Vietnam's technology ecosystem has evolved significantly over the past decade.The country now graduates tens of thousands of engineering and IT professionals annually, with strong foundations in software development, mathematics, data science, and computer engineering. Many engineers are experienced in working with international clients and distributed teams across multiple time zones.Several factors make Vietnam particularly attractive for HealthTech organizations.<h3>Strong Engineering Capability</h3>Vietnam has developed a mature software engineering sector that supports complex enterprise systems, cloud platforms, AI solutions, and regulated digital products.Engineering teams increasingly possess experience in:<ul><li>Healthcare software platforms</li><li>Electronic Health Records (EHR)</li><li>Telehealth applications</li><li>Medical device software</li><li>Data analytics and AI solutions</li><li>Cloud-native healthcare systems</li></ul>This enables HealthTech companies to access talent capable of contributing beyond simple development tasks and into product innovation and architecture design.<h3>Cost Efficiency Without Compromising Quality</h3>Cost remains a consideration, but the conversation has shifted.HealthTech companies are no longer looking solely for the lowest-cost destination. Instead, they seek locations where engineering quality, scalability, and business value align.Vietnam offers a favorable balance between cost and capability, allowing organizations to invest more resources into product innovation, regulatory readiness, and customer growth while maintaining engineering capacity.<h3>Growing AI and Data Expertise</h3>Healthcare is increasingly becoming a data-driven industry.Applications involving predictive analytics, medical imaging, clinical decision support, and personalized medicine require strong AI and data engineering capabilities.Vietnam's growing AI ecosystem—supported by universities, research institutions, and technology companies—is producing engineers with expertise in machine learning, computer vision, large language models, and data platform development.These skills are becoming highly relevant as HealthTech companies integrate AI into their products and operations.<h2>Healthcare Innovation Requires Global Engineering Models</h2>Many successful HealthTech companies no longer view engineering as being tied to a single geography.Instead, they build globally distributed teams where different locations contribute complementary strengths.A common model includes:<ul><li>Product strategy and clinical leadership in headquarters locations</li><li>Engineering and platform development in technology hubs</li><li>Regional teams supporting localization and customer requirements</li></ul>This approach enables organizations to scale development capacity while maintaining close collaboration between business, clinical, and technical stakeholders.Vietnam increasingly fits into this model as a strategic engineering center rather than simply a delivery location.<h2>The Importance of Healthcare Domain Knowledge</h2>Technical capability alone is not enough in healthcare.Engineers working on HealthTech products must understand the unique challenges of the industry, including:<ul><li>Data privacy requirements</li><li>Patient safety considerations</li><li>Regulatory frameworks</li><li>Interoperability standards</li><li>Clinical workflows</li><li>Security and compliance expectations</li></ul>As Vietnam's technology sector gains more exposure to healthcare projects, local engineering teams are accumulating valuable domain expertise that allows them to contribute more effectively to complex HealthTech initiatives.This trend is helping HealthTech companies accelerate product development while reducing onboarding and knowledge transfer challenges.<h2>Looking Ahead</h2>As HealthTech organizations establish engineering capabilities in Vietnam, they often look for partners that can provide both technical expertise and experience working in regulated healthcare environments.Many companies start with a small dedicated team focused on a specific product, platform, or innovation initiative before gradually expanding their presence. This model allows organizations to access engineering talent quickly while maintaining alignment with product and business goals.At VMO, we have seen this trend firsthand through collaborations with healthcare providers, digital health platforms, health insurers, and MedTech companies across different markets. Our teams have contributed to projects ranging from patient engagement platforms and healthcare data solutions to AI-enabled applications and cloud-based healthcare systems.What many HealthTech organizations value most is not simply development capacity, but engineering teams that understand the importance of security, compliance, interoperability, and reliability in healthcare technology.As the industry continues to evolve, Vietnam is becoming an increasingly strategic location for organizations seeking to scale innovation while maintaining high engineering standards. &nbsp;

Why HealthTech Companies Are Expanding Engineering Teams in Vietnam

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By reading this article, you will gain valuable insights into the significant advantages of enlisting the expertise of a skilled SAP logistics consultant. It will provide a clear understanding of how such consultants can revolutionize logistics functions, leading to cost reduction, improved operational efficiency, and remarkable professional achievements.

SAP Logistics: Unlocking the Key Benefits, Strategies & Best Practices

This article explores the concepts of SAP logistics business processes and emphasizes the importance of logistics in supply chain optimization

sap-logistics-unlocking-the-key-benefits-strategies-best-practices

In the world of e-commerce, delivering exceptional customer experiences is key to standing out in a competitive market. Salesforce Commerce Cloud, a robust e-commerce platform, empowers businesses to create seamless, personalized, and high-performing online storefronts. To make the most of this powerful tool, it's essential to implement effective best practices that optimize your use of Salesforce Commerce Cloud. In this article, we'll explore essential strategies to elevate your e-commerce game and achieve outstanding results.<h3 style="margin-left:0px;">1. Strategic Planning and Alignment</h3>To succeed in the digital landscape, every business needs a solid e-commerce strategy aligned with its overall objectives. Begin by understanding your target audience, market segment, and competition. Develop a roadmap that outlines your growth goals, milestones, and strategies for achieving them. Salesforce Commerce Cloud offers the tools you need to bring your vision to life.Suppose you're a fashion retailer targeting young professionals. Your strategic plan might involve expanding your product offerings to include sustainable fashion lines that resonate with your eco-conscious audience. Salesforce Commerce Cloud enables you to curate personalized shopping experiences for this specific demographic, driving engagement and loyalty.<figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1692180613186-Salesforce%20Commerce%20Cloud%20Best%20Practices_1.jpg" alt="Salesforce Commerce Cloud Best Practices"></figure><h3 style="margin-left:0px;">2. Salesforce Commerce Cloud Best Practices: Responsive and Mobile-First Design</h3>With the increasing number of mobile shoppers, having a responsive and mobile-friendly design is non-negotiable. Salesforce Commerce Cloud enables you to create a storefront that looks and performs seamlessly across various devices and screen sizes. A mobile-first approach ensures that your customers enjoy a consistent and engaging experience, regardless of the device they're using.Imagine you're a tech accessories retailer. With Commerce Cloud, you can ensure that your website's design is responsive and mobile-friendly. This means that customers shopping for smartphone cases or wireless headphones can easily browse and make purchases on their mobile devices, without encountering any usability issues.<figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1692180633596-Salesforce%20Commerce%20Cloud%20Best%20Practices_2.jpg" alt="Salesforce Commerce Cloud Best Practices"></figure><h3 style="margin-left:0px;">3. Personalization and Recommendations</h3>Customers expect tailored experiences, and Commerce Cloud's personalization capabilities allow you to meet those expectations. Utilize customer data and behaviors to provide targeted product recommendations, personalized promotions, and relevant content. This level of personalization enhances engagement and increases conversion rates.Suppose you operate a beauty and skincare online store. By utilizing Commerce Cloud's personalization features, you can analyze a customer's past purchases and browsing history to suggest complementary products, such as moisturizers or serums, enhancing their shopping experience and boosting your average order value.<figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1692180766955-Salesforce%20Commerce%20Cloud%20Best%20Practices_3.png" alt="Salesforce Commerce Cloud Best Practices"></figure><h3 style="margin-left:0px;">4. Salesforce Commerce Cloud Best Practices: Streamlined Checkout Process</h3>A streamlined checkout process is essential for reducing cart abandonment rates. Salesforce Commerce Cloud enables you to simplify the checkout process by offering guest checkout options, clear steps, and convenient features like address auto-fill and saved payment information. Make purchasing a breeze for your customers.Example: As a gourmet food retailer, a simplified checkout process is essential. With Salesforce Commerce Cloud, you can offer a guest checkout option, allowing customers to purchase artisanal products without the need for creating an account. This frictionless experience reduces cart abandonment rates and boosts conversions.<figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1692180821612-Salesforce%20Commerce%20Cloud%20Best%20Practices_4.png"></figure><h3 style="margin-left:0px;">5. Optimized Performance and Speed</h3>Slow-loading websites are a major turn-off for customers. With Commerce Cloud, you can optimize your storefront's performance and loading speed. From image optimization to caching mechanisms and content delivery networks (CDNs), these optimizations ensure that your customers enjoy fast page load times and a frictionless shopping experience.Running a home decor e-commerce store? With Commerce Cloud, you can optimize your website's loading speed by compressing high-resolution images of furniture and decor items. This ensures that customers can swiftly explore your offerings, view product details, and make purchase decisions without delays.<h3 style="margin-left:0px;">6. Data-Driven Insights</h3>Data analytics is a powerful tool for understanding customer behavior and making informed decisions. Within Commerce Cloud, utilize reporting tools to gain insights into sales trends, conversion rates, and user interactions. These insights empower you to make data-driven improvements to your strategies.<figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1692180921988-Salesforce%20Commerce%20Cloud%20Best%20Practices_5.jpg"></figure><h3 style="margin-left:0px;">7. Salesforce Commerce Cloud Best Practices: SEO and Content Optimization</h3>A well-optimized website is more likely to rank higher in search engine results. Leverage Salesforce Commerce Cloud's capabilities to optimize product descriptions, meta tags, and URLs for search engines. Implementing SEO best practices enhances your website's visibility and drives organic traffic.Operating a book retailer's website? By using Commerce Cloud's SEO tools, you can optimize product descriptions and meta tags for popular book genres and authors. This boosts your website's visibility in search engine results, leading to more organic traffic from avid readers seeking their next literary adventure.<figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1692180967854-Salesforce%20Commerce%20Cloud%20Best%20Practices_6.png"></figure><h3 style="margin-left:0px;">8. Omnichannel Integration</h3>Integrating Commerce Cloud with various channels such as social media, marketplaces, and physical stores creates a unified shopping experience. Customers can seamlessly transition from one touchpoint to another, enjoying a consistent and engaging journey across all interactions.Imagine you have a sports apparel brand. By integrating Commerce Cloud with your physical store's inventory and social media platforms, you can offer customers the option to buy online and pick up in-store. Additionally, customers can seamlessly transition between browsing products on social media and making purchases on your website.<figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1692181026238-Salesforce%20Commerce%20Cloud%20Best%20Practices_7.png"></figure><h3 style="margin-left:0px;">9. Salesforce Commerce Cloud Best Practices: Regular Testing and Quality Assurance</h3>Thorough testing is crucial to ensuring your storefront's functionality, usability, and performance. Regular quality assurance checks help identify and resolve issues promptly, ensuring that your customers always enjoy a seamless experience.If you manage an electronics e-commerce store, frequent quality assurance checks ensure that all product specifications, images, and pricing information are accurate and up to date. This prevents customer dissatisfaction due to receiving different products than expected.<h3 style="margin-left:0px;">10. Salesforce Commerce Cloud Best Practices: Security and Compliance</h3>Protecting customer data and ensuring compliance with regulations is paramount. Salesforce Commerce Cloud provides secure payment gateways, SSL certificates, and features to help you maintain a secure shopping environment. Prioritize the security and privacy of your customers' sensitive information.<figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1692181073713-Salesforce%20Commerce%20Cloud%20Best%20Practices_8.png"></figure><h3 style="margin-left:0px;">11. Continuous Improvement</h3>E-commerce is a dynamic field, and continuous improvement is vital for success. Listen to customer feedback, monitor key performance indicators, and iterate on your strategies. Salesforce Commerce Cloud Best Practices offers the flexibility to adapt and optimize over time.Suppose you own a home appliance e-commerce website. Regularly reviewing customer feedback and monitoring analytics can lead to valuable insights. If you notice a trend of customers abandoning their carts during the checkout process, you can identify and address any potential usability issues.<h3 style="margin-left:0px;">12. Salesforce Commerce Cloud Best Practices: Training and Skill Development</h3>Invest in training for your team to ensure they are proficient in using Commerce Cloud's features and tools. Staying updated on new releases and capabilities empowers your team to leverage the platform's full potential.Example: As a toy retailer, investing in training for your team ensures they're well-versed in using Commerce Cloud's features. They can learn to set up seasonal promotions, update inventory listings, and manage customer inquiries effectively, leading to a seamless shopping experience.<h3 style="margin-left:0px;">13. Salesforce Commerce Cloud Best Practices: Scalability and Future-Proofing</h3>As your business grows, scalability becomes essential. Build a scalable architecture that can accommodate increased demand. Stay informed about updates and enhancements to Commerce Cloud to future-proof your e-commerce endeavors.Example: Operating a tech gadget e-commerce store? With Commerce Cloud, you can easily accommodate increased traffic during seasonal sales or product launches. This scalability ensures your website remains responsive and efficient even during peak shopping periods.<figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1692181119450-Salesforce%20Commerce%20Cloud%20Best%20Practices_9.png"></figure><h3 style="margin-left:0px;">Conclusion</h3>Salesforce Commerce Cloud is a powerful platform that empowers businesses to create exceptional e-commerce experiences. By implementing these best practices, you can optimize your use of Commerce Cloud, create engaging storefronts, and provide your customers with seamless, personalized, and high-performing online shopping experiences.Remember that the e-commerce landscape is ever-evolving, and staying ahead of the curve requires ongoing dedication to improvement and innovation. By incorporating these best practices, you'll be well-equipped to achieve outstanding results and drive your e-commerce success to new heights.

To make the most of this powerful tool, it's essential to implement effective best practices that optimize your use of Salesforce Commerce Cloud. In this article, we'll explore essential strategies to elevate your e-commerce game and achieve outstanding results.

Salesforce Commerce Cloud Best Practices: Boost The E-commerce Game

In this article, we'll explore essential strategies to elevate your e-commerce game and achieve outstanding results.

salesforce-commerce-cloud-best-practices-boost-the-e-commerce-game

Salesforce, the leading global CRM provider, has introduced Einstein GPT, a groundbreaking generative AI CRM technology. This innovation revolutionizes customer experiences by seamlessly integrating AI-generated content across sales, service, marketing, commerce, and IT interactions, all at an unprecedented scale. By combining Salesforce's proprietary AI models with generative AI technology from a network of partners and real-time data from the Salesforce Data Cloud, Einstein GPT empowers customers to leverage OpenAI's advanced AI models effortlessly.&nbsp;With natural-language prompts embedded within Salesforce CRM, users can generate dynamic content that adapts in real-time to changing customer information and preferences. From personalized emails for sales representatives to prompt responses for customer service professionals and targeted content for marketers, Einstein GPT enables users to enhance their interactions and boost productivity. It even automates code generation for developers, streamlining the development process. Salesforce continues to push the boundaries of AI-driven customer engagement with Einstein GPT, delivering unparalleled value to businesses across industries.“Einstein GPT…is another way we are opening the door to the AI future for all our customers, and we’ll be integrating with OpenAI at launch.”&nbsp;said Marc Benioff, CEO of Salesforce.<figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1685613471959-2.jpg"></figure>Salesforce is seamlessly integrating OpenAI's ChatGPT technology with its own private AI models, resulting in the delivery of highly relevant and reliable AI-generated content. By combining forces, Salesforce aims to extend the reach of this powerful technology to a broader audience, enabling more individuals and businesses to benefit from its capabilities.&nbsp;Sam Altman, the CEO of OpenAI, expressed excitement about this collaboration, highlighting how it facilitates learning about real-world usage, a crucial factor in the responsible development and deployment of AI. Salesforce and OpenAI share a common belief in the responsible and ethical advancement of AI, making this integration a significant step forward in harnessing the power of AI within the CRM domain.<h3>What can do with Einstein GPT in CRM?</h3>Einstein GPT represents the evolutionary leap of Salesforce's existing AI technology, Einstein, which already empowers over 200 billion AI predictions daily within the Customer 360 ecosystem. With Einstein GPT, customers can now leverage the fusion of Salesforce's proprietary Einstein AI models with ChatGPT and other top-tier large language models. This integration enables users to employ natural-language prompts on their CRM data, unlocking a host of powerful and efficient automation while generating personalized, AI-generated content.<h4>Einstein GPT for Service:&nbsp;</h4><figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1685613683233-4.jpg"></figure>Automated Customer Service, powered by Salesforce Service Cloud, revolutionizes the customer service experience by leveraging artificial intelligence and automation. With features such as Einstein Bots and Service Cloud Voice, businesses can provide efficient and personalized support at scale. This solution enables companies to automate routine tasks, freeing up agents' time to focus on more complex customer inquiries.&nbsp;By harnessing AI-powered chatbots, businesses can deliver instant responses and resolutions, reducing wait times and increasing customer satisfaction. Additionally, Service Cloud Voice integrates voice channels into the customer service workflow, facilitating seamless interactions and enabling agents to provide real-time assistance. With Automated Customer Service, businesses can streamline their support processes, improve agent productivity, and deliver exceptional customer experiences.<h4>Einstein GPT for Sales:</h4><figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1685613785171-3.jpg"></figure>AI for Sales, offered by Salesforce, transforms the sales process by leveraging artificial intelligence to drive efficiency and effectiveness. With AI-powered tools such as Einstein Forecasting and Einstein Opportunity Scoring, sales teams can gain accurate insights into revenue projections and prioritize high-potential opportunities. The integration of AI into the sales workflow enables sales representatives to personalize interactions, deliver timely recommendations, and automate administrative tasks. By harnessing the power of AI, sales teams can improve forecasting accuracy, increase win rates, and enhance overall sales performance.<h4>Einstein GPT for Marketing:</h4><figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1685613836696-5.jpg"></figure>Salesforce's Marketing Cloud offers a comprehensive solution for driving customer engagement and delivering personalized experiences. With AI-powered tools like Einstein Engagement Scoring and Einstein Journey Insights, marketers can gain valuable insights into customer behavior and preferences. By leveraging data-driven intelligence, marketers can create targeted campaigns, optimize customer journeys, and deliver personalized content across multiple channels.&nbsp;The integration of AI technology enables marketers to automate tasks, improve segmentation, and enhance campaign performance. With Marketing Cloud's engagement capabilities, businesses can connect with their customers in a more meaningful and impactful way, driving customer loyalty and maximizing marketing ROI.<h4>Einstein GPT for Slack Customer 360 apps:</h4><figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1685613946881-6.jpg"></figure>Provide AI-driven customer insights within Slack, including intelligent summaries of sales opportunities and highlighting user actions such as knowledge article updates.<h4>Einstein GPT for Developers:</h4><figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1685614331169-7.jpg"></figure>A powerful tool that combines Salesforce's AI models with OpenAI's ChatGPT technology. By integrating natural language prompts, developers can generate code, automate tasks, and enhance productivity. The integration of Einstein GPT enables developers to create personalized, AI-generated content and streamline their development process. This technology empowers developers to leverage the capabilities of large language models and harness the power of AI within the Salesforce platform. With Einstein GPT, developers can revolutionize their workflows and deliver innovative solutions that drive business success.<h4>ChatGPT for Slack, built by OpenAI:</h4>A collaborative effort between Salesforce and OpenAI. This innovative app brings a range of AI-powered capabilities to Slack, including advanced conversation summaries, comprehensive research tools for acquiring knowledge on any subject, and efficient writing assistance for swiftly composing messages. Stay connected, informed, and productive with the ChatGPT for Slack.<h4>The customer perspective:&nbsp;</h4>From the viewpoint of customers such as HPE, L'Oréal, RBC US Wealth Management, and S&amp;P Global Ratings, the significance of generative AI in enhancing customer engagement is evident. These organizations attest to the value that generative AI brings to their interactions with customers, resulting in improved engagement and enriched experiences.<h3>Successful Cases.</h3><h4>Ford.</h4><figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1685615256488-8.jpg"></figure>Ford's customer experience transformation is highlighted, showcasing impressive results achieved through Salesforce's CRM solutions and Einstein GPT application. Ford successfully increased its customer satisfaction rating by 37% and improved its response time by 50% by implementing Salesforce Service Cloud. With Salesforce Marketing Cloud, Ford achieved a 60% increase in email open rates and a 40% improvement in click-through rates, enabling targeted and effective marketing campaigns. By leveraging Salesforce Commerce Cloud, Ford achieved a significant 71% increase in online vehicle configuration completions, enhancing the digital car-buying experience for customers. These remarkable numbers demonstrate the tangible impact of Ford's collaboration with Salesforce and Einstein GPT in reinventing its customer experience.<h4>L'Oréal.</h4><figure class="image"><img src="https://vmo-website-prod.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1685615265058-9.jpg"></figure>L'Oréal's innovative use of data to create unique beauty experiences with the help of Salesforce's CRM solutions and Einstein GPT. By leveraging Salesforce Marketing Cloud, L'Oréal achieved an impressive 49% increase in email open rates and a remarkable 45% improvement in click-through rates, enabling personalized and engaging marketing campaigns. Through the implementation of Salesforce Service Cloud, L'Oréal successfully reduced customer response time by 60% and improved its customer satisfaction rating by 40%. These outstanding numbers demonstrate the significant impact of L'Oréal's collaboration with Salesforce in delivering exceptional beauty experiences to their customers.<h3> In conclusion.</h3>Salesforce Einstein GPT is the transformative power in revolutionizing the way businesses interact with their customers. By combining Salesforce's AI models with OpenAI's cutting-edge technology, organizations can harness the full potential of generative AI to deliver personalized, relevant, and trusted content across various touchpoints. This groundbreaking collaboration empowers sales teams with automated content generation, customer service professionals with quicker response capabilities, marketers with targeted campaigns, and developers with code generation. With Salesforce Einstein GPT, organizations can leverage the power of AI to drive innovation, streamline operations, and forge deeper connections with their customers. &nbsp;

The article highlights the transformative power of Salesforce Einstein GPT in revolutionizing the way businesses interact with their customers. With Salesforce Einstein GPT, organizations can leverage the power of AI to drive innovation, streamline operations, and forge deeper connections with their customers.

Salesforce Einstein GPT - The Door to The AI Future Of CRM

The article highlights the transformative power of Salesforce Einstein GPT in revolutionizing the way businesses interact with their customers.

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About the RoleWe are looking for a Senior DevOps Engineer with strong expertise in AWS, Kubernetes, and CI/CD to build and operate scalable cloud-native platforms. You will work closely with development teams to automate infrastructure, optimize deployment processes, and ensure system reliability, security, and performance.Responsibilities<ul><li>Design and manage scalable, secure, and highly available AWS infrastructure.</li><li>Build and maintain Kubernetes environments (EKS or self-managed).</li><li>Develop and optimize CI/CD pipelines for automated deployments.</li><li>Implement Infrastructure as Code using Terraform or CloudFormation.</li><li>Collaborate with engineering teams on cloud-native and microservices architectures.</li><li>Monitor system performance and ensure reliability through logging, metrics, and alerting.</li><li>Apply security best practices across infrastructure and deployment pipelines.</li><li>Participate in Agile development processes and technical discussions.</li><li>Create and maintain technical documentation.</li></ul>

DevOps Engineer (Tokyo, Japan)

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<ul><li style="text-align:justify;">Develop and maintain backend systems and APIs using Python Django.</li><li style="text-align:justify;">Build and support frontend applications using Angular.</li><li style="text-align:justify;">Design, develop, and optimize scalable, secure, and high-performance applications.</li><li style="text-align:justify;">Work with PostgreSQL for database design, integration, and optimization.</li><li style="text-align:justify;">Implement authentication and authorization solutions using OAuth2 and OIDC.</li><li style="text-align:justify;">Write clean, maintainable code and ensure software quality through testing and code reviews.</li><li style="text-align:justify;">Participate in system design discussions and contribute to technical solutions.</li><li style="text-align:justify;">Collaborate with cross-functional teams in an Agile environment.</li><li style="text-align:justify;">Support troubleshooting, performance improvements, and mentoring team members when needed.</li></ul>

Fullstack Developer (Python Django, Angular - English Fluent)

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Summary:&nbsp; The Data Scientist role focuses on building propensity models and sizing market opportunities for VMO project with banking clients. This hybrid position requires a blend of data science and engineering skills to create production-grade pipelines. The role is pivotal in driving sales strategy through data-driven outputs. Candidates should have a strong background in Python and SQL, along with proven experience in propensity modeling.<ol><li>Propensity Modeling &amp; Ranking: &nbsp; &nbsp; Predict CTR and engagement probability &nbsp; &nbsp; Use models like XGBoost / LightGBM &nbsp; &nbsp; Optimize ranking using NDCG, MRR, Precision@K</li><li>Feature Engineering: &nbsp; &nbsp; Build features from user behavior, interaction signals, and context &nbsp; &nbsp; Handle sparse and noisy data</li><li>Cold Start Handling: &nbsp; &nbsp; Design strategies for new users and new offers &nbsp; &nbsp; Implement hybrid and fallback approaches</li><li>Bias Handling: &nbsp; &nbsp; Mitigate popularity and exposure bias &nbsp; &nbsp; Implement diversity and re-ranking strategies</li><li>Model Evaluation: &nbsp; &nbsp; Define and track CTR, conversion, NDCG, AUC &nbsp; &nbsp; Continuously improve engagement metrics</li><li>Scalability &amp; Deployment: &nbsp; &nbsp; Build systems for millions of users &nbsp; &nbsp; Enable real-time or near real-time inference</li></ol>

AI Engineer ( Strong Python) - ENG GOOD

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Job Summary We are looking for 2 Senior Full-Stack Developers to join a cloud-native product team building enterprise-grade applications on Microsoft Azure. The role involves designing and implementing frontend interfaces, backend APIs, and microservices that integrate deeply with Azure cloud services. You will work across the full delivery lifecycle, from architecture decisions to CI/CD pipeline setup and production deployment.Key Responsibilities • &nbsp; &nbsp;Design and build responsive frontend applications using React or Angular, TypeScript, and chart libraries • &nbsp; &nbsp;Develop and maintain backend APIs and microservices using C# and .NET, following RESTful design principles • &nbsp; &nbsp;Implement background services, messaging queue patterns, and the Saga Pattern for distributed transaction management • &nbsp; &nbsp;Integrate applications with Azure services including Azure Front Door, API Management, Application Gateway, Azure Service Bus, Azure Redis, Azure Key Vault, and managed databases • &nbsp; &nbsp;Write and maintain CI/CD pipelines on Azure Pipelines, including build, test, scan, and deploy stages following DevSecOps practices • &nbsp; &nbsp;Apply security practices including SAST, dependency scanning, image scanning, secret management, and pipeline security gates • &nbsp; &nbsp;Containerize services using Docker with multi-stage builds; deploy and troubleshoot workloads on Azure Kubernetes Service (AKS) • &nbsp; &nbsp;Participate in Agile/Scrum ceremonies; understand and apply the 12 Cloud Native Factors in application design • &nbsp; &nbsp;Follow governance and security policies for Azure Resource Groups, service configurations, and user access control

Fullstack (.Net+ReactJS/Angular) DU33 - ENG GOOD

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POSITION OVERVIEWAs a Senior Engineer, you will lead the design and development of high-performance, multi-core system software for LTE/5G baseband systems. You will play a key role in architecture decisions, performance optimization, and technical mentorship.

Baseband (PHY / UPC) Software Design Engineer (Senior/Experienced) - Telecom Industry

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<ul><li>GenAI developers to design, prototype, and deploy AI-driven solutions that optimize internal business processes.&nbsp;</li><li>The team will collaborate on a shared project under the guidance of a closely involved Technical Leader and work closely with the Product Owner on daily execution and prioritization.</li><li>Sample project scopes includes: - HR Agent – Build an AI assistant to respond to HR-related inquiries and support internal staff.&nbsp; - Power Automate Integration – Develop automated reporting workflows and streamline operational processes.&nbsp; - Legal Agent – Create an AI system capable of reviewing customer contracts and performing structured analysis for the legal team. &nbsp;</li></ul>

AI Engineer (ENG) - AIS

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<ul style="list-style-type:disc;"><li>Designing and maintaining scalable integration pipelines using Azure Logic Apps, Azure Storage, API Management, Microsoft Fabric, and related Azure technologies</li><li>Implementing API-based, event-driven, and scheduled integration workflows</li><li>Ensuring integration solutions are secure, scalable, highly available, and compliant with standards such as GDPR</li><li>Collaborating with technical teams and business stakeholders to support data accessibility and integrity</li><li>Monitoring, troubleshooting, and continuously improving integration reliability and performance</li><li>Supporting CI/CD and infrastructure deployment using Azure DevOps and IaC tools such as ARM, Bicep, or Terraform Providing technical leadership and mentoring junior engineers</li><li>Documenting workflows and processes for both technical and business audiences &nbsp;</li></ul>

Data Engineer (ENG) - AIS

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<ul><li>Xây dựng, cải tiến và ban hành quy trình làm việc trong các phòng ban thuộc mảng Vận hành, Kinh doanh và 1 phần của mảng Sản xuất (đã có QA &amp; PMO phụ trách chính).</li><li>Phối hợp với các bên liên quan để tạo mới, cập nhật và duy trì toàn bộ tài liệu liên quan đến hệ thống QMS &amp; ISMS của Công ty.</li><li>Chịu trách nhiệm quản lý, duy trì và kiểm soát hệ thống tài liệu ISO của Công ty.</li><li>Chịu trách nhiệm chứng nhận, duy trì và cải tiến liên tục hệ thống quản lý chất lượng (ISO 9001) và an toàn thông tin (ISO 27001) của Công ty.</li><li>Tổ chức và hỗ trợ các phòng ban thực hiện các cuộc đánh giá nội bộ và bên ngoài cho QMS và ISMS</li><li>Hướng dẫn, giám sát các phòng ban khắc phục điểm không phù hợp sau các cuộc đánh giá.</li><li>Hỗ trợ khối Sản xuất, Kinh doanh review và trả lời các hạng mục/ survey liên quan tới chứng chỉ, tiêu chuẩn, quy trình/quy định của Công ty.</li><li>Thực hiện chương trình đánh giá rủi ro và quản trị rủi ro hàng năm</li></ul>

ISO Executive

iso-executive

We are seeking a highly skilled Fullstack Developer with experience in both Backend and Frontend development, utilizing TypeScript, SQL, and NoSQL databases (e.g., MongoDB, DynamoDB). Candidates with a solid understanding of DevOps and Cloud platforms, along with proficiency in Datadog for observability and monitoring, are highly preferred.

Fullstack Engineer (ENG) -DU35

fullstack-engineer-eng-du35

1. Product Strategy &amp; Vision Define and evolve the omnichannel product vision for Health &amp; Beauty, aligning with business KPIs Lead cross-functional alignment with Marketing, Supply Chain, Retail Stores, Business Analyst, and E-Com teams. Conduct competitive benchmarking and identify white-space opportunities. 2. E-Commerce Platform Leadership Own digital roadmap for the e-commerce website and mobile app. Drive conversion optimization through: Unified customer loyalty Personalized product discovery Simplified stacked promotion Frictionless checkout) Manage integrations with ERP, OMS, Fulfillment, and payment gateways. 3. Omnichannel Experience Design Design seamless cross-channel journeys.&nbsp; Partner with store operations to deploy digital in-store experience. Enable unified customer profiles across touchpoints.\ 4. Data-Driven Optimization Partner with Analytics and Data Science to run A/B tests and personalization experiments Define and track North Star metrics: Customer Lifetime Value, Omnichannel Engagement Rate, Digital Revenue

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