Metal 3D printing is transforming the way high-precision components are manufactured. Yet ensuring quality throughout a layer-by-layer production process remains one of the industry's most complex technical challenges. Detecting defects early is critical, not only for maintaining product quality, but also for reducing material waste, production time, and operational costs.

AI benchTALKs #04 | AI for Advanced Metal 3D Printing

AI benchTALKs #04 | AI for Advanced Metal 3D Printing: How AI Is Reshaping Precision Manufacturing

ai-benchtalks-04-ai-for-advanced-metal-3d-printing

<h2>Will Your Next Doctor Be an Avatar? Exploring the Future of AI-Powered Patient Engagement</h2>Imagine opening your healthcare app late at night with a question about your medication. Instead of waiting for office hours, a lifelike virtual healthcare assistant appears, listens to your concern, and responds in natural conversation—while understanding your medical history and knowing when to escalate you to a clinician.This future is closer than many people think.Advances in generative AI, natural language processing (NLP), and digital human technology are making AI avatars a valuable extension of modern healthcare. While they won't replace doctors, they are changing how providers connect with patients, making healthcare more accessible, responsive, and personalized.<h2>Why Patient Engagement Is Evolving</h2>Patients increasingly expect the same convenience from healthcare that they experience in banking, retail, and other digital services. At the same time, providers face growing challenges, including clinician shortages, rising patient volumes, and increasing administrative workloads.AI-powered avatars help bridge this gap by providing instant support, reducing routine administrative tasks, and keeping patients engaged throughout their care journey.<h2>How AI Avatars Are Being Used Today</h2>Healthcare organizations are already exploring AI avatars across multiple touchpoints.Virtual assistants can answer common questions about medications, appointments, hospital services, and post-discharge care, giving patients immediate guidance while reducing pressure on support teams.Before appointments, avatars can collect symptoms and medical history updates, allowing clinicians to focus more on diagnosis and treatment rather than paperwork. After treatment, they can check in with patients, remind them to take medication, monitor recovery, and flag concerns that require medical attention.For patients living with chronic conditions such as diabetes or hypertension, AI avatars also provide ongoing coaching, health education, and personalized reminders that encourage better long-term adherence.<h2>Why Digital Humans Feel Different from Chatbots</h2>Unlike traditional chatbots that rely on text, AI avatars combine conversational AI with realistic voice and facial expressions to create a more natural interaction.Patients can simply speak instead of type, making healthcare more accessible for older adults and those with limited digital literacy. This human-like experience also helps build trust and encourages patients to ask questions they might otherwise hesitate to raise.Behind these interactions are technologies such as Large Language Models (LLMs), speech AI, computer vision, and secure integration with Electronic Health Records (EHRs), enabling conversations that are both intelligent and context-aware.<h2>Challenges That Can't Be Ignored</h2>As promising as AI avatars are, they must be implemented responsibly. Healthcare organizations need to ensure patient data remains secure, comply with regulations such as HIPAA and GDPR, and make it clear when patients are interacting with AI rather than a human clinician.Equally important, AI should support not replace medical professionals. The best solutions are designed to handle routine interactions while seamlessly escalating complex or urgent cases to healthcare providers.<h2>The Future Is Collaborative</h2>The next generation of healthcare won't replace doctors with avatars. Instead, AI will become the digital front door to care, helping patients schedule appointments, answer routine questions, complete pre-visit assessments, and receive personalized follow-up support.By automating repetitive interactions, clinicians can spend more time on what matters most: delivering expert, compassionate care.At&nbsp;VMO, we help healthcare organizations build secure, AI-powered digital health solutions from intelligent virtual assistants and patient engagement platforms to healthcare data engineering and system integration. By combining AI expertise with healthcare domain knowledge, we enable providers to create smarter, more connected patient experiences while keeping clinicians at the heart of care.As AI continues to evolve, the question may no longer be&nbsp;whether you'll interact with a healthcare avatar but how it can make your healthcare journey faster, easier, and more personalized.

Exploring the Future of AI-Powered Patient Engagement

exploring-the-future-of-ai-powered-patient-engagement

<h2>Model Context Protocol (MCP): The Foundation Powering the Next Generation of AI Agents</h2><h2>1. Why is everyone talking about MCP?</h2><ul><li>AI has evolved from chatbots to AI Agents capable of reasoning, planning, and executing complex tasks.</li><li>As organizations adopt AI Agents in real-world environments,&nbsp;connectivity has become a major challenge.</li><li>AI Agents need secure access to enterprise data, business applications, and external tools, but custom integrations are difficult to scale.</li><li>Introduced by Anthropic in 2024 and now governed by the Linux Foundation,&nbsp;Model Context Protocol (MCP) provides a common protocol for communication between AI models and external tools, applications, and data sources.</li><li>Rather than being another AI model, MCP serves as the infrastructure that enables AI to operate effectively in real-world environments.</li></ul><h2>2. Why does MCP matter?</h2>MCP is often described as&nbsp;"USB-C for AI" because it standardizes how AI systems connect to external resources.This does&nbsp;not mean direct connections to databases, APIs, or other tools are no longer possible—they remain a valid approach and continue to work well in many scenarios.What MCP addresses is the duplication of integration effort. Without a shared protocol, development teams often rebuild similar integration logic for every AI platform or tool that needs access to the same enterprise systems. As the number of AI platforms grows, these integrations become increasingly difficult to maintain.With MCP, developers can build a connector once and reuse it across multiple AI platforms that support the protocol instead of reimplementing the same integration repeatedly.More importantly, MCP expands what AI can actually do in enterprise environments.Instead of relying solely on knowledge learned during training, AI can:<ul><li>Access and format real-time enterprise data for LLMs.</li><li>Connect securely to company resources with governed access and permissions.</li><li>Take actions across multiple systems through standardized tool integrations.</li><li>Automate end-to-end business workflows rather than completing isolated tasks.</li></ul>In other words, MCP enables the transition from conversational AI to action-oriented AI Agents.<h2>3. Why do enterprises choose MCP over direct integrations?</h2>If direct integrations already work, why do many organizations introduce an intermediate layer such as MCP?Several architectural considerations make this approach attractive for enterprise environments:<ul><li>Security &amp; access control – Rather than exposing database credentials directly to AI models, MCP enables organizations to limit permissions, control access, and keep credentials hidden.</li><li>Abstraction &amp; maintainability – Database schemas and APIs evolve over time. MCP abstracts implementation details so backend changes only require updating the connector rather than every AI application.</li><li>Data safety &amp; correctness – Instead of allowing AI to generate arbitrary queries, MCP exposes predefined tools and validates operations, reducing the risk of invalid queries, unintended data modification, or security vulnerabilities.</li><li>Observability &amp; compliance – A standardized protocol makes it easier to log, monitor, and audit how AI Agents access enterprise resources, supporting governance and regulatory requirements.</li><li>Reusability – Connectors built with MCP can be reused across multiple AI models and applications instead of being tightly coupled to a single implementation.</li></ul>Ultimately, MCP does not replace direct integrations. It provides a standardized, secure, and reusable way for AI systems to interact with enterprise resources at scale.<h2>💬 Expert Insight</h2>"With the rise of AI coding agents as the first wave of AI-accelerated programming, the next wave will accelerate the entire software development lifecycle—from writing documentation to testing and deployment. MCP removes much of the integration friction that has traditionally limited wider enterprise adoption."— Tech Lead AI, VMO<h2>4. How is the MCP ecosystem evolving?</h2>Since its introduction, MCP has gained rapid adoption across the AI ecosystem.Leading AI assistants—including Claude, ChatGPT, and Gemini—are building support for MCP alongside developer tools such as Claude Code, Cursor, VS Code, Windsurf, and Codex CLI.Enterprise platforms including IBM BeeAI, Microsoft Copilot Studio, and Postman are also integrating MCP into their AI offerings.The protocol itself continues to evolve in three key directions:<ul><li>Scalability: Supporting stateless architectures and distributed deployments.</li><li>Agent-to-Agent Collaboration: Enabling AI Agents to delegate tasks, retrieve results asynchronously, and recover from failures.</li><li>Enterprise Readiness: Strengthening security, observability, authentication (SSO), and configuration management for production environments.</li></ul>Together, these developments are positioning MCP as a foundational layer for enterprise AI infrastructure.<h2>5. What does MCP enable in practice?</h2>The value of MCP becomes clear through real-world applications.<ul><li>Scientific Research: PapersFlow enables AI to search hundreds of millions of research papers while verifying citations directly from developer workflows.</li><li>Software Engineering: Claude Code can generate applications from Figma designs by interacting with external development tools through MCP.</li><li>Enterprise Productivity: AI Agents can connect with Google Calendar, Slack, GitHub, and Notion to automate scheduling, summarize project updates, and execute business workflows.</li><li>Enterprise Transformation: Riyadh Air has partnered with IBM to develop AI-native operational capabilities powered by autonomous AI Agents.</li></ul>These examples illustrate a broader trend: AI is moving beyond conversation toward execution.6. What opportunities does MCP create for Vietnamese IT companies?For technology companies, MCP represents more than a new protocol—it represents a new layer of the AI technology stack.Because MCP is an open standard, Vietnamese software companies can develop MCP Servers, AI tools, and enterprise integrations that work across multiple AI platforms instead of being tied to a single ecosystem.Beyond software outsourcing, this creates opportunities to deliver AI Agent solutions, enterprise AI integration services, and production-ready AI infrastructure.Internally, engineering teams can also improve development productivity by leveraging MCP-enabled tools such as Claude Code and Cursor, reducing integration effort and focusing on core business logic.Finally, as MCP continues to evolve under the Linux Foundation, developers also have the opportunity to contribute directly to an emerging global open standard.<h2>Conclusion</h2>Model Context Protocol is not simply another AI technology.It is an open standard that enables AI systems to securely interact with external tools, enterprise applications, and real-world data through a common interface.As AI adoption shifts from conversational assistants toward autonomous AI Agents, interoperability is becoming just as important as model intelligence.In that context, MCP is emerging as one of the foundational technologies enabling the next generation of enterprise AI

Model Context Protocol (MCP): The Foundation Powering the Next Generation of AI Agents

The Foundation Powering the Next Generation of AI Agents

the-foundation-powering-the-next-generation-of-ai-agents

<h2>What if healthcare could prevent a heart attack before the first symptom ever appears?</h2>For decades, cardiovascular care has largely been reactive. Patients visit a doctor after experiencing chest pain or shortness of breath, or when routine screenings reveal elevated risk factors. While preventive medicine has made significant progress, predicting who will experience a heart attack years in advance has remained an enormous challenge.By analyzing millions of health records, medical images, genetic markers, wearable device data, and lifestyle patterns, AI is helping healthcare providers identify subtle warning signs that humans simply cannot detect. Rather than waiting for disease to manifest, healthcare is moving toward a future where risks are anticipated, and interventions happen years earlier.This shift represents more than technological advancement. It marks the emergence of&nbsp;Preventive Intelligence: using AI to continuously assess health risks, personalize prevention strategies, and improve patient outcomes before critical events occur.<h2>Why Traditional Risk Assessment Isn't Enough</h2>Most cardiovascular risk assessments rely on established clinical indicators, including:<ul><li>Blood pressure</li><li>Cholesterol levels</li><li>Smoking history</li><li>Diabetes</li><li>Age and family history</li><li>Body Mass Index (BMI)</li></ul>While these factors remain valuable, they provide only part of the picture.Two individuals with nearly identical clinical profiles may experience vastly different outcomes. One may remain healthy for decades, while another suffers a cardiac event within a few years.The missing insight often lies within highly complex relationships across thousands of variables, relationships that AI models are particularly effective at identifying.<h2>How AI Predicts Cardiovascular Risk Earlier</h2>Modern AI systems combine multiple sources of health information to build far more comprehensive risk profiles than traditional scoring models.<h3>Medical Imaging</h3>AI can detect microscopic changes in CT scans, retinal images, echocardiograms, and cardiac MRI scans that may indicate early vascular disease long before symptoms develop.Researchers have demonstrated that AI algorithms can uncover hidden biomarkers that are often invisible during routine clinical interpretation.<h3>Electronic Health Records</h3>Years of clinical history provide valuable predictive signals.AI analyzes:<ul><li>Medication history</li><li>Previous diagnoses</li><li>Laboratory trends</li><li>Hospital admissions</li><li>Physician notes</li><li>Family history</li></ul><h3>Wearable Devices</h3>Smartwatches and fitness trackers continuously monitor:<ul><li>Heart rate variability</li><li>Resting heart rate</li><li>Physical activity</li><li>Sleep quality</li><li>Blood oxygen levels</li><li>Cardiac rhythm abnormalities</li></ul>Continuous monitoring allows AI to identify gradual physiological changes that may otherwise go unnoticed.<h3>Genetics and Biomarkers</h3>When combined with genomic information and advanced laboratory biomarkers, AI can estimate inherited cardiovascular risk with increasing accuracy.Rather than relying on a single genetic mutation, machine learning evaluates thousands of genetic variants alongside environmental and behavioral factors.<h2>From Reactive Care to Preventive Intelligence</h2>The real value of AI lies not in predicting disease but in enabling earlier intervention.Imagine a patient whose AI-generated risk profile indicates a high likelihood of a cardiac event within the next decade.Instead of waiting until symptoms appear, clinicians could recommend:<ul><li>Lifestyle coaching</li><li>Nutrition programs</li><li>Exercise interventions</li><li>Earlier cholesterol management</li><li>Blood pressure optimization</li><li>More frequent monitoring</li><li>Personalized follow-up schedules</li></ul><h2>Digital Twins: Simulating Future Health</h2>One of the most exciting developments is the rise of&nbsp;digital twins in healthcare.A digital twin is a virtual representation of a patient's physiological condition that evolves using real-world health data.By combining:<ul><li>Medical history</li><li>Imaging</li><li>Wearable data</li><li>Laboratory results</li><li>Lifestyle information</li></ul>AI can simulate how cardiovascular health may change under different scenarios.Clinicians may eventually compare the impact of medication, dietary changes, exercise, or smoking cessation before treatment even begins, allowing for more personalized preventive strategies.<h2>The Challenges That Must Be Solved</h2>Despite impressive progress, AI-powered prevention still faces important hurdles.<h3>Data Quality</h3>Predictive models are only as reliable as the data they learn from. Missing, inconsistent, or biased datasets can reduce accuracy and fairness across different populations.<h3>Explainability</h3>Healthcare professionals need to understand&nbsp;why an AI system identifies a patient as high risk. Transparent, explainable AI is essential for building clinical trust and supporting informed decision-making.<h3>Privacy and Security</h3>Predictive healthcare depends on highly sensitive patient information. Strong governance, encryption, regulatory compliance, and responsible data stewardship remain critical to protecting patient privacy.<h3>Clinical Validation</h3>AI should enhance, not replace clinical expertise. Predictive models must undergo rigorous validation across diverse populations before becoming part of routine care.<h2>What This Means for Healthcare Organizations</h2>As preventive intelligence matures, healthcare providers and life sciences organizations have an opportunity to redesign care around proactive intervention rather than reactive treatment.Key areas of investment include:<ul><li>AI-powered clinical decision support</li><li>Secure healthcare data platforms</li><li>Interoperable electronic health records</li><li>Remote patient monitoring solutions</li><li>Predictive analytics infrastructure</li><li>Explainable AI governance frameworks</li></ul>Organizations that establish these capabilities today will be better positioned to deliver more personalized, efficient, and value-based care in the years ahead.<h2>Looking Ahead</h2>AI is unlikely to predict every heart attack with perfect accuracy—and it shouldn't be viewed as a replacement for clinical judgment. However, its ability to uncover hidden patterns across vast amounts of health data is transforming how cardiovascular risk is understood and managed.The future of healthcare will be defined not only by better treatments, but by the ability to identify risk earlier, intervene sooner, and support healthier lives before disease progresses.The question is no longer whether AI will play a role in preventive medicine.It's how quickly healthcare organizations can integrate predictive intelligence into everyday clinical practice.As AI, wearable technology, and precision medicine continue to converge, prevention may become one of healthcare's most powerful innovations—helping shift the focus from treating illness to preserving long-term health.

Can AI Predict a Heart Attack 10 Years Before It Happens? The Rise of Preventive Intelligence

Can AI Predict a Heart Attack 10 Years Before It Happens?

can-ai-predict-a-heart-attack-10-years-before-it-happens

On July 8, 2026, VMO joined its strategic partner, Yokogawa Electric Corporation, in the Scholarship Award Ceremony held at the Posts and Telecommunications Institute of Technology (PTIT), honoring outstanding students from the Applied Information Technology Program.The ceremony recognized students who have demonstrated exceptional academic performance, technical capabilities, and remarkable achievements in technology competitions. More than a celebration of excellence, the event reaffirmed a shared commitment to empowering Vietnam's next generation of technology professionals and encouraging them to pursue innovation with a global mindset.Representatives from Yokogawa, VMO, and PTIT gathered to congratulate the scholarship recipients and celebrate their accomplishments. The event also provided an opportunity for students to connect with industry leaders and gain insights into the skills, mindset, and opportunities needed to thrive in the rapidly evolving global technology landscape.Strengthening the Connection Between Industry and EducationThe scholarship program reflects the shared vision of Yokogawa, VMO, and PTIT in fostering closer collaboration between academia and industry. By recognizing talented students and supporting their professional growth, the initiative contributes to developing a highly skilled workforce ready to meet the demands of the digital era.At VMO, we believe that nurturing young talent is essential to building a sustainable technology ecosystem. Collaborating with leading global partners and educational institutions enables us to create meaningful opportunities for students while helping bridge the gap between academic learning and real-world industry experience.A Partnership Built on a Shared VisionThe Scholarship Award Ceremony reflects the continued commitment of VMO and Yokogawa Electric Corporation to fostering innovation and developing future technology talent. As strategic partners, both organizations remain dedicated to expanding collaboration across education, talent development, and technology initiatives, creating lasting value for students, the industry, and the broader Vietnam-Japan innovation ecosystem.

VMO and Yokogawa Electric Corporation Celebrate Outstanding PTIT Students at Scholarship Award Ceremony

VMO & Yokogawa Electric Corporation Award PTIT Scholarships

vmo-yokogawa-electric-corporation-award-ptit-scholarships

A subtle increase in respiratory rate. A slight drop in oxygen saturation. A change in heart rate variability so small it escapes the human eye.Individually, these signals may seem insignificant. Together, they can tell a very different story.Today, artificial intelligence is transforming patient monitoring from a system that reacts to emergencies into one that predicts them. By continuously analyzing millions of physiological data points in real time, AI is helping clinicians intervene earlier, improve outcomes, and redefine what proactive healthcare looks like.The future of patient monitoring isn't about watching patients more closely, it's about&nbsp;understanding them sooner.<h2>Why Traditional Monitoring Is No Longer Enough</h2>Healthcare has always relied on monitoring patients, but the approach has changed little over decades.Vital signs are checked every few hours. Nurses respond when alarms sound. Physicians interpret trends during rounds. Care teams intervene once deterioration becomes clinically apparent.The challenge isn't the dedication of clinicians; it's the sheer volume of data.An ICU patient can generate&nbsp;over a million physiological data points every day. Across an entire hospital, no human team can realistically process every heartbeat, breathing pattern, laboratory result, medication change, and clinical note in real time.As a result, warning signs are often recognized only after a patient's condition has already worsened.<h2>AI Is Already Saving Lives</h2><h2>Predicting Sepsis Before It Happens</h2>Sepsis remains one of healthcare's deadliest conditions because every hour of delayed treatment significantly increases mortality.AI models can identify subtle combinations of changing vital signs and laboratory values long before traditional warning systems activate.Hospitals using predictive sepsis monitoring are enabling clinicians to begin treatment earlier, often before patients show obvious symptoms.<h2>Watching Patients Beyond Hospital Walls</h2>Healthcare no longer ends when patients leave the hospital.Remote Patient Monitoring (RPM) has become one of the fastest-growing applications of AI.Patients recovering at home now wear devices that continuously measure:<ul><li>Heart rate</li><li>Blood pressure</li><li>Oxygen saturation</li><li>Activity</li><li>Sleep quality</li><li>Body temperature</li><li>Blood glucose</li></ul>AI transforms these continuous streams into actionable insights.A heart failure patient whose weight increases by just one kilogram, whose daily activity declines slightly, and whose resting heart rate rises by only a few beats per minute may appear perfectly stable.AI recognizes those tiny changes as an early warning for fluid retention and alerts clinicians before hospitalization becomes necessary.<h2>Real-World Success Stories</h2><h2>BioIntelliSense: Continuous Monitoring That Predicts Deterioration</h2>BioIntelliSense's&nbsp;BioButton wearable continuously captures respiratory rate, heart rate, skin temperature, activity, and other physiological measurements.Combined with AI analytics on AWS, the platform achieved remarkable clinical outcomes:<ul><li>73% of deterioration events detected early</li><li>50% reduction in manual vital-sign collection</li><li>Average hospital stay shortened by nine hours</li></ul>Instead of relying on four manual observations each day, clinicians receive continuous intelligence 24/7.<h2>Clinomic Mona: An AI Co-Pilot for Intensive Care</h2>Germany-based Clinomic developed&nbsp;Mona, an AI-powered bedside assistant now supporting hospitals across Europe.Rather than displaying fragmented patient information, Mona brings together:<ul><li>Vital signs</li><li>Laboratory results</li><li>Imaging</li><li>Electronic health records</li><li>Predictive analytics</li><li>Voice interaction</li></ul>The result is a single clinical intelligence platform capable of anticipating deterioration before it becomes critical.Hospitals reported:<ul><li>550 clinician hours saved per ICU bed each year</li><li>68% fewer documentation errors</li><li>143% increase in care capacity</li></ul><h2>Johns Hopkins Hospital: AI at Hospital Scale</h2>Predictive monitoring isn't limited to individual patients.Johns Hopkins created a centralized command center using machine learning to continuously monitor hospital operations and patient flow.The system predicts:<ul><li>ICU demand</li><li>Patient deterioration</li><li>Admission surges</li><li>Resource utilization</li></ul>This allows hospital leaders to make proactive operational decisions instead of reacting to bottlenecks after they occur.<h2>AI in Behavioral Health</h2>Behavioral healthcare is also embracing predictive monitoring.One nationwide provider deployed AI-powered automated patient assessments between clinical visits.The results were striking:<ul><li>91% abstinence rate after 30 days</li><li>89% avoided readmission</li><li>948,000+ automated patient touchpoints</li><li>35,000+ clinical staff hours saved</li></ul>Rather than replacing therapists, AI helped identify patients at risk early enough for timely intervention.<h2>How VMO Helps Healthcare Innovators Build Predictive Care</h2>At&nbsp;VMO, we partner with healthcare providers, MedTech companies, and digital health innovators to build secure, scalable AI-powered patient monitoring solutions.Our expertise spans:<ul><li>AI &amp; Machine Learning</li><li>Remote Patient Monitoring (RPM)</li><li>Wearable &amp; IoT Integration</li><li>Real-time Data Engineering</li><li>Cloud-native Healthcare Platforms</li><li>FHIR &amp; HL7 Interoperability</li><li>HIPAA- and GDPR-aligned Software Development</li></ul>Whether you're developing the next generation of virtual care, integrating AI into hospital workflows, or building connected health platforms, VMO delivers the engineering expertise to help transform patient data into proactive, life-saving intelligence. &nbsp;

From Reactive to Predictive: How AI Is Giving Healthcare the Power to See What's Coming

How AI Is Giving Healthcare the Power to See What's Coming

how-ai-is-giving-healthcare-the-power-to-see-what-s-coming

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

On April 1, 2021, VMO Holdings Technology Joint Stock Company (VMO) held a Ceremony to announce its Vision, Mission &amp; Core Values which has been solidified during the past 10 years of establishment and development. On that enduring journey full of proud milestones was the great leadership of the Board of Directors, in alignment with the consensus of all the members of VMO.&nbsp;Along with the outstanding development and growth, VMO embraces the goal of meeting an increasingly rigorous requirements of the IT market, conquering the satisfaction of significant customers in various large-scale projects. Above all lies the ultimate development goal of VMO, closely tied with its core values, lofty mission, and new vision to bring VMO to a new position, increase its influence and spread more good values to the community.In parallel with the investment and development of human resources and technology, VMO clearly understand the desires and ideal that company needs to implement to make VMO a global technology company. VMO officially announce its Mission, Vision &amp; Core values Statement:&nbsp;OUR VISION&nbsp;To be recognized as a Global Leading IT Company<ul><li>To actualize the innovative idea of clients around the world with professional software development and business consultation services.</li></ul>OUR MISSIONFrom Idea to Reality, From Goodwill to Impact<ul><li>VMO turn&nbsp;the&nbsp;ideas of the clients&nbsp;into valuable products that actively contribute for the betterment of the society.</li></ul>OUR CORE VALUESDesire<ul><li>Desire is the aspiration to achive greatness. We desire, we change, we thrive.</li></ul>Transparency<ul><li>&nbsp;VMO Holdings embraces transparency. Internally, we make sure that every voices are listened. To clients, we build the relationship with goodwill and trust. Transparency is the foundation of sustainable development.</li></ul>Conscientiousness<ul><li>We treat each task&nbsp;with&nbsp;passion and enthusiasm. Dedication is the secret of outstanding efficiency.</li></ul>Synergy&nbsp;<ul><li>We&nbsp;are group&nbsp;of&nbsp;different personalities with a same will&nbsp;and common goal. Synergies is the engine of great teamwork.</li></ul>VMO Holdings Technology Joint Stock Company hopes that a new vision, mission, and core values will serve to achieve company’s development goals, bring company to a new position, upgrade its corporate culture, and create useful values to contribute to the development of global humanity.

On April 1,  VMO officially announced vision, mission and Core values Statement

VMO ANNOUNCED VISION, MISSION, CORE VALUES

vmo-announced-vision-mission-core-values

On December 24, 2019, VMODEV Hanoi Technology Joint Stock Company officially established a branch of VMO Japan at 〒101-0047 Tokyo , Chiyoda-ku , Uchikanda, 2-14-12, Hoshiya 6th Building No 402, one of World's largest economic centers.&nbsp;Founded in 2012, VMODEV has over 8 years developing and accompanying many European and American businesses, successfully building many technological products from the concept stage to delivering to users, including the product reaches more than 15 million users worldwide.Quality, Flexibility, Speed are the core values that the leaders and employees of VMODEV have pursued for nearly 10 years. Identifying Japan as the next important market in the company's long-term development strategy, Mr. Hoang Tuan Hai, CEO of VMODEV said: “The Japanese IT market is a large market with strict requirements for quality. We believe that by understanding the culture of our team in Japan, VMODEV can completely bring success to Japanese businesses, such as the satisfaction we bring to clients in the Europe and America, EU markets”.In Japan, VMODEV wishes to assist clients in deploying digital business models, as well as applying IT platforms and new technologies such as AI, Cloud, RPA ... to improve productivity and efficiency for current business models. VMODEV will provide high quality IT human resources for Japanese businesses. It is expected that after Japan, VMODEV will continue to expand more branches in countries such as the USA, Singapore, Korea ... in the near future.&nbsp;More information about VMODEVVMODEV was founded in 2012 by technology enthusiasts and desires to contribute and bring practical values to society. Currently the company has 4 working offices and its headquarters are located in Hanoi, Vietnam. Over 8 years of working with many partners in Europe, America, EU, Asia ... VMODEV has developed more than 300 projects with clients from 11 countries. The products we design and deploy reach more than 45 million users globally.&nbsp;Contact information<figure class="table"><table><tbody><tr><td>VMODEV HANOI TECHNOLOGY JOINT STOCK COMPANYAddess: 15th Floor, TTC Tower, 19 Duy Tan st., Dich Vong Hau ward., Cau Giay dist., Hanoi 100000Phone number: +84 24 3312 0103Website: <a href="https://www.vmodev.com/">https://www.vmodev.com</a>Email: <a href="mailto:info@vmodev.com">info@vmodev.com</a></td><td>VMO JAPAN JOINT STOCK COMPANYAddress: 〒101-0047 Tokyo , Chiyoda-ku , Uchikanda, 2-14-12, Hoshiya 6th Building No 402Phone number: 03-4400-2818Website: <a href="https://www.vmodev.jp/">https://www.vmodev.jp</a>Email: <a href="mailto:infojp@vmodev.com">infojp@vmodev.com</a></td></tr></tbody></table></figure>&nbsp;

On December 24, 2019, VMODEV officially established a branch of VMO Japan

VMODEV OFFICIALLY ESTABLISHED A BRANCH IN JAPAN

vmodev-officially-established-a-branch-in-japan

<ul><li>&nbsp;Design, develop, and maintain ETL/ELT pipelines to ingest, transform, and load data from multiple sources into cloud data platforms.</li><li>Build and optimize data models following Medallion architecture (Bronze/Silver/Gold layers) or equivalent layered data design.</li><li>Develop and maintain data pipelines using tools such as Databricks, Azure Data Factory, or Microsoft Fabric.</li><li>Ensure data quality, consistency, and reliability through validation, testing, and monitoring frameworks.</li><li>Collaborate with Data Analysts, Data Scientists, and Backend Engineers to define data requirements and deliver fit-for-purpose datasets.</li><li>Optimize query performance and storage costs across data warehouse and lakehouse environments.</li><li>Implement and maintain CI/CD pipelines for data workflows, including version control and automated deployment.</li><li>Apply data governance, security, and access control best practices in line with project and compliance requirements.</li><li>Troubleshoot data pipeline issues and provide timely resolution to minimize downtime and business impact.</li><li>Document data architecture, pipeline logic, and technical processes for team knowledge sharing.</li><li>Participate in technical discussions and provide input on data architecture decisions for ongoing and upcoming projects.</li></ul>

Data Engineer - DU33 - ENG GOOD

data-engineer-du33-eng-good

About the RoleThis is more than just a data labeling position. In addition to producing high-quality annotations, you will contribute to building annotation workflows, quality standards, and project guidelines that directly impact the performance of AI models in the IoT and smart device domain.This role offers a clear career path toward Quality Control (QC) Lead and Data Operations positions.Key Responsibilities<ul><li>Accurately annotate various types of data, including images, videos, sequential data, and point cloud data, according to project requirements.</li><li>Ensure annotated datasets meet high standards of accuracy, consistency, and completeness.</li><li>Continuously improve existing annotation workflows to enhance efficiency and productivity.</li><li>Contribute to developing annotation guidelines and quality control (QC) standards.</li><li>Collaborate closely with team members to deliver projects on schedule.</li><li>Train and onboard new team members.</li></ul>

Data Annotation Specialist

data-annotation-specialist

Position Overview&nbsp; &nbsp; We are looking for experienced Senior Software Testers to join cross-functional engineering teams working on advanced 5G/LTE Radio Access Network software products.&nbsp; &nbsp; The role focuses on software integration, verification, test automation, system analysis, and quality assurance activities for Radio Unit Application Software (ASW) and Baseband Software (BBSW) platforms.&nbsp; &nbsp; You will work closely with developers, system experts, technical leads, and project managers in an Agile R&amp;D environment to ensure high-quality telecom-grade software delivery.&nbsp; Key Responsibilities&nbsp;<ul><li>Design, execute, and maintain software verification and integration test activities.</li><li>Analyze system requirements and define comprehensive test scenarios and test strategies.&nbsp;</li><li>Develop and maintain automated test frameworks, scripts, and verification tools.&nbsp;</li><li>Perform feature verification, integration testing, regression testing, and system validation.&nbsp;</li><li>Work closely with development teams to identify, analyze, and troubleshoot software issues.</li><li>Support continuous integration and automated test execution environments.&nbsp;</li><li>Analyze system behaviors, logs, and performance results to identify defects and improvements.&nbsp;</li><li>Participate in root cause analysis and Trouble Report (TR) resolution activities.&nbsp;</li><li>Ensure testing coverage and quality standards across software releases.&nbsp;</li><li>Contribute to process improvements, automation efficiency, and testing best practices.&nbsp;</li><li>Collaborate effectively with distributed global engineering team.&nbsp;</li></ul>

Integration and Verification testing

integration-and-verification-testing

Our business environment relies heavily on software for many functions - from intelligent monitoring systems to automation processes, and cloud computing continues to allow us to modernize, consolidate IT infrastructure, automate workloads and pursue next-generation innovation. To continue this transformation, we’re seeking engineer with expertise in software technology, firm grasp of emerging technologies, platform, applications, and ability to customize to help our business become more secure and efficient. You’ll participate in all aspects of the desktop/web development lifecycle for solution including designing, implementing, building, deploying, testing, and troubleshooting market issues to ensure high standard of application performance, uptime, scale, code quality and thoughtful design.Responsibility<ul><li>Software Development: Designing, developing, testing, deploying and maintaining modular- based systems in accordance with best practices.</li><li>Problem Solving: Troubleshoot incidents, identify root cause, fix and document problems, and implement preventive measures.</li><li>Agile Scrum Practices: Participate actively in Agile Scrum processes, including sprint planning, daily stand-ups, retrospectives, and demos.</li><li>Collaboration: Work closely with cross-functional teams, including product management, design, and QA to ensure seamless integration and delivery.</li><li>&nbsp;Documentation: Maintain accurate and up-to-date technical documentation of software components and systems.</li></ul>

Fullstack .Net WPF

fullstack-net-wpf

<ul><li>Break down main requirements together with the teams and ensure clear scope alignment.&nbsp;</li><li>Work closely with surrounding organizations and coordinate teams across geographical locations.&nbsp;</li><li>Guide teams in implementing architecture, functionality, and features.&nbsp;</li><li>Ensure the backlog is visible, transparent, prioritized, and well understood.&nbsp;</li><li>Own end-to-end delivery responsibility from design to integration and verification.&nbsp;</li><li>Plan milestones, manage dependencies, and track progress together with the teams.&nbsp;</li><li>Proactively manage risks, issues, and escalations.&nbsp;</li><li>Secure required resources (people and equipment) with support from line and program management.&nbsp;</li><li>Ensure quality, timeline adherence, and predictable delivery.&nbsp;</li><li>Drive continuous improvement in products, processes, and ways of working.&nbsp;</li></ul>

Operational  Project Owner

operational-project-owner

Job Description: We’re seeking for Pre-senior/Senior BA/DA to join our team&nbsp;Key Responsibilities<ul><li>Gather, analyse and formalise user’s business requirements and processes, evaluate on feasibility of implementation and manage scope of project.</li><li>Prepare project documentation such as Requirement Specifications/Use Case Specifications etc.</li><li>Adhere to project scope, update requirement traceability matrix, inform and record out-of-scope issues.</li><li>Develop technical design specification and translate technical design into process/program specification. Involve in the design review session.</li><li>Make changes to configurable items, which include hardware, software, documentation, etc.</li><li>Assist in the integration testing, system testing, User Acceptance Test &amp; implementation activities.</li><li>Prepare user manual and operations manual, and plan &amp; facilitate training of users and operators.</li><li>Provide post implementation support (including production support and service requests).</li><li>Escalate and discuss critical issues such as scope creep with the product managers.</li><li>Conduct requirement gathering sessions. Conduct gap analysis of current business process to identify improvement opportunities.</li><li>Collaborate with vendors to address integration challenges, fostering seamless system operation and reliability across systems used in the company.</li><li>Collaborate with stakeholders to enhance systems processes, ensuring alignment with overall business objectives.</li><li>Constantly explore opportunities to enhance systems and explore new tools in the market focusing on improving the efficiency and experience of users.</li><li>Provide technical training to a large audience from the user's perspective.</li><li>In-Depth Performance and Data Analysis for the system and data used by users.</li><li>Support multiple product and project streams, along with varying resources, across the team to ensure on time and quality delivery of all solutions.</li></ul>

Business Analyst

business-analyst

About the Role&nbsp;:&nbsp;Responsible for managing end-to-end recruitment for positions in Telecom, Embedded, Wireless, C/C++, Network, and other specialized technical fields. Proactively develop candidate sources, perform talent mapping, and provide recruitment consultation to support the company’s strategic workforce needs.Key Responsibilities1. Recruitment<ul><li>Manage recruitment activities for positions including Telecom Engineer, Embedded Engineer, Wireless Engineer, C/C++ Engineer, Network Engineer, and related technical roles.&nbsp;</li><li>Handle the full recruitment lifecycle, including sourcing, screening, interviewing, offering, and onboarding.&nbsp;</li><li>Ensure achievement of recruitment KPIs in terms of quality, quantity, and turnaround time.&nbsp;</li></ul>2. Talent Mapping &amp; Market Intelligence<ul><li>Conduct talent mapping of target companies in Telecom, Embedded, and technology-related fields.&nbsp;</li><li>Research the talent market, competitors, and recruitment trends.&nbsp;</li><li>Build and maintain a pipeline of potential candidates to support long-term hiring needs.&nbsp;</li></ul>3. Stakeholder Management<ul><li>Work closely with Hiring Managers and business units to understand recruitment requirements.&nbsp;</li><li>Provide consultation on talent market insights, candidate availability, and appropriate recruitment strategies.&nbsp;</li><li>Track, update, and report recruitment progress on a regular basis.&nbsp;</li></ul>4. Sourcing &amp; Networking<ul><li>Proactively expand sourcing channels, networking activities, and referral networks.&nbsp;</li><li>Build candidate communities and maintain relationships with potential candidates in the market.</li></ul>

Talent Acquisition Specialist

talent-acquisition-specialist

We are seeking a talented Data Scientist / AI Engineer with strong expertise in Generative AI, NLP, and LLM-based applications. The ideal candidate will have hands-on experience building end-to-end GenAI workflows and applying advanced AI technologies to solve real-world business problems.&nbsp;In This Role, You Will:&nbsp;<ul><li>Design and develop end-to-end Generative AI and NLP solutions.</li><li>Build and optimize LLM, RAG, Agentic AI, and NLP applications for business use cases.</li><li>Perform prompt engineering and develop scalable GenAI workflows.</li><li>Develop production-ready AI systems using Python and PySpark.</li><li>Collaborate closely with business and technical teams to deliver AI solutions with measurable impact.</li><li>Clearly communicate technical findings and recommendations to stakeholders.</li></ul>

Data Scientist - AIS

data-scientist-ais

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.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@KFeature Engineering: &nbsp; &nbsp; Build features from user behavior, interaction signals, and context &nbsp; &nbsp; Handle sparse and noisy dataCold Start Handling: &nbsp; &nbsp; Design strategies for new users and new offers &nbsp; &nbsp; Implement hybrid and fallback approachesBias Handling: &nbsp; &nbsp; Mitigate popularity and exposure bias &nbsp; &nbsp; Implement diversity and re-ranking strategiesModel Evaluation: &nbsp; &nbsp; Define and track CTR, conversion, NDCG, AUC &nbsp; &nbsp; Continuously improve engagement metricsScalability &amp; Deployment: &nbsp; &nbsp; Build systems for millions of users &nbsp; &nbsp; Enable real-time or near real-time inference

AI Engineer - onsite

ai-engineer-onsite

<ul><li>Develop, execute, and maintain test plans, test cases, and test scripts for a digital platform.</li><li>Perform functional, regression, performance, integration, and user acceptance testing (UAT).</li><li>Collaborate with developers, business analysts, and designers to understand requirements and ensure test coverage.</li><li>Identify, document, and track defects using issue tracking tools (e.g., JIRA).</li><li>Validate bug fixes and perform re-testing as needed.</li><li>Participate in sprint planning, stand-ups, and retrospectives in an Agile environment.</li><li>Ensure digital products meet accessibility standards and cross-browser/device compatibility.</li><li>Develop and support automation testing efforts and contribute to test automation frameworks.</li><li>Provide QA sign-off for releases and deployments.</li></ul>

Search results

You share it

We care IT

LET'S BUILD SOMETHING GREAT TOGETHER