Page 7 – OpenText Blogs

Continuous testing 101: What you need to know

Have you ever tried to build a LEGO® set only to realize—dozens of steps into the project—that you misplaced a tiny piece early on? As a result, the entire structure looks off… or worse, you can’t finish it at all. Now imagine that happening in software development. A single overlooked bug or integration issue early in the process can derail your entire release. That’s where continuous testing comes in. It’s like checking each piece as you go, ensuring everything fits correctly—before you get too far to fix it easily. In this blog, we’ll break down what continuous testing is, why it matters, and how automation and AI make it smarter than ever.

What is continuous testing?

Continuous testing is the process of executing automated tests throughout the software delivery pipeline—not just at the end. It ensures every code change is validated early, often, and automatically, so that defects are caught when they’re cheapest and easiest to fix. Think of it as embedding quality checks into every stage of development.

What is an example of great continuous testing?

Let’s say a developer is running daily SAP updates across multiple regions. Every night, automated software testing scripts run regression tests on critical business processes. With continuous testing, failures are flagged immediately, enabling fixes before users are affected—all without human intervention.

With AI-powered automation and test management software, the team maintains high coverage with minimal maintenance effort, even as applications evolve rapidly.

Why is it an important topic today?

Software delivery is shifting from scheduled releases to on-demand, always-on development. Organizations adopting agile and DevOps need testing to keep pace (see what is agile testing). Without continuous testing, teams risk releasing bugs into production—or slowing delivery to avoid risk. In a world where digital performance directly affects business outcomes, continuous testing is essential to delivering value faster and safer.

What role does automation have?

Automation is the engine that powers continuous testing. It enables testing to scale without the need for manual execution. The OpenText automation framework includes AI-enhanced object recognition, auto-maintained scripts, and test data management—reducing test flakiness and helping teams focus on building rather than fixing.

What role does AI have?

AI makes continuous testing smarter and more resilient. OpenText applies AI to detect UI changes, auto-heal broken scripts, and even suggest test scenarios based on user behavior. This dramatically reduces the maintenance overhead of test automation—a major blocker for many teams.

Is it related to continuous integration?

Yes—continuous testing is tightly integrated with continuous integration (CI). As developers check in code, CI tools trigger automated tests immediately. This feedback loop ensures every build is evaluated for risk. OpenText integrates with Jenkins, GitLab, Azure DevOps, and others to ensure testing fits seamlessly into your CI/CD pipeline.

How is it different from agile testing?

Agile testing is a broader philosophy that supports the agile development cycle with fast, collaborative, and iterative testing. Continuous testing is a tactic within agile—focused on running tests continuously and automatically. In addition, Agile testing often involves manual exploratory testing too, while continuous testing is automation-driven and pipeline-integrated.

Deliver quality software

Continuous testing is not just a best practice—it’s a business enabler. With OpenText, organizations gain the tools to deliver quality software faster, reduce risk, and simplify test management across complex, modern systems. Find out how you can deliver with continuous testing.

Dylan Roberts

August 12, 2025

DevOps, Technologies

AI, automated testing, Automation, continuous quality, continuous testing, software testing

DevOps vs DevSecOps: Key differences and why they matter

In software development, methodologies come and go but few have made as profound an impact as DevOps. Then came DevSecOps, the security-enhanced sibling that promises to integrate security into every stage of the DevOps lifecycle.

But what exactly sets DevSecOps apart from DevOps? And does adding “Sec” really change the game?

Let’s break it down.

DevOps: Speed meets collaboration

DevOps is a set of practices that aims to bridge the gap between software development (Dev) and IT operations (Ops). Its goal is simple but powerful: enable organizations to deliver applications and services at high velocity.

Key characteristics of DevOps:

Collaboration between dev and ops teams
CI/CD pipelines for faster, automated deployments
Infrastructure as Code (IaC) for consistency and scalability
Monitoring and logging to ensure performance and uptime

DevOps is all about speed, automation, and breaking down silos.

DevSecOps: Security joins the party

DevSecOps builds on the foundation of DevOps by integrating security into the development process from the very beginning. Instead of treating security as a final gate, DevSecOps embeds it into every phase of the SDLC (Software Development Life Cycle).

Key characteristics of DevSecOps:

Shift-left security, where security practices begin in early development stages
Automated security testing within CI/CD pipelines
Threat modeling and compliance checks as code is developed
Collaboration between development, operations, and security teams

With DevSecOps, security becomes everyone’s responsibility, not just the security team’s problem at the end of the pipeline.

DevOps vs DevSecOps: What’s the difference?

Feature	DevOps	DevSecOps
Focus	Speed, automation, and reliability	Speed, automation + integrated security from start to finish
Team involvement	Dev + Ops	Dev + Ops + Security
Security approach	Often reactive, tested at the end	Proactive, built-in from the start
Tooling	CI/CD, IaC, monitoring tools	CI/CD + SAST, DAST, container scanning, policy-as-code
Goal	Deliver fast, reliable code	Deliver fast, reliable, and secure code

Why DevSecOps matters

In today’s cloud-native, microservices-driven world, the attack surface is expanding rapidly. High-profile breaches often exploit vulnerabilities that could have been caught earlier with a security-first mindset.

Adopting DevSecOps leads to:

Fewer vulnerabilities in production
Faster remediation of security issues
Improved compliance with regulations like GDPR, HIPAA, and PCI-DSS
Better collaboration across traditionally siloed teams

It’s not about slowing down development, it’s about enabling secure development at speed.

Can you transition from DevOps to DevSecOps?

Absolutely. Here are some steps to begin:

Educate teams on secure coding practices and threat awareness.
Integrate security tools into your CI/CD pipelines.
Automate security testing to ensure it scales with development.
Foster a culture where security is part of every conversation.

The transition isn’t just technical, it’s cultural.

Speed is great. Security is better. Both is best.

DevOps transformed how we build and deliver software. DevSecOps is transforming how we build secure software. While DevOps gets you to production faster, DevSecOps ensures you get there at speed, safely.

In a world where cyber threats are increasing in frequency and complexity, security can no longer be an afterthought. Incorporating security into your DevOps isn’t a nice-to-have, it’s a necessity.

Ready to shift left? Your code (and your customers) will thank you. Learn more about how the OpenText DevSecOps solution can help you deliver software faster without sacrificing security.

Mary Ludwig

August 12, 2025

DevOps, News & Events, Security, Technologies

devops, DevOps Cloud, DevSecOps

Your DevOps stack doesn’t need more tools. It needs more control.

Speed used to be enough. It isn’t anymore. In regulated industries and large enterprises, velocity without visibility isn’t innovation—it’s risk. Teams need a way to deliver software faster without sacrificing compliance, quality, or control. They need a DevOps platform for the AI era.

Enter OpenText™ DevOps Cloud. This isn’t another DIY toolchain. It’s a unified platform, anchored by OpenText™ Core Software Delivery Platform and powered by OpenText DevOps Aviator™—built for AI-led, compliant, enterprise-scale delivery.

One platform. Total pipeline control.

Modern DevOps teams aren’t asking for more tools. They’re asking for tools that work together. OpenText DevOps Cloud replaces toolchain sprawl with orchestration, traceability, and full visibility across the value stream.

From planning and testing to release and operations, everything runs on one platform. With more than 250 integrations, teams don’t have to rip and replace: they just work smarter, faster, and more securely.

And with embedded GenAI assistants, you don’t just automate the busywork, you surface risks earlier, generate tests on demand, and reduce time to resolution dramatically.

Intelligent delivery doesn’t require more tools. It requires one that knows what to do.

Compliance that moves at DevOps speed

In industries like banking, healthcare, telecom, and government, every release must be auditable, secure, and reliable. Governance can’t be an afterthought. OpenText makes it native.

From embedded quality gates and policy enforcement to traceability across Jira, SAP, and test pipelines, we ensure that every change is tracked, every artifact is linked, and every release meets the standards that matter most.

Whether you’re building digital banking platforms, migrating to S/4HANA, or delivering life-critical health apps, OpenText DevOps Cloud helps you move fast and stay in bounds.

Test like its mission-critical (because it is)

Downtime during a product launch or ERP cutover doesn’t just delay delivery. It can cripple trust.

OpenText empowers you to test at scale, under real-world conditions. Our performance engineering tools simulate global load patterns, diagnose bottlenecks with AI, and surface failure patterns before users ever feel the impact.

OpenText DevOps Aviator even predicts release risk and helps optimize load distribution for cloud-native and hybrid workloads. You don’t just find problems faster—you prevent them altogether.

When performance breaks, trust breaks. With OpenText, it doesn’t have to.

Built for the AI era. Proven at enterprise scale

DevOps Aviator is embedded directly into the platform. It generates tests, flags compliance issues, forecasts release risk and accelerates delivery decisions without requiring teams to jump between tools.

Enterprises like Kellanova and OpenText itself trust the platform to consolidate delivery workflows, enforce compliance, and deliver at scale. At OpenText, over 7,000 engineers rely on DevOps Cloud daily across 50+ products, using embedded AI to plan, test, and release with speed and confidence. Across industries, customers are reducing deployment time by 96%, increasing test coverage by 17x, and securing complex systems with ease.

Ready to replace chaos with control? Your teams are ready to move faster. Your business needs to move safer. And your toolchain needs to start working for you, not against you. OpenText DevOps Cloud is the platform built for what’s next: the DevOps platform for the AI era.

Gabriel Martinez

August 11, 2025

DevOps, Technologies

DevOps Aviator, DevOps Cloud, devops platform, modern devops, SDLC
From experiments to expected: How AI is fundamentally reshaping the retail industry in 2025

The retail landscape of 2025 bears little resemblance to that of even a few years ago. The industry has decisively moved beyond viewing Artificial Intelligence (AI) as a mere experimental tool or futuristic concept. Today, AI is an expected—indeed essential—component of any competitive retail strategy. Its pervasive integration across customer-facing interactions and back-end operations is fundamentally reshaping how retailers compete, operate, and engage with consumers. AI solutions like OpenText Aviator are playing a pivotal role in this transformation.

The evolution: From niche to non-negotiable

Historically, AI in retail was often confined to rudimentary recommendation engines or basic chatbots. These early forays, while promising, were limited in scope and impact. Fast forward to 2025, and AI’s capabilities have matured dramatically, transitioning from isolated experiments to deeply embedded, mission-critical functions. The drivers for this accelerated adoption are clear: surging consumer expectations for hyper-personalization, fierce e-commerce competition, and the urgent need for greater operational efficiency and supply chain resilience.

4 key shifts driven by AI in retail

1. Hyper-personalization and the one-to-one experience

The days of generic segmentation are over. AI now empowers retailers to deliver truly bespoke experiences. Using sophisticated algorithms, machine learning models, and increasingly generative AI, retailers analyze vast datasets—including browsing behavior, purchase history, real-time context (such as local weather or current events), and sentiment from customer interactions—to craft highly individualized experiences. This extends to dynamic pricing, personalized product recommendations, and tailored marketing campaigns delivered across all channels.

Generative AI is no longer just a novelty; it’s actively creating personalized product descriptions, marketing copy, and even facilitating virtual try-on experiences, significantly reducing friction in the customer journey and enhancing conversion rates.

2. Elevated customer experience and service automation

The humble chatbot has evolved into a sophisticated virtual assistant. Powered by advanced Natural Language Processing (NLP) and Large Language Models (LLMs), AI-driven conversational agents provide 24/7, human-like support. They adeptly handle routine inquiries, guide customers through complex purchases, and even offer proactive assistance based on predictive analytics. This frees human agents to focus on more complex, empathetic interactions, significantly improving overall customer satisfaction and operational scalability. The frictionless experiences now expected by consumers—from seamless returns to instant query resolution—are largely underpinned by intelligent automation.

3. Optimized operations and predictive efficiency

Beyond the customer interface, AI is revolutionizing back-end retail operations. AI models are crucial for several key areas:

Demand Forecasting: Far more accurate than traditional methods, AI integrates diverse data points to predict demand with unprecedented precision, minimizing stockouts and overstocking, which are critical for margin protection.

Inventory Management: AI-powered systems automate stock tracking, optimize reorder points, and guide warehouse automation, leading to significant cost savings and improved availability.

Dynamic Pricing: Continuous analysis of market conditions, competitor pricing, and real-time demand allows AI to adjust prices dynamically, maximizing revenue and market competitiveness.

Loss Prevention: Computer vision systems combined with AI actively detect suspicious activities in stores, significantly reducing shrinkage and improving security.

4. Resilient and transparent supply chains

Retail supply chains, historically prone to disruptions, are becoming more agile and transparent with AI. AI-driven analytics provide end-to-end visibility, predicting potential bottlenecks or delays before they impact operations. This predictive capability enables proactive mitigation strategies, enhancing resilience. Furthermore, AI combined with blockchain technology is increasing traceability, ensuring product authenticity, ethical sourcing, and adherence to sustainability goals—a growing expectation for modern consumers.

The path forward: Navigating the AI imperative

The shift from experiments to expected means that AI is no longer a strategic option but a strategic imperative. Retailers who fail to embrace and integrate AI across their operations risk falling behind competitors who are leveraging these tools to gain unprecedented insights, optimize processes, and deliver superior customer experiences.

However, success with AI is not merely about adopting technology; it requires a holistic approach. Key considerations include:

Data Foundation: Ensuring clean, integrated, and accessible data is the bedrock for effective AI.

Ethical AI and Trust: Retailers must be transparent about AI usage, prioritize data privacy, and ensure AI systems are free from bias to maintain consumer trust.

Talent Transformation: Investing in upskilling employees and attracting AI talent will be crucial for maximizing AI’s potential.

Scalability and Security: Deploying AI solutions that can scale with business growth while maintaining robust security protocols is paramount.

The future of AI and retail

As we move deeper into 2025, AI is not just changing the retail industry; it is becoming the retail industry. Solutions like OpenText Aviator are enabling retailers to harness this power securely, responsibly, and at scale, ensuring they remain competitive and relevant in an increasingly intelligent marketplace.

Scott Lundstrom

August 11, 2025

Analytics, Aviator AI, Industries, Information Technology, Line of Business, Retail, Technologies

AI, AI & Analytics Services, Personalization, predictive maintenance, supply chain
How AI in government is doomed to fail without a data management strategy
Artificial Intelligence (AI) is poised to radically transform government services. From automating routine tasks to enabling smarter decision-making, AI promises to revolutionize public sector service delivery, improve citizen experiences, and drive efficiency across agencies.

But a sobering trend is quietly emerging: many government AI projects stall or fail to deliver meaningful results. The reason isn’t a lack of vision or funding; it’s the reality that most agencies lack the data management foundation necessary for AI to succeed.

Between 70% and 85% of AI projects fail to meet their expected outcome. Public sector and enterprise initiatives consistently face even higher risks when data management is lacking.

Why data management is crucial to government AI projects

Government agencies must confront the state of their data to deliver on the promise of AI. They can do this by addressing:
- Siloed and fragmented information: Decades of legacy systems, paper records, and disconnected databases have created fragmented data environments. AI systems require unified, accessible, and high-quality data to function effectively.
- Data quality challenges: Poor data quality, redundancy, and outdated records undermine the accuracy and reliability of AI-driven insights. As industry experts note, “garbage in, garbage out” is especially true for machine learning and analytics.
- Compliance and security risks: Sensitive government data must be managed with strict attention to privacy, compliance, and security. Without robust data governance, AI initiatives risk exposing agencies to regulatory and reputational harm.
The lesson is clear: no matter how advanced AI technology is, it cannot compensate for disorganized, incomplete, or inaccessible data. For public sector leaders, investing in a comprehensive data management strategy is not a nice-to-have strategy; it’s the foundation for any successful AI initiative.

Why AI needs clean, accessible data

For AI to deliver on its promise in government, agencies must ensure their data is high-quality, well-governed, and readily accessible. Even the most advanced commercially available AI systems run off the rails when relying on poor-quality data, providing inaccurate analysis or even creating hallucinations.

The foundation: AI’s dependence on quality data
- Training and automation:
  AI and machine learning models require large volumes of accurate, well-structured data to learn, adapt, and automate processes. If data is incomplete, outdated, or siloed, AI systems can’t function effectively or deliver meaningful results. To deploy AI and derive insights from government data, it’s important to train the tool against accurate information sets.
- Bias and reliability:
  Poor data quality can introduce bias, errors, or blind spots into AI-driven decisions, undermining trust and potentially leading to costly mistakes in public sector operations.
Over 80% of government departments experience data silos, leading to inefficiencies in service delivery and complicating cross-agency initiatives.

Building a data management strategy for AI

To unlock the full potential of AI in government, agencies must develop and implement a robust data management strategy. This helps you ensure that data is organized, accessible, and reliable, with key prerequisites for effective AI training, automation, and decision-making.

Data inventory and classification: Know what you have and where it lives
- Conduct a comprehensive data inventory to identify all data assets across departments, systems, and formats.
- Classify data based on sensitivity, usage, and relevance to AI initiatives.
Understanding the data landscape helps agencies prioritize efforts, reduce duplication, and ensure compliance.

Expert Tip: Manually classify early-stage data, and let trusted tools automatically categorize high-volume data sets.

Archiving and retiring legacy data: Freeing up resources and reducing noise
- Identify inactive or obsolete data that no longer needs to be in active systems but must be retained for compliance or historical purposes.
- Archive or retire legacy data to reduce storage costs, improve system performance, and minimize data clutter that can confuse AI models.
- Implement policies for defensible deletion where appropriate to manage the data lifecycle responsibly.
Expert Tip: Some agencies have funded AI initiatives by shifting operating funds from contractors supporting legacy applications after archiving the system data.

Digitizing and integrating paper records for AI-readiness
- Convert paper-based records into digital, searchable formats to make them accessible for AI analysis.
- Integrate digitized records with existing digital data repositories to create a unified data environment.
This step is critical for public sector agencies with extensive paper archives, enabling AI to leverage all available information.

Expert Tip: Do not simply scan paper records into electronic images. Rather, use intelligent capture tools to automatically route the scanned document into workflows or archives, where the data can be readily accessible with no further action.

Continuous data quality monitoring and improvement
- Establish ongoing processes to monitor data quality, accuracy, and completeness.
- Use automated tools and AI-powered data cleansing solutions to detect and correct errors.
- Regularly update data governance policies to adapt to evolving compliance requirements and technological advances.
Government agencies lay the groundwork for AI success by building a comprehensive data management strategy and powering AI initiatives with clean, accessible, well-governed data.

Expert Tip: Establish a data governance board comprised of agency, legal, technology, and mission personnel.

The role of modern content management

Intelligent content management systems help agencies organize, classify, and govern their information, turning “dark data” into actionable insights. These platforms automate data pipelines, ensure compliance, and provide the foundation for AI-driven innovation in government services. Agencies that have adopted AI-powered content management report improved efficiency, better decision-making, and enhanced citizen experiences.

How OpenText can help

Before launching any AI initiative, take a critical look at your agency’s data quality, accessibility, and governance practices. This does not require a thorough assessment from a consulting firm; a simple in-house evaluation can make a major difference. This foundation ensures your AI projects are built on solid ground, maximizing impact, minimizing risk, and setting your organization up for long-term digital success. OpenText Core Content Management is designed to help public sector organizations:
- Inventory and classify data: Centralize information across legacy systems and paper archives, making it searchable and AI-ready.
- Retire and archive legacy data: Move inactive or obsolete records to secure and compliant archives, reducing costs and operational noise.
- Digitize and integrate paper records: Convert paper documents into digital formats, enabling seamless integration with AI and analytics platforms.
- Enforce data governance: Apply robust policies for data quality, security, and compliance, ensuring your data is trustworthy and accessible for AI initiatives.
By partnering with OpenText, your agency can accelerate its journey toward effective AI adoption, confident that your data foundation is secure, compliant, and optimized for innovation. Learn more about how OpenText can support your mission to deliver smarter, safer, and more cost-effective public services.
Keith Nelson

August 11, 2025

Industries, Information Technology, Line of Business, Public Sector

AI in government, Data governance for government AI, government data management strategy, public sector AI challenges
Navigating VMware post-Broadcom
Broadcom’s acquisition of VMware has compelled organizations to critically re-evaluate their hybrid cloud strategies and confront the long-term risks of vendor dependency. Concerns over shifting licensing models, mandatory product bundling, and roadmap changes are not merely operational disruptors. They can significantly increase costs and negatively impact long-term plans, innovation velocity, and competitive standing.

Organizations have been closely evaluating whether staying the course with VMware remains in their best interest, asking themselves How do we ensure a truly agile, resilient, and cost-effective IT foundation for the next decade?

Turning disruption into a modernization strategy

VMware has been a cornerstone for many enterprises for years, still powering over 70% of on-premises virtualized workloads as of 2023, according to IDC’s Worldwide Quarterly Cloud IT Infrastructure Tracker (Q4 2023). While some organizations have decided to stay the course with VMware, others are already transitioning—or planning to—in small or large ways. However, untangling years and even decades of investment requires careful planning. A rushed VMware transition can disrupt operations and cause severe, unexpected system or operational issues. That’s why moving away from VMware should follow a well-governed approach—one that accounts for licensing, dependencies, skill sets, and long-term platform alignment.

But here’s the silver lining: This disruption isn’t just a challenge—it’s an opportunity to modernize IT operations, explore solutions that align with your hybrid infrastructure and vision, and build a more agile, future-ready foundation.

Three strategic pillars for a smooth transition

If you’re looking to reduce your reliance on Broadcom’s VMware, you might consider adopting a platform-agnostic management approach while gradually shifting workloads to alternative infrastructure or cloud environments. Here are three essential pillars to guide you through this transition:
1. Unify your automation and management across hybrid environments
2. Carefully plan a secure workload migration
3. Incorporate intelligent and AI-enhanced technology for improved ongoing IT operations
Why OpenText?

OpenText offers a holistic approach designed to help you navigate these changes:
- An AI-powered IT operations and automation platform that’s ready for your hybrid environment. It helps streamline operations, improve compliance, and optimize IT costs.
- Leading migration services along with expert consulting to support your transition at your own pace.
- Flexible licensing options—including SaaS or on premises, subscription or perpetual, ala carte or bundled solutions—to meet your changing needs.
Our automation platform seamlessly integrates with popular tools like ServiceNow, Ansible, and Terraform, all while managing your VMs, Kubernetes, and bare metal across private and public clouds.

Define your future

VMware’s transformation isn’t just happening to you—it’s a call to action.

For a deeper dive, see this post: Alternatives to VMware: What’s your next move?
Alex Rwankuba

August 8, 2025

IT Operations, Technologies

Automation Center, VMware
DFIR: The unsung hero of cybersecurity
In today’s threat landscape, where cyberattacks are more frequent, complex, and damaging than ever before, many organizations are doubling down on prevention—deploying firewalls, endpoint protection, and threat detection systems. But prevention alone is no longer enough. When an incident inevitably slips through the cracks, the ability to understand, contain, and recover from the cyberattack is crucial. That’s where DFIR—Digital Forensics and Incident Response—comes in.

DFIR is the backbone of an effective cybersecurity program. It provides the tools and methodologies to investigate and analyze cyber incidents, uncover the root cause, collect digital evidence and prevent future breaches. When integrated into a broader security strategy, Digital Forensics and Incident Response (DFIR) transforms a reactive posture into a resilient one.

What is DFIR?

Digital Forensics and Incident Response (DFIR) is a specialized discipline that combines two vital areas of expertise:
- Digital forensics involves the collection, preservation, and analysis of digital evidence. It focuses on reconstructing the actions of attackers (or insiders), identifying the data they accessed or stole, and determining how they penetrated the environment.
- Incident response is the structured approach to identifying, managing, and mitigating cyber threats and breaches. It includes triage, containment, eradication, recovery, and post-incident analysis.
Together, Digital Forensics and Incident Response (DFIR) helps organizations respond quickly and effectively to cybersecurity incidents, minimize damage, and strengthen defenses for the future.

Why DFIR matters more than ever

As attack surfaces expand and threats become more sophisticated, security teams are overwhelmed by an increasing number of alerts and data. Digital Forensics and Incident Response (DFIR) brings clarity to the chaos by helping SOC teams investigate cyberattacks. Here’s how:

1. Understanding the full scope of an attack

When a breach occurs, it’s rarely obvious how deep the compromise goes. Was it one device or the entire network? Did the attackers steal data or just poke around? DFIR helps answer these questions and investigate the cyberattack with precision by reconstructing the attack timeline, identifying the initial access point, tracking lateral movement, and pinpointing exfiltrated data.

2. Minimizing downtime and financial loss

Every second counts during a cyberattack. DFIR accelerates the investigation and containment process, reducing downtime and limiting the attacker’s ability to cause damage. This can mean the difference between a minor incident and a full-blown crisis costing millions in recovery, lost business, and reputational damage.

3. Supporting legal and regulatory compliance

Digital forensics solutions provide crucial evidence for legal proceedings and compliance reporting. Whether it’s demonstrating adherence to GDPR, HIPAA, or industry-specific regulations, DFIR ensures SOC teams collect digital evidence legally and demonstrates due diligence and data handling integrity with a structured response.

4. Hardening security posture

The lessons learned during a Digital Forensics and Incident Response (DFIR) investigation don’t just help with the current incident—they fuel improvements across your entire security stack. Analyzing how the attack occurred and the vulnerabilities attackers exploited is crucial. With this information, your team can proactively patch weaknesses, improve detection rules, and refine response protocols.

DFIR in the real world

What happens if an organization experiences a ransomware attack? A prevention-based system may detect suspicious behavior—but DFIR digs deeper. It determines how the malware entered, what systems were encrypted, and whether the attacker stole data. It also supplies information on how the threat actor moved across the network. This forensic intelligence not only helps recover but also strengthens defenses against future variants of the same threat.

Investigators also use Digital Forensics and Incident Response (DFIR) solutions to investigate insider threats. These are one of the most common yet difficult types of attacks to detect. A 2024 report by Cybersecurity Insiders revealed that 83% of organizations experienced at least one insider attack, and 48% reported an increase in such attacks over the past year

Through deep forensic analysis, security teams can uncover unauthorized data transfers, tampering, or sabotage that may not trigger alerts in traditional monitoring systems.

What you can do to improve your security posture

In the ever-evolving world of cybersecurity, DFIR is not just a technical speciality. It’s a strategic necessity. It empowers organizations to respond swiftly to incidents, limit damage, learn from attacks, and ultimately build a stronger security foundation. While prevention will always be essential, DFIR ensures you’re never blindsided—and never helpless—when an attack does occur.

For organizations serious about cybersecurity, investing in DFIR tools, talent, and processes isn’t optional. It’s mission critical.

Contact us at https://www.opentext.com/products/digital-investigations-and-forensics to learn more about how OpenText can help you build a faster, smarter, and more defensible incident response strategy.
Peri Storey

August 8, 2025

Line of Business, Security, Security, Technologies

DFIR, Digital Forensics and Incident Response, Insider threat
5 Supply chain predictions for 2025

If the past few years have taught us anything, it’s that supply chains aren’t just operational engines, they are strategic levers for growth, resilience, and innovation. In 2025 and 2026, that role only grows more critical. Global pressures persist, but so does the pace of technological change. The companies that adapt fastest will win.

What’s emerging isn’t just a smarter, reinvented supply chain, but one with virtually limitless potential.

So, what’s coming down the line? Heading into 2025, we expect major shifts fueled by AI, real-time data, and sustainability mandates. Here are five shifts that will shape how supply chains operate and how businesses stay competitive in the years ahead.

5 Supply chain trends shaping 2025 and beyond

1. AI moves from helpful assistant to confident operator

AI in supply chain management is advancing rapidly, but it hasn’t replaced human decision-makers yet. Most companies still want people firmly in the loop, especially when the stakes are high.

What’s changing is AI’s role in the conversation? Thanks to more intuitive, explainable models, AI is becoming a more trusted collaborator. It suggests actions, surfaces insights, and guides decisions in real time. The goal isn’t autonomy for its own sake. It’s smarter orchestration between human expertise and machine speed.

OpenText’s Business Network Aviator is a great example in helping supply chains turn AI insights into action. By using large language models to resolve issues proactively and guide users through complex scenarios, it enables a more confident, conversational kind of AI. Not just smarter AI, but truly collaborative AI.

2. Digital twins level up to real-time supply chain ecosystems

Digital twins aren’t just internal simulations anymore. They’re turning into networked systems that enable real-time supply chain visibility , from suppliers to partners to end customers.

These “twin networks” give companies synchronized insight into inventories, order status, and disruptions across the full supply web. The payoff? Faster scenario planning, better risk mitigation, and real-time agility that static dashboards just can’t touch. It’s no surprise that the global digital twin market, valued at USD 17.73 billion in 2024, is expected to grow to USD 259.32 billion by 2032, with a remarkable CAGR of 40.1%, according to Fortune Business Insights.

OpenText’s real-time supply chain insights “form a holistic view of your supply chain and logistics flows and enable improved scenario planning.” In short, it’s good if you can test before things break.

3. Sustainability isn’t optional, and it’s driving smarter models

Climate disclosure is becoming law, not just best practice. With regulations like Scope 3 emissions reporting and the EU’s ESPR tightening, traceability is moving from nice-to-have to must-have.

But it’s not all red tape. These requirements are sparking innovation, especially around circular supply chain models. Think product-as-a-service, remanufacturing, and reverse logistics, all enabled by tools like digital product passports.

As OpenText highlights, digital product passports revolutionize transparency by enabling full lifecycle traceability. Sustainability is evolving from a compliance checkbox to a business advantage.

4. Fragmentation will force smarter, more flexible logistics

Global trade isn’t getting simpler. Geopolitical tensions, regionalization, and climate disruptions are making traditional routes riskier and forcing logistics to get creative.

In response, supply chains are becoming more multi-modal and diversified. AI-powered logistics platforms are helping businesses dynamically replan routes across air, sea, rail, and road, often on the fly.

And strategies like nearshoring and regional sourcing are gaining traction, not just for risk mitigation, but for faster delivery and tighter control.

OpenText supports this shift with solutions that promote resilient supply chains by giving supply chain leaders real-time visibility, data-driven planning tools, and the ability to adapt quickly when conditions change. Supply chain traceability solutions help companies stay ahead of disruptions, and make smarter logistics decisions with confidence.

5. AI won’t replace supply chain talent, it’ll upgrade it

Let’s be clear: AI isn’t coming for your job. But it is changing what your job looks like. As automation scales, new roles are emerging around data fluency, AI oversight, and scenario-based planning. AI isn’t replacing talent; it’s redefining it. From data scientists to scenario planners, tomorrow’s supply chain pros will thrive at the intersection of tech and strategy.

OpenText is helping enable this shift by designing AI tools that enhance human decision-making rather than override it. Their approach focuses on freeing up talent with AI for higher-value work, not replacing it, so organizations can unlock the full potential of both people and technology. That’s the future. Not man versus machine, but better together.

Are you ready for the future of the supply chain?

These shifts aren’t just trends; they’re imperatives. They’re signals of where supply chain strategy is headed. To lead in the next era of supply chain, companies must act now. The companies that thrive will be the ones who lean in early, experiment often, and stay flexible.

Learn how OpenText is helping companies digitize their supply chains and delivering the technologies that will revolutionize supply chains in 2025 and beyond.

Naomi Skinner

August 8, 2025

Business Network, Integration, Line of Business, Supply Chain, Technologies

Digitize Supply Chains
Why OpenText is one of the top EDI vendors of 2025
Electronic Data Interchange (EDI) remains the backbone of business-to-business communication. This comprehensive analysis explores why OpenText stands out in the competitive EDI market and why businesses are increasingly choosing our solutions for critical data exchange needs.

The evolution of EDI solutions in 2025

The EDI landscape has transformed significantly in recent years, with integration capabilities, cloud functionality, and AI-driven analytics becoming more than just luxuries. Today, they are essential features. At OpenText, we’ve not only kept pace with these changes, but we’ve consistently set new standards for the industry.

Key market trends driving EDI adoption in 2025
- API-EDI hybrid ecosystems are becoming standard practice
- Cloud-native architecture is replacing legacy on-premise systems
- AI and machine learning is enhancing document mapping and error detection
- Real-time processing capabilities are reducing transaction delays
- Enhanced security protocols are addressing evolving cyber threats
Why OpenText is a leader in the EDI market in 2025

Whether you’re new to EDI or looking to modernize your existing solution, adopting OpenText’s EDI solutions can transform your business operations, streamline your supply chain, and position you for success in an increasingly digital world.

1. Comprehensive integration capabilities

OpenText operates the world’s largest EDI network and offers a comprehensive suite of B2B/EDI integration solutions. Their platform seamlessly connects with:
- ERP systems (SAP, Oracle NetSuite, Microsoft Dynamics)
- Cloud applications
- IoT devices
- Supply chain management solutions
- Accounting and back-office systems
OpenText provides comprehensive support for document creation, transmission, reception, and management, along with specialized tools for EDI translation and mapping, supporting all major standards such as Tradacoms, ANSI X12, and EDIFACT. This interconnectivity provides customers with a truly unified business ecosystem, eliminating data silos and enabling end-to-end visibility.

2. Cloud-first strategy with flexible deployment options

While many vendors have migrated to the cloud, OpenText has pioneered a cloud-first approach that maintains flexibility for customers with complex requirements:
- OpenText Cloud: Fully managed SaaS EDI solution
- Hybrid deployment options: Balancing cloud benefits with on-premise security requirements
- Multi-cloud support: AWS, Azure, Google Cloud Platform compatibility
- Containerized architecture: Enabling consistent performance across environments
This flexibility allows organizations to implement EDI solutions aligned with their unique cloud strategies.

3. Unmatched global trading partner network

OpenText’s Business Network includes over 1 million trading partners across 175 countries. This extensive network provides:
- Pre-established connections reducing onboarding time
- Industry-specific trading communities for retail, automotive, healthcare, and manufacturing
- Standardized templates for common business processes
- Regulatory compliance across multiple jurisdictions
This established network significantly reduces the time to implement new trading relationships.

4. Advanced security and compliance features

In an era of increasing regulatory requirements and security threats, OpenText has invested heavily in:
- End-to-end encryption for all data in transit and at rest
- Comprehensive audit trails for regulatory compliance
- Adaptive authentication mechanisms preventing unauthorized access
- Continuous monitoring for potential security threats
- Automated compliance updates for global regulations (GDPR, CCPA, etc.)
These security features provide organizations with confidence that their critical business data remains protected.

5. Scalable performance for modern business volumes

OpenText’s infrastructure has been engineered to handle:
- Massive transaction volumes during peak periods
- Complex document types beyond traditional EDI formats
- Real-time processing for time-sensitive business processes
- Predictable performance even during infrastructure maintenance
This scalability ensures businesses can grow without concerns about EDI capabilities becoming a bottleneck.

Why OpenText is a top EDI vendor

OpenText is consistently positioned as a Leader in the IDC MarketScape for Multi-Enterprise Supply Chain Commerce Networks, reflecting its strong market presence and strategic capabilities. This leadership is further demonstrated through measurable success across a diverse range of customers and industries.

Global Retail Chain: Reduced supplier onboarding time from weeks to days while increasing transaction accuracy from 55% to 98%.

Automotive Manufacturer: Achieve highly reliable, agile business operations with OpenText’s EDI VAN solution, supporting just-in-time manufacturing processes across 30 countries.

Healthcare Provider Network: Successfully processed patient orders 50% faster, enabled HIPAA compliant communications, and on-time delivery of medical supplies directly to patients’ homes using OpenText’s healthcare-supported EDI solutions.

OpenText’s EDI solutions for businesses of all sizes

OpenText offers various implementation options to match your specific business needs:

OpenText B2B™ Integration Essentials

Designed specifically for small and medium-sized businesses new to EDI, this solution digitizes and automates B2B document exchange without requiring EDI expertise. It supports major standards and protocols, offers pre-built trading partner maps, and includes features like dashboards, error reporting, advanced packing and inventory workflows, and multi-user collaboration, aimed at accelerating partner onboarding and improving operational efficiency while meeting buyer/vendor compliance requirements.

OpenText™ B2B Integration Foundation

Perfect for both growing mid-market companies and established enterprises, this affordable solution offers a balanced combination of outsourced EDI integration and self-service onboarding tools, prebuilt trading partner kits and ERP adapters (like NetSuite, Dynamics 365, and SAP S/4HANA), as well as rich visibility via dashboards and analytics to automate and simplify partner collaboration. Backed by global support and built for high availability, it reduces integration costs and accelerates digital supply chain transformation.

OpenText™ B2B Integration Enterprise

This enterprise-level solution provides B2B managed services that enable organizations to outsource their entire EDI program while maintaining the capability to exchange diverse EDI transactions with business partners. The platform supports everything from purchase orders and advance shipping notices to invoices and payments, all while minimizing strain on internal resources.

This enterprise-level solution provides a fully managed EDI service that enables organizations to outsource their complex B2B ecosystem needs. It leverages the world’s largest business network and leading B2B integration experts to improve supply chain collaboration, enhance visibility, and streamline day-to-day operations with customers, suppliers, financial institutions, and logistics partners. Designed with security and AI readiness in mind, it helps businesses remain resilient and agile in the face of evolving challenges.

Choose OpenText as your EDI vendor in 2025

While many vendors offer competent EDI solutions, OpenText’s combination of integration depth, global reach, security focus, and proven reliability has established them as the clear market leader for 2025.

Organizations looking to optimize their B2B communications, streamline supply chain operations, and future-proof their digital business exchanges should consider OpenText as their first-choice EDI vendor, whether they’re new to EDI or looking to modernize existing solutions.

For businesses in complex, regulated industries or those with global operations, OpenText’s combination of innovation and stability provides the foundation needed for successful digital transformation initiatives built on reliable data exchange.

Getting started with OpenText EDI solutions

The journey to implementing an enterprise-grade EDI solution begins with a thorough assessment of your organization’s specific requirements and existing systems. OpenText’s consultative approach ensures that implementations align with business objectives while minimizing disruption to ongoing operations.

Want to see for yourself? Try our interactive B2B interactive demo.
Get the Demo
Want to learn more? Contact us.
Naomi Skinner

August 7, 2025

Business Network, Line of Business, Supply Chain, Technologies

Business Network, EDI, supply chain
Catalent boosts speed and quality in drug development and manufacturing

Catalent is one of the world’s largest Contract Development and Manufacturing Organizations (CDMO). We help pharma and biotech companies to develop and produce vital medical treatments. At any given time, we have over 1,000 products in development.

We’re constantly trying to strike a balance between getting products to market quickly and maintaining strict quality and compliance standards. However, our old approach of multiple document management solutions and piles of paper was making this increasingly difficult.

Our people were literally weighed down by paper. For instance, when manufacturing a new batch of drugs, our operators had to print out a 150-page batch record document and haul it from workstation to workstation to capture the information they needed. We knew this approach wasn’t sustainable, so we started looking for a better way.

Creating a single source of truth

After considering many options, we found what we were looking for in OpenText™ Documentum™ Content Management (CM) for Life Sciences. What caught our attention was how well it aligned with our industry’s needs. The Documentum Quality and Manufacturing solution is pre-validated to meet pharmaceutical standards and offered robust controls for auditing.

We also decided that a privately hosted cloud-based platform worked best for our business. We needed to onboard 16,000 users across seven countries. Opting for OpenText™ Private Cloud didn’t just simplify the initial migration, it will make it much easier to keep everyone on the same page and scale services up as we continue to grow. Best of all, OpenText handles the technical side of things, so we can focus on our core mission.

OpenText™ Professional Services mapped our business specific processes and requirements to the solution and configured the environment in a private cloud. Our experience with them has been top notch. They’ve helped us through the journey of going from multiple legacy systems to one of the best Life Sciences industry solutions on the market proven to meet large enterprise needs.

We’ve come such a long way already with OpenText. With OpenText Documentum CM for Life Sciences, we finally have a single source of truth for everything from batch records to standard operating procedures (SOPs).

Finding a better balance

The results speak for themselves. We’ve slashed paper usage by up to 30% across 15 manufacturing sites—that’s a win for both efficiency and the environment.

Most importantly, we’re closer to perfecting the tightrope walk between speed and quality. Our people have access to the most current and approved content at their fingertips. Likewise, standardized workflows mean processes run the same way, every time. It gives us the consistency and confidence to move faster while maintaining impeccable quality standards, so we are ready for Health Authority audits.

At the end of the day, that helps us get life-saving treatments off the production line as quickly and safely as possible—allowing us to make good on our mission to help people live better and healthier lives.

To learn more about our approach to content management, read our case study.
Read the case study

Lindsay Fernandez

August 7, 2025

Cloud, Content Services, Industries, Life Sciences, Line of Business, Operations, Technologies

CDMO, Content management, Documentum CM for Life Sciences, Life sciences, OpenText Documentum, OpenText Private Cloud, pharmaceuticals, Quality and Manufacturing

What is continuous testing?

What is an example of great continuous testing?

Why is it an important topic today?

What role does automation have?

What role does AI have?

Is it related to continuous integration?

How is it different from agile testing?

Deliver quality software

DevOps: Speed meets collaboration

DevSecOps: Security joins the party

DevOps vs DevSecOps: What’s the difference?

Why DevSecOps matters

Can you transition from DevOps to DevSecOps?

Speed is great. Security is better. Both is best.

One platform. Total pipeline control.

Compliance that moves at DevOps speed

Test like its mission-critical (because it is)

Built for the AI era. Proven at enterprise scale

The evolution: From niche to non-negotiable

4 key shifts driven by AI in retail

1. Hyper-personalization and the one-to-one experience

2. Elevated customer experience and service automation

3. Optimized operations and predictive efficiency

4. Resilient and transparent supply chains

The path forward: Navigating the AI imperative

The future of AI and retail

Why data management is crucial to government AI projects

Why AI needs clean, accessible data

Building a data management strategy for AI

Data inventory and classification: Know what you have and where it lives

Archiving and retiring legacy data: Freeing up resources and reducing noise

Digitizing and integrating paper records for AI-readiness

Continuous data quality monitoring and improvement

The role of modern content management

How OpenText can help

Turning disruption into a modernization strategy

Three strategic pillars for a smooth transition

Why OpenText?

Define your future

What is DFIR?

Why DFIR matters more than ever

DFIR in the real world

What you can do to improve your security posture

5 Supply chain trends shaping 2025 and beyond

1. AI moves from helpful assistant to confident operator

2. Digital twins level up to real-time supply chain ecosystems

3. Sustainability isn’t optional, and it’s driving smarter models

4. Fragmentation will force smarter, more flexible logistics

5. AI won’t replace supply chain talent, it’ll upgrade it

The evolution of EDI solutions in 2025

Key market trends driving EDI adoption in 2025

Why OpenText is a leader in the EDI market in 2025

1. Comprehensive integration capabilities

2. Cloud-first strategy with flexible deployment options

3. Unmatched global trading partner network

4. Advanced security and compliance features

5. Scalable performance for modern business volumes

Why OpenText is a top EDI vendor

OpenText’s EDI solutions for businesses of all sizes

Choose OpenText as your EDI vendor in 2025

Getting started with OpenText EDI solutions

Creating a single source of truth

Finding a better balance