The demands on IT organizations to navigate a rapidly evolving technology stack while maintaining data compliance, security and data accessibility have never been greater. Organizational changes such as mergers and acquisitions, mandates to move data into cost-effective cloud solutions, and regulatory data privacy and retention requirements add increasing complexity to IT planning. That’s why a comprehensive data archiving strategy has become essential to building a winning, long-term IT plan. Strategies that are too fragmented will fail; you need a combination of best-in-class data archiving capabilities built with a company that can deliver across many different applications and datasets simultaneously.
Moreover, data archiving cannot block users from accessing critical information they need daily. Users need secure, reliable access, and increasingly, even more sophisticated tools to search and analyze data, including generative AI intelligent assistance.
OpenText delivers on these requirements with its comprehensive information archiving approach, including OpenText™ Information Archive for combined structured content and data archiving of any dataset and OpenText™ Core Archive for SAP Solutions that delivers a SaaS-based active-archiving solution uniquely integrated into SAP for maximum cost savings, security, and user convenience. And now, OpenText™ Content Aviator, the AI content management intelligent assistant, is available to provide search, summarization, analysis, tables, and even data charting for data and content stored in your data archive.
We are pleased to announce that OpenText has been named a “Top Player” in the Radicati Information Archiving Market Quadrant 2025. We believe this repeated recognition reflects our customers’ success in addressing data archiving compliance and user accessibility needs securely and cost-effectively is an essential pillar of IT planning.
Radicati Information Archiving Market Quadrant 2025
An analysis of the market for information archiving solutions revealing Top Players, Trail Blazers, Specialists and Mature Players.
“Information Archive offers regulatory compliance where accessibility and reporting across transactional and content records are required”
OpenText information archiving solutions “support GxP compliance”
OpenText “integrates a natural language chat directly into its archiving user interface, providing search, summarization, analysis and translation of archived data and content.”
At OpenText, our innovation roadmap includes a substantial investment in information archiving solutions integrated into the full information lifecycle, improving user productivity and effectiveness with GenAI and other advanced AI capabilities.
Customers share their perspectives on OpenText’s B2B integration platform
The results are in, OpenTextTM Business Network Cloud customers are deriving significant value from their investments with OpenText. With a legacy spanning decades in the B2B integration space, we’ve cultivated deep expertise in technologies that seamlessly connect organizations across global supply chains. But don’t just take our word for it. Through our partnership with UserEvidence, we’re now able to quantify and showcase authentic customer experiences in ways that transcend traditional case studies and testimonials.
This data-driven approach to customer evidence provides potential customers with transparent, verified insights directly from their peers—actual users who leverage our solutions daily to solve complex supply chain challenges.
As organizations continue to navigate unprecedented disruptions and digital transformation initiatives, having access to reliable, peer-validated information is increasingly more critical to the decision-making process. That’s why we’re particularly proud of what our customers are saying, and how their verified feedback demonstrates the tangible impact of our Business Network solutions.
Quantifying Customer Insights with UserEvidence
UserEvidence, a U.S.-based customer evidence platform, independently validates feedback collected directly from our clients, providing transparent and credible insights into real-world experiences. Recent verified data from this platform clearly demonstrates the significant value OpenText customers are deriving from our Business Network solutions:
88% of OpenText users agree that B2B Integration Enterprise is a critical component of their supply chain strategy.
89% of OpenText users saw at least a 25% increase in the number of opportunities uncovered from insights generated by using OpenText B2B Integration Enterprise.
86% of OpenText users saw an increase in supply chain visibility by at least 25% by using OpenText B2B Integration Enterprise.
Parikshit Singh, a software engineer with Lear, shares feedback on support received from OpenText.
Sharing the Impact in Their Own Words: Customer Perspectives
What does this value look like in practice? Our customers explain the tangible benefits they’re experiencing.
“(It’s) user friendly (and) easy to customize. The configuration and connectivity are fully secure and user friendly.” – Naval Singh, EDI business analyst, Google
“OpenText is a reliable company that provides valuable solutions, which have consistently helped us improve our operations and efficiency.” – Siddheswari Donturkurthi, EDI developer, Sony
“OpenText has been a trusted partner for many years, and the service they provide has been good. Account managers and experts from OpenText have given great attention to my company.” – Muraly Munandy, Integration Lead, BAT
“OpenText does a great job of managing, maintaining and administering the components of a managed services EDI relationship.” – Supply Chain Supplier Portal and EDI Administrator, an industrial conglomerates company
“OpenText has enabled us to participate in EDI transactions with vendors in a timeframe which we could not have matched with our current infrastructure and resources. We are also enabled to increase the number of vendors we exchange documents with relative ease and speed.” – Internet Software & Services Company
“Using OpenText B2B Integration Enterprise has allowed us to overcome obstacles in meeting our performance goals. We are now at 100% for the month of August!” – Thomas Rolfes, Supervisor, Polaris Industries Inc.
Discovering More Authentic Customer Success Stories
These testimonials represent just a sample of the wealth of customer insights available through our UserEvidence program. For a deeper dive into how OpenText solutions are transforming supply chain operations across diverse industries, explore our comprehensive User Research hub. There, you’ll find detailed customer evidence, including quantitative metrics and qualitative feedback that showcase real-world applications and outcomes.
Janaina Souza, from General Mills, shares feedback on support received from OpenText.
Building Supply Chain Resilience Through Digital Transformation
In today’s complex business landscape, OpenText Business Network Cloud delivers more than just connectivity. It provides a robust digital backbone that powers end-to-end visibility and control. Our integrated financial, operational, and supply chain solutions enable organizations to streamline processes, eliminate information silos, and leverage data-driven insights that drive strategic decision-making. As global markets face unprecedented volatility, from geopolitical tensions to environmental challenges, these capabilities aren’t merely advantageous — they’re essential for maintaining a competitive advantage and operational continuity.
Taking the Next Step in Your Supply Chain Evolution
Ready to see how OpenText can transform your B2B integration capabilities and strengthen your supply chain resilience? Explore how our solutions have helped organizations like yours overcome complex challenges and achieve measurable results.
Visit Business Network Customer Stories to discover specific use cases and implementation successes across various industries and company sizes. Contact us to discuss how we can help you build a more agile, intelligent supply chain ecosystem for the future.
Artificial intelligence promises to bring a new era of productivity and efficiency to government services and activities. Agencies across the US Federal government have been investigating, planning and implementing AI-based systems that take advantage of advances such as large language models, generative AI, and novel uses of machine learning. The new administration has begun discussing an “AI-first” strategy to streamline government services and decision-making. A new Request for Information from the National Science Foundation “requests input from all interested parties on the Development of an Artificial Intelligence (AI) Action Plan.” This action plan will likely result in recommendations on various topics, including applications of AI in government and public services, cybersecurity, data privacy, and the effective and practical requirements for information governance as the action plan takes shape.
Central to successfully implementing AI is the need for great content management and, with it, content-aware AI systems that can safely and securely deliver trusted machine learning and generative AI capabilities. When combining these elements with AI governance principles, IT and business analysts can be assured that they build on a strong foundation to deliver AI-first productivity and efficiency within each agency.
High-impact opportunities for AI in government
Within each agency AI use case inventory, some common use cases stand out:
Intelligent document capture and workflow processing. AI can evaluate incoming documents, images, and faxes to recognize text and handwriting, extract metadata, classify content for downstream processing and apply security policy. This can help streamline thousands of individual government processes.
Case, contract, and project management applications. Invariably, even highly predictable processes such as law enforcement or legal case management, contract and project management involve large volumes of complex, unstructured documents. Generative AI search and summarization can help users navigate to essential documents quickly and answer questions in minutes, potentially saving hours of difficult document review and research. Moreover, when combined with a content management system, the everyday management of information organizes and governs the content; it also facilitates AI context, significantly improving the accuracy, trustworthiness, and security of AI within the workforce.
Research. Research databases invariably provide text and field searching. However, this sometimes requires users to review dozens or potentially hundreds of documents to find the correct answer. Generative AI that can connect to many different research repositories can consolidate the search process and help speed the research and citation process. AI systems can also provide additional classification and scoring capabilities to evaluate research effectiveness and validity.
Human resources and recruiting efforts. Human resources processes involve large volumes of unstructured and semi-structured content. Generative AI can help to compress workloads when dealing with applicant pools or querying for expertise or field experience within the department.
Freedom of Information Act support. Responding to a FOIA request can be time-consuming and expensive for an agency. Moreover, assuring coverage of complex topics across multiple repositories can complicate the process. AI systems that can access numerous repositories using AI-trained natural language processing (NLP) and provide content labeling and redaction can help streamline these processes and facilitate FOIA responses efficiently.
Use cases that test limits
Some use cases test the limits of traditional AI and machine-learning systems. This is especially true when dealing with complex file formats or rich media. AI systems need to establish secure access to information, the ability to work with many different file formats, and appropriate AI for that media. As an example, some use cases that would test the limits of more traditional systems include:
Speech-to-text transcription and speaker recognition. The ability to turn speech into text accurately, translate it to a common user language, and identify the speaker is called out in several inventories.
Machine vision and object detection. Various use cases require the ability to detect objects and conditions from video feeds. Surveillance cameras, weather cameras, and other video feeds can provide valuable source data, but reviewing the content can be laborious and error-prone without AI. AI can speed up these detection and review tasks and even increase accuracy.
CAD and Engineering management. CAD drawings are used for knowledge management, reference, and research applications. Content management that can handle engineering use cases and incorporates generative AI can help identify drawings for collaboration and reference and quickly cite the actual drawings.
OpenText™ Knowledge Discovery is the foundation of a comprehensive AI strategy
OpenText™ Knowledge Discovery provides a complete solution for addressing complex or large-scale AI use cases for government agencies. With powerful, built-in full-text search, a generative AI-based natural language interface, and visualizations illuminating your data’s hidden relationships, it is the perfect tool for ad hoc search and more directed Q&A applications.
AI content management helps organizations and agencies understand their content and achieve productivity by identifying content quickly, labeling and protecting it, and intelligently putting it to work.
Some of its many capabilities include:
Real-time categorization and machine-trainable classification can instantly group and direct content to key processes.
Review, workflow, and redaction capabilities help facilitate collaborative review of vast content stores, label content, initiate workflows and secure and protect content.
Metadata enrichment can identify sensitive or privacy-related information to apply critical access controls and security labels.
Rich media AI allows agencies to generate audio transcriptions and translations, identify speakers, and provide facial and object recognition in images and video.
Notably, OpenText Knowledge Discovery can connect to existing content repositories (over 160 out of the box) and process over 2,000 file formats. With over 20 years and dozens of patents, OpenText Knowledge Discovery is a comprehensive, secure and scalable solution for addressing AI-first government.
By integrating great content management with generative AI and machine learning technologies, hundreds of high-value, highly productive AI use cases can be quickly implemented. Use cases in various domains, such as case management, research, human resources, and more, showcase AI’s transformative potential to improve government efficiency and productivity while remaining safe and secure. By leveraging advanced AI capabilities, organizations can streamline complex processes, manage vast amounts of unstructured data, and improve decision-making.
In today’s rapidly evolving digital landscape, the convergence of various technologies has introduced new challenges and opportunities for cybersecurity. As organizations strive to protect their critical infrastructure and data from increasingly sophisticated cyber threats, Managed Extended Detection and Response (MxDR) solutions have emerged as a vital component of a robust cybersecurity strategy. This blog delves into the significance of MxDR for threat detection and how it can help organizations safeguard their most valuable assets.
Understanding MxDR
Managed Extended Detection and Response (MxDR) is a comprehensive cybersecurity service designed to provide continuous monitoring, detection, and response capabilities across an organization’s IT environment. By integrating advanced technologies and expert services, MxDR aims to enhance the security posture of organizations, ensuring the protection of critical infrastructure and sensitive data.
MxDR solutions are not just about technology; they also encompass the expertise and experience of cybersecurity professionals who work tirelessly to protect organizations from cyber threats. These solutions combine cutting-edge tools with human intelligence to provide a holistic approach to cybersecurity. By leveraging the strengths of both technology and human expertise, MxDR solutions offer a robust defense against the ever-evolving threat landscape.
Key components of MxDR
Continuous monitoring and detection: MxDR solutions offer 24/7/365 monitoring of IT networks, identifying potential threats in real-time. This proactive approach helps organizations detect and mitigate cyber threats before they can cause significant damage.
Advanced threat intelligence: Leveraging global threat intelligence, MxDR solutions provide insights into emerging threats and attack vectors. This information enables organizations to stay ahead of cyber adversaries and adapt their security measures accordingly.
Incident response and remediation: In the event of a cyber incident, MxDR solutions facilitate rapid response and remediation. Expert incident response teams work to contain and eradicate threats, minimizing the impact on the organization’s operations.
Scalability and flexibility: MxDR solutions are designed to scale with the organization’s needs, providing tailored security measures that can adapt to changing environments and regulatory requirements.
Enhanced security posture: MxDR solutions provide comprehensive visibility into IT environments, enabling organizations to identify and address vulnerabilities effectively.
Proactive threat management: Continuous monitoring and advanced threat intelligence allow organizations to detect and respond to threats proactively, reducing the risk of cyber incidents.
Operational resilience: By ensuring the security of critical infrastructure, MxDR solutions help maintain operational continuity and resilience in the face of cyber threats.
Regulatory compliance: MxDR solutions assist organizations in meeting industry-specific regulatory requirements, ensuring compliance with cybersecurity standards and guidelines.
Resource optimization: The SaaS model of MxDR solutions allows organizations to optimize their resources, focusing on core business activities while relying on expert cybersecurity services.
Real-world validation
OpenText™ MxDR has been recognized for its outstanding performance in the MITRE Engenuity ATT&CK Evaluations for Managed Services. The evaluation highlighted OpenText’s ability to detect and respond to threats with zero false positives, significantly reducing alert fatigue for security teams. This recognition underscores the effectiveness of OpenText MxDR in maintaining cyber resilience and protecting critical infrastructure.
Additionally, OpenText MxDR has been praised for its ability to reduce noise by 97% and detect 99% of threats, as demonstrated in the MITRE Engenuity ATT&CK Evaluations. This capability ensures that security teams can focus on actual security incidents rather than being overwhelmed by false positives.
A recent blog details a successful threat hunt against a ransomware group, showcasing the practical application of an MxDR solution. It describes how OpenText’s threat hunters identified and mitigated a sophisticated attack using advanced threat detection techniques.
Moreover, OpenText was recently named #58 in the MSSP Alert Top 250 MSSPs for 2024. This ranking highlights OpenText’s commitment to providing top-tier managed security services and underscores its position as a leader in the cybersecurity industry.
Act now
As cyber threats continue to evolve, the need for robust cybersecurity measures has never been more critical. MxDR solutions offer a comprehensive approach to protecting IT environments, providing organizations with the tools and expertise needed to safeguard their most valuable assets. By implementing MxDR, organizations can enhance their security posture, ensure operational resilience, and achieve regulatory compliance, all while optimizing their resources and reducing costs.
Don’t wait until it’s too late. Strengthen your cybersecurity defenses today with OpenText MxDR. Contact us to learn how we can help you stay ahead of the ever-changing threat landscape and protect your organization’s future.
The rapid evolution of cyber threats has necessitated the adoption of advanced technologies to enhance threat detection and response capabilities. Supervised and unsupervised machine learning, and generative AI have emerged as transformative tools in cybersecurity, significantly altering how Security Operations Centers (SOCs) operate.
These technologies enable faster, more accurate threat detection and response, while reducing the workload on human analysts.
Supervised machine learning in threat detection
Supervised machine learning (ML) relies on labeled datasets to train models that can classify data or predict outcomes. In cybersecurity, this approach is particularly effective for identifying known threats based on historical attack patterns.
Applications in threat detection
Malware classification:
Supervised ML models are trained on datasets of known malware signatures and behaviors. This enables them to classify incoming files or activities as malicious or benign with high accuracy.
For example, these models can detect phishing emails by analyzing features like sender reputation, email content, and attachment types.
Intrusion detection systems (IDS):
Supervised ML enhances IDS by identifying deviations from normal traffic patterns that match known attack signatures.
This allows for real-time alerts when specific attack vectors, such as SQL injections or Distributed Denial of Service (DDoS) attacks, are detected.
Real-time anomaly detection:
Pre-trained machine learning models establish complex baselines of normal activity across multiple dimensions (e.g., network traffic, user behavior). They can identify subtle deviations that indicate sophisticated attacks such as zero-day exploits.
Impact on SOCs
Increased Efficiency: By automating the detection of known threats, supervised ML reduces the time SOC analysts spend on repetitive tasks like malware classification.
Limitations: The reliance on labeled data means supervised ML struggles with identifying novel or zero-day threats, requiring complementary approaches like unsupervised learning.
Unsupervised machine learning in threat detection
Unsupervised machine learning does not rely on labeled data but instead identifies patterns and anomalies within datasets. This makes it particularly useful for detecting previously unknown threats.
Applications in threat detection
Anomaly detection:
Unsupervised ML models establish baselines of “normal” behavior within network traffic or user activity. Deviations from these baselines are flagged as potential threats.
For example, unusual login times or access to sensitive files from unexpected locations can trigger alerts.
Behavioral analytics:
These models analyze user behavior to detect insider threats or compromised accounts by identifying unusual actions that do not fit typical usage patterns.
Entity resolution:
Identify and merge records that refer to the same entity across different datasets—by leveraging clustering and similarity-based techniques without requiring labeled training data.
Impact on SOCs
Proactive defense: Unsupervised ML enables SOCs to detect emerging threats that lack historical data or predefined signatures.
Reduced false positives: By refining anomaly detection over time with dynamic baselines adjusted continuously so unsupervised machine learning models adapt to changing circumstance and the resulting new norms, automatically, resulting in reduction inthe number of false alarms that analysts must investigate.
Challenges: The lack of labeled data can lead to difficulty in contextualizing anomalies, requiring human intervention to validate alerts. Recent development in leveraging correlation techniques to generate Behavioral Threat Indicators and generative AI are starting to alleviate this burden.
Generative AI in threat detection
Generative AI represents a significant leap forward by leveraging deep learning techniques to create predictive models and simulate scenarios. Its ability to analyze vast datasets and generate synthetic data makes it a powerful tool for threat detection.
Applications in threat detection
Virtual assistant:
Analyzes vast amounts of security data from various sources, using natural language processing to generate insights, summaries, and actionable recommendations to assist security analysts in tasks like threat hunting, incident response, and posture management.
Helps SOCs identify and address potential security issues faster and more efficiently; this includes summarizing complex incidents, providing remediation steps, and highlighting critical details from large data sets, all through a user-friendly natural language interface.
Threat contextualization:
Generative AI enhances situational awareness by correlating data from various sources to provide detailed insights into a threat’s origin, target, and potential impact.
For example, when a new type of malware is detected, generative AI can predict its behavior based on similarities with known malware families.
Synthetic data generation:
Generative AI creates synthetic datasets to simulate attack scenarios, enabling organizations to test their defenses against emerging threats without exposing real systems to risk.
Impact on SOCs
Enhanced decision-making: By providing contextualized insights into threats, generative AI enables SOC teams to make faster and more informed decisions.
Automation of low-level tasks: Generative AI automates repetitive tasks like IP analysis and risk assessment, freeing analysts to focus on strategic initiatives.
Proactive defense: Its predictive capabilities transform cybersecurity from a reactive measure to a proactive system that anticipates attacks before they occur.
Dual-Use risks: Generative AI’s capabilities can also be exploited by threat actors to create sophisticated attacks like deepfakes or automated phishing campaigns.
Comparative impact on SOC operations
The integration of these technologies has redefined how SOCs operate by improving efficiency, accuracy, and scalability.
Feature
Supervised ML
Unsupervised ML
Generative AI
Threat Identification
Known threats based on historical data
Unknown threats via anomaly detection
Predictive identification of novel threats
False Positive Reduction
Moderate
High
Very High
Automation Level
Moderate
High
Very High
Proactive Capabilities
Limited
Moderate
Extensive
SOC Analyst Workload
Reduced for repetitive tasks
Reduced for anomaly investigations
Significantly reduced through automation
Compute Workload
Medium – Ideal for detection of known threats such as malware
High – Ideal for unknown threat detection.
Very High – Ideal for context enrichment and decision assistance.
Challenges and Mitigations
Requires labeled data – Unsupervised Machine Learning provides the essential complementary capability.
Difficult anomaly contextualization – BTI (Behavioral Threat Indicator) and generative AI tackle this issue.
Dual-use risks and computational costs – Rapidly evolving detection LLMs and increasingly efficient techniques address these concerns.
Despite its recent entry into the cybersecurity stage, Identity Threat Detection and Response (ITDR) has gained notable traction among IT and security teams. ITDR combines SIEM and identity security into an integrated environment that not only ties events to identities but initiates a security response. Because ubiquitous connectivity to sensitive information continues to spread, organizations are recognizing that they need to invest in more effective ways to secure their sensitive digital assets.
What makes ITDR different?
The identity elements of ITDR include addressing risks associated with compromised credentials, identity misuse, and insider threats. They are the focus because it’s typically easier to exploit compromised credentials rather than potential software vulnerabilities to circumvent security. Whether phished, stolen from repositories, or captured from loggers, credentials remain the foundation of today’s outsider intrusions. As such, to be effective, organizations need stronger security than just a claimed identity with its credentials.
The Dark Reading – OpenText ITDR Survey
Only a few years ago, Gartner broke out a separate security category focused on detecting and responding to identity-based threats – ITDR. Because of ITDR’s rapid assentation and emphasis, OpenText commissioned Dark Reading to conduct a survey to assess their defense posture against identity-based attacks. In the same way that Harley Adams and I walked through other Dark Reading surveys, we will take you through our latest survey.
After a quick run through the demographic, we’ll review how far along ITDR deployments are, highlight trends, discuss perceived value, and pull out some surprising nuances.
Join our live webinar to discuss the results!
View our webinar on demand, hear the survey results first hand and get our experts’ take on what it means for your organization.
The beginning of the year is the perfect time to reflect on one’s successful journey and set our sights on the future. At OpenText, our Canadian roots have always been a source of pride, shaping our commitment to innovation, diversity, and ethical business practices. Born at the University of Waterloo, we’ve grown into a global leader, yet our core values remain steadfast.
As one of Canada’s largest software companies, OpenText plays a critical role in fueling the country’s technology sector. We invest in local talent, partner with top Canadian universities, and support emerging startups, ensuring that the next generation of innovators has the tools they need to succeed. Our presence strengthens Canada’s position as a global technology hub, proving that world-class innovation can thrive outside Silicon Valley. Being a proudly Canadian company is more than just geography—it’s about embracing the values of inclusivity, resilience, and forward-thinking leadership that define our nation.
Embracing the future with OpenText
In 2025, we’re more dedicated than ever to empowering businesses with cutting-edge solutions:
AI-powered content management: Our latest Cloud Editions (CE) 25.1 seamlessly integrate cloud, security, and AI technologies, forming the foundation for sustainable growth and innovation.
Enhanced customer engagement: OpenText™ Core Messaging now includes rich media experiences and expanded omnichannel communications, enabling businesses to deliver ultra-personalized, on-brand interactions across various platforms.
Commitment to sustainability: Through the OpenText Zero-In Initiative, we’re focused on achieving measurable Environmental, Social, and Governance (ESG) goals, harnessing technology for the greater good.
Join us on the journey
As we navigate the evolving digital landscape, OpenText remains your steadfast partner, offering:
Cultural alignment: With a deep understanding of the Canadian market, we tailor our solutions to resonate with your unique business dynamics and values.
Unwavering support: Our dedicated team is committed to your success, providing local expertise and personalized service every step of the way.
Let’s embark on this exciting journey together, leveraging Canadian-born innovation to propel your business toward its strategic goals in 2025 and beyond. Explore the broad range of solutions we offer to help you tackle your biggest information management challenges.
The concept of digital product passports (DPPs) may revolutionize how we track, use, maintain, and repair products throughout their lifecycle, including recycling and repurposing. Emerging EU regulations focused on sustainability are a key driver for DPPs adoption, but similar efforts are also underway in other parts of the world. Beyond regulations, there are other compelling business benefits organizations should consider as they navigate the rapidly evolving space.
Watch The Video – 5 Things You Should Know About DPPs
I recently spoke at the 10th Annual SCL HUB Supply Chain & Logistics Conference in London alongside my colleague, Steve Dale, where we discussed the 5 Things You Should Know About Digital Product Passports and shared insights on how to best leverage DPPs within your supply chain.
OpenText Subject Matter Experts discuss Digital Product Passports at the 10th annual SCL HUB Supply Chain Conference
What is a digital product passport?
A digital product passport, or a DPP, is essentially a digital record linked with a physical product that contains a comprehensive set of information pertaining to that specific product. This may include things like manufacturing location, date and time, product materials and composition, labels and certifications, environmental impact, instruction and maintenance manuals, service history, and so on.
To capture the key elements included in a DPP, the CIRPASS project—a program funded by the EU to clear the way for piloting and deploying standards-based digital products passports—defined DPP as “a structured collection of product related data with pre-defined scope and agreed data management and access rights conveyed through a unique identifier and that is accessible via electronic means through a data carrier.”
Bit of a mouthful, yes, but the CIRPASS definition illustrates the EU’s ambition behind digital product passports, which is to make them dynamic enablers of new business models and stakeholder collaboration as opposed to just a static collection of product attributes on a web page.
Why do digital product passports matter?
Emerging EU regulation is the primary reason why interest around digital product passports is growing rapidly as it will force organizations selling their products in the EU to comply with new mandates. A key piece of legislation driving DPPS adoption in Europe is the Ecodesign for Sustainable Products Regulation (ESPR), which was entered into on July 18th 2024.
The ESPR mandates the deployment of digital product passports across a broad range of product categories, but the details are governed by additional regulations that focus on specific types of goods. For example, a battery regulation passed by the EU in July 2023 mandates the adoption of QR-code based digital battery passports starting from February 18th, 2027, for all electric vehicle, light mobility vehicle and industrial batteries with a capacity greater than 2kWh.
The rollout of EU mandates is happening gradually between 2026 and 2030. In addition to batteries, other types of goods prioritized by the EU include textiles, electronics, tires, and goods related to the construction value chain such as steel.
While the EU is leading on digital product passports, similar developments are happening around the world. The UK government has proposed a policy concept for product passports as part of its waste and resource strategy. The Canadian government has initiatives around battery passports for EV batteries and US discussions are occurring within the automotive industry. China has launched development for its own digital product passports, while India has identified digital product passports as an opportunity for its software industry. Other developments and discussions have also been taking place at least in Brazil, Indonesia, South Korea, Australia, Chile and Japan.
From regulatory compliance to a business opportunity
For organizations operating in today’s global marketplace, DPPs represent both a challenge and an opportunity. Manufacturers must navigate and adapt to new and emerging regulatory requirements—much of which are still unknown and being defined—but they can also unlock significant value for their business.
Implementing DPPs forces companies to invest in linking the products they manufacture with a digital repository. The ability to capture data at key points during production and logistics processes provides businesses deeper visibility into their supply chains through better product traceability. Not only does this help track goods as they move through the supply chain, but it can drive value post-sale by enabling manufacturers to minimize the scope of product recalls and capture valuable insights on product usage, maintenance, repairs and recycling. When using unique product identifiers, manufacturers can also establish mechanisms to protect their products against counterfeiting and even theft.
Beyond product traceability and authentication, another great opportunity relates to crafting new kinds of digital customer experiences. While the regulations require manufacturers to offer an easy way to access specific product information through a digital channel, how this mandated information is served and what else is made available is likely to be highly flexible. This means that manufacturers can embed the regulated information as part of an overall brand experience and even combine it with loyalty programs, customer support and tailored marketing campaigns—within the bounds of privacy regulations, of course.
Successful DPP deployment strategy enables a win-win-win situation
The benefits of digital product passports extend to multiple stakeholders across the value chain. As discussed, for manufacturers DPPs provide enhanced product traceability, brand protection and new opportunities to build digital customer experiences.
For customers buying and using the product, DPPs provide easy access to a rich set of information covering product safety, correct usage, sustainability, composition, product origins and more. Customers can also benefit from the enhanced brand experience offered by manufactures through things like easy product authentication and better warranty programs.
In addition to manufacturers and the customers buying their products, digital product passports can benefit third parties, including retailers and distributors, maintenance and repair service providers, authorities, and others.
Key benefits of a DPP strategy
The potential for this “win-win-win” situation benefiting various parties is there, but delivering on it requires a comprehensive strategy backed up by investment in the right digital capabilities. These include, for example, the following:
Digital product link: Mechanism through which a user can access the digital product passport, such as a product traceability service offering serialized QR-codes for unique product identification.
Digital product passport user interface: The view that a user sees when they access the digital product passport making all the required information available, such as a web content management system. Crafting the user experience may also involve leveraging a customer data management system for richer customer engagement and personalization.
Backend integrations and data acquisition: Obtaining the various types of information relating to the product such as GTIN and other identifiers, information coming from suppliers, and supply chain and transportation events. This may include integrations with international data spaces or other product data sharing platforms, industry data pools, and more. Building and maintaining these integrations requires an integration platform that can support all the required data flows across the ecosystem.
On top of the technical capabilities, organizations need a strategy and expertise for deploying these in their operations. Depending on the scope and ambitions of the overarching digital product passport solution, working closely with selected software vendors, leveraging a phased approach where possible, and leaving enough time for comprehensive solution design and project planning play a key role in ensuring success.
To find out how OpenText can help on your journey to adopting digital product passports, contact us for more information.
Migrating to the cloud is a significant step for any business, but it’s often surrounded by misconceptions that can create hesitation. Let’s focus and demystify some of these common concerns and explore how OpenText, as your trusted cloud partner, can help you navigate the cloud migration journey with confidence.
Misconception 1: Keeping data on-premises is safer than in the cloud
Myth: Some fear that migrating to the cloud means losing control over their data and IT infrastructure. Keeping data secure and compliant is a resource-intensive activity that requires specialized tools and expertise
Reality: With OpenText, you retain control over your data. Our cloud solutions offer robust management tools and customizable options, ensuring you have the control and visibility you need. In the OpenText Cloud our experts become an extension of your security team. They manage security and privacy threats 24/7.
Misconception 2: We will lose control of our application and our data once it is in the cloud
Myth: Many businesses fear that migrating to the cloud means relinquishing control over their applications and data. This myth stems from concerns about data security, accessibility, and management in a cloud environment.
Reality: You retain ownership of your data in the cloud. OpenText as a cloud provider ensures that you have full control over your data, including who can access it and how it is used. You can set permissions, manage access controls, and monitor data usage to ensure it aligns with your policies. OpenText employs advanced security measures, including end-to-end encryption, regular security assessments, and compliance with industry standards like ISO 27001 and SOC 2. In many cases, data can be more secure in the cloud than on-premises
Misconception 3: It’s cheaper to stay on-premises
Myth: The belief that maintaining on-premises IT infrastructure is cheaper than migrating to the cloud is a common misconception. It’s easy to overlook the many hidden costs that make operating on-premises more expensive: allocating shared infrastructure components, operational maintenance, application upgrade and update cycles, security and privacy control overhead, and performance optimization.
Reality: Cloud services operate on a pay-as-you-go model, converting capital expenses into operational expenses. This means you only pay for the resources you use, which can be more manageable and predictable. In addition, cloud providers handle maintenance, updates, and hardware refreshes as part of their service. This eliminates the need for businesses to invest in and manage these tasks, reducing overall costs. In addition, the cloud offers unparalleled scalability and flexibility. You can easily scale resources up or down based on demand, ensuring you only pay for what you use. This elasticity allows you to respond quickly to changing business needs without the financial burden of over-provisioning
Misconception 4: We will have performance issues and compatibility concerns
Myth: Users worry that the geographic distance between cloud servers and their location can cause delays in data transmission, leading to slower application performance. There are also some incorrect viewpoints that applications may not be designed for cloud environments, leading to performance issues when migrated. Also many businesses worry that their existing applications and systems won’t be compatible with cloud environments, leading to disruptions and additional costs.
Reality: While network latency can be an issue, solutions like edge computing and multi-cloud architectures can significantly reduce latency by bringing data closer to the user. Upgrading to a cloud-native release provides a modernized architecture and will make adopting feature updates faster, easier and more cost-effective (learn about OpenText Cloud Editions). During the ‘move to modernize’ activities OpenText’s migration team will upgrade your applications as part of moving to the cloud. You will maximize the benefits of being in the cloud by using the latest application version to gain agility and fuel growth. Learn about these options with OpenText’s cloud migration services.
Choosing your partner
Choosing the best partner for performing a migration of data to the cloud is an important step to consider. From process expertise to compliance to the latest processes and technologies, OpenText™ Professional Services experts can guide and support you throughout the cloud migration process. By putting your valuable data into the hands of OpenText Professional Services, the cloud experts will provide the quickest return on investment and give you peace of mind while delivering security, reliability, compliance and scalability of your data, whether in the OpenText Cloud, hybrid scenarios or even in other 3rd party clouds. For more information on migrating to the cloud, please contact us.
Most built-in security analytics solutions are nothing more than basic rule sets and correlation scripts. They offer little protection against subtle insider threats and emerging attack vectors. If your system’s idea of “behavior analysis” is flagging a single late-night login without context, or drowning your SOC in useless alerts, it’s effectively worthless. The real challenge isn’t collecting more data—it’s connecting the dots in real time, refining baselines automatically, and highlighting suspicious behavior that actually matters. That’s where advanced behavioral analytics makes all the difference.
The real power of behavioral analytics
At its core, behavioral analytics is about knowing how your users, devices, and systems act on a daily basis—then spotting even the slightest deviation. It doesn’t rely on the same old laundry list of “bad” signatures. Instead, it figures out what’s normal for each individual or entity and flags anything significantly off-track. There are three key factors that make true behavioral analytics solutions powerful.
Adaptive learning: When your organization evolves, so do your baselines. No endless tuning or guesswork—just continuous adaptation.
Context-driven insights: It’s not about a random login alert; it’s about understanding that a user who typically accesses financial records at 10 AM is suddenly pulling them at Midnight from a remote IP.
Proactive approach: Relying on known signatures is fine for everyday attacks, but it crumbles when faced with stealthy insiders or brand-new exploits.
Why traditional security measures fall short
Every SIEM, EDR, NDR, XDR, DLP, IAM, and any other acronym for a security solution lists behavioral analytics as a feature. However, while this so-called “behavioral analytics” capability might look great on a features list, does it truly adapt to real-world change? We’ve seen baked-in behavioral analytics frequently crumble in key areas:
High false positives: You don’t need another flood of meaningless alerts.
Negligence toward insider threats: Curious how that unsuspecting employee suddenly accessed confidential info at 3 AM? Static rules aren’t going to catch that nuance.
Manual overload: If your security teams are stuck updating rules every time someone switches departments, your “analytics” are a time sink, not a solution.
True behavioral analytics fixes these blind spots by zeroing in on genuine anomalies – no more “just trust us” rules that may or may not align with your reality.
How OpenText does it differently
Plenty of vendors throw around “behavioral analytics,” but OpenText actually delivers. We recently announced the launch of OpenText™ Core Threat Detection and Response. It uses unsupervised machine learning and advanced AI to address what other solutions often miss. Here is what it can do for your business:
Always-evolving baselines Tired of babysitting your detection system with manual rule updates? OpenText Core Threat Detection and Response adjusts on its own—so you get fewer false alarms and a more authentic read on user behavior.
Seamless integration with real context We slot right into Microsoft Defender for Endpoint and Entra ID without forcing you to re-architect your environment, adding a powerful layer of analytics on top of your existing tools.
High-context alerts, not mystery warnings We won’t leave you guessing why something’s been flagged. Our system gives you the full story—who did what, when, and why it’s actually suspicious—so you can act fast.
Automated threat hunting Let your threat hunters stop threats. Our system hunts down suspicious behavioral patterns in the background, giving defenders precious time to tackle genuine threats—not sift through noise.
Proactive insider threat detection Insider threats can gut your business from the inside out. By focusing on subtle behavioral shifts, we catch the warning signs early—long before you’re dealing with a data breach nightmare.
Scalability that grows with you Your business changes, your threat landscape evolves, and we keep up. Period.
Tangible benefits OpenText offers that you can’t ignore
Early detection of hidden threats Competitors talk the talk; we walk the walk. We catch that rogue employee funneling files to a personal account before it spirals into a headline-grabbing incident.
Reduced alert fatigue Ever wonder how much time your SOC wastes on false positives? By focusing on genuine anomalies, you trim the fat and let your analysts focus on the real issues.
Continuous adaptation Every time you add a new application or shift roles, your detection just updates—no human intervention required to stay current.
Speedy investigations Why? Because your team doesn’t have to waste hours piecing together a million random alerts. Our context-driven approach streamlines everything.
Complement, don’t replace We’re not telling you to toss your SIEM or endpoint tools. We’re giving them a powerful ally to actually deliver the results you’ve been expecting.
Ready to get serious about threat detection?
Let’s be honest: attacks have gotten a lot smarter, while many security solutions have barely moved the needle. If you’re done settling for generic, rules-heavy “behavior analytics” that fails to live up to the hype, maybe it’s time for a change.
OpenText™ Core Threat Detection and Response doesn’t just layer on more noise. We focus on real anomalies, minimize guesswork, and help you spot dangers before they become disasters. Plus, we slide right into your existing security world, so you can level up without tearing down.
Learn how the truly adaptive behavioral analytics of OpenText Core Threat Detection and Response can transform your security posture. No fluff. No filler. Just the proactive, context-rich detection you’ve been missing. Would you like to see it in action? Check out our interactive demo.
