Across industries, AI-driven data analytics services is revolutionizing how organizations derive value from their information. From healthcare to finance, logistics to retail, companies are leveraging AI to go beyond static reports—identifying patterns, anticipating trends, and automating decisions in real time. This intelligent approach doesn’t just enhance efficiency; it unlocks entirely new ways to serve customers and optimize operations.

In this blog, we explore how and why AI-driven analytics services has proven to be a game changer for industries.

What makes AI analytics truly transformative is its real-time capability. It continuously ingests and processes streaming data—be it customer clicks on a website, financial transactions, or sensor readings on factory floors—instantly surfacing anomalies, trends, or opportunities. For instance, a fraud detection system can block suspicious activity the moment it’s detected, and a supply chain tool can reroute logistics within seconds of a delay. This immediacy empowers organizations to act not just intelligently—but instantly—where every second counts.

Now, with this evolution, businesses have moved from descriptive to predictive and prescriptive analytics. Instead of asking, “What happened?” companies now ask, “What will happen?” and “What should we do?” AI makes analytics faster, more accurate, and deeply adaptive, powering smarter strategies across industries and unlocking competitive advantages once thought impossible.

Healthcare

In healthcare, AI analytics empowers predictive diagnostics by analyzing medical histories, genetics, and imaging data to anticipate disease risks before symptoms appear. Hospitals use AI to optimize resource allocation—beds, staff, and medical supplies—improving patient flow and reducing wait times. It also plays a critical role in detecting billing anomalies and insurance fraud, safeguarding both patients and providers.

Manufacturing

AI is the brain behind the modern “smart factory,” where machines and sensors constantly stream data to predict equipment failures before they happen—minimizing downtime and maintenance costs. Computer vision systems scan production lines in real time to detect quality defects or deviations, driving consistent output and higher product standards.

Finance

In the fast-paced world of finance, AI crunches vast datasets to assess credit risk, spot fraudulent transactions instantly, and group customers based on behavior for personalized offerings. It’s also revolutionizing trading—machine learning algorithms process market signals, news, and historical trends to inform portfolio strategies and execute trades at optimal moments.

Energy and Utilities

AI analytics enables energy providers to fine-tune grid performance, balancing supply and demand dynamically. Predictive maintenance helps prevent blackouts by alerting teams to aging infrastructure. Additionally, AI tools monitor carbon emissions and energy consumption in real time, supporting regulatory compliance and corporate sustainability goals.

First, the democratization of AI is enabling small and mid-sized businesses to harness tools once exclusive to tech giants. Cloud-based platforms and plug-and-play analytics tools are lowering barriers, allowing businesses with limited resources to tap into powerful insights. For instance, Shopify merchants can now use built-in AI tools for customer segmentation and inventory optimization—capabilities that once required dedicated data science teams.

Second, the growing emphasis on explainable AI is making analytics more transparent and trustworthy. As regulations tighten and ethical concerns rise, businesses are embracing models that offer clear reasoning behind predictions. This shift enhances accountability and helps companies gain stakeholder trust. For example, in financial services, explainable models are helping lenders justify credit decisions, reducing bias and increasing fairness.

Finally, AI is increasingly integrating with other cutting-edge technologies to deliver richer insights and greater automation. The Internet of Things (IoT) fuels real-time analytics by streaming sensor data from devices across industries—think smart meters in energy grids or wearables in healthcare. Blockchain ensures data integrity and traceability in AI workflows, particularly in supply chain analytics. And edge computing allows for AI processing directly on devices, reducing latency—vital for autonomous vehicles or predictive maintenance in remote factories.

Together, these trends signal a future where AI analytics is not only more powerful and pervasive but also more inclusive, ethical, and intertwined with the digital fabric of every industry. Businesses that embrace this evolution won’t just stay competitive—they’ll shape what’s next.

However, this transformation is not without its hurdles. Data privacy and regulatory compliance remain top concerns, especially with standards like GDPR in Europe and HIPAA in healthcare. Organizations must prioritize secure data handling and implement consent-driven data policies. Equally pressing is the challenge of data quality and integration. AI systems are only as good as the data they ingest—fragmented, outdated, or biased datasets can derail outcomes and degrade trust in the insights delivered.

Talent is another bottleneck. There’s a growing skills gap in AI and data science, making it difficult for companies to build or maintain in-house analytics capabilities. Investing in workforce development, reskilling programs, or strategic partnerships with technology providers can bridge this divide.

Beyond these, businesses should also foster a culture of data literacy—ensuring that teams across functions can interpret and apply AI-driven insights effectively. Integration with emerging technologies like IoT or edge computing should be seen not as a complexity but as an opportunity to unlock deeper, real-time intelligence.

Utthunga delivers scalable and ethical AI-driven data analytics services tailored for tomorrow’s industries. We empower businesses to unlock real-time insights, overcome data challenges, and lead with AI powered intelligence. From strategy to execution, we help you stay competitive in a fast-evolving, data-first world.

Ready to transform your analytics journey with AI? Contact us here to get started.

In 2021, the global shipping giant Maersk suffered a massive ransomware attack through the NotPetya malware. Within hours, its entire IT infrastructure—across 130 countries—was crippled, ports stalled, and critical data lost. The breach, which originated from a compromised Ukrainian accounting software, cost the company over $300 million.

Such threats loom over every company irrespective of the domain, scale and the kind of security in place. This is because, today’s digital threat landscape is evolving rapidly, with cybercriminals targeting even the most unsuspecting businesses. Relying solely on fragmented solutions is no longer enough. What’s needed is a holistic strategy that merges robust cybersecurity with smart, proactive IT management. That’s where SOC (Security Operations Center) Services step in—offering continuous monitoring, prevention, and resilience as a complete protection strategy.

In this blog, we discuss how SOC services can help businesses stay ahead of threats, the importance of integrated cybersecurity strategies, and what a complete protection approach looks like today.

SOC (Security Operations Center) services are specialized outsourced services that focus on protecting a company’s digital infrastructure. They go beyond basic IT support, offering end-to-end cybersecurity operations—such as real-time threat monitoring, incident detection and response, vulnerability management, and compliance reporting. Core components like 24/7 surveillance, threat intelligence, automated alerting, and forensic analysis work in tandem to create a secure and responsive cyber defense framework.

In today’s rapidly evolving threat landscape, SOC services play a critical role in safeguarding digital assets. With cyberattacks growing in sophistication and frequency, organizations need more than basic security. SOC services provide centralized visibility, expert analysis, and proactive defense to identify and neutralize threats before they cause damage. This makes SOC an essential layer in building a resilient, compliant, and future-ready cybersecurity posture.

In the case of Maersk, a proactive SOC service setup could have detected vulnerabilities early, applied timely patches, and isolated the threat before it spread—potentially preventing the massive operational shutdown, financial loss, and reputational damage that followed such a large-scale ransomware attack.

The digital threat landscape is no longer just evolving—it’s escalating. Cyberattacks have grown not only in frequency but also in their precision and complexity. What once started as nuisance viruses has now become a battlefield of advanced ransomware, nation-state attacks, and AI-driven exploits. Phishing schemes have become more convincing, using social engineering and deepfakes to bypass even well-trained users. Ransomware, as seen in the Maersk incident, can now paralyze global operations within hours. Insider threats, both malicious and accidental, continue to rise, amplified by remote work and increasingly distributed networks.

What makes the risk graver today is that future threats may exploit technologies we haven’t fully secured—such as quantum computing, which could render current encryption obsolete, or AI-based attacks capable of learning and adapting faster than human defenders. We’re entering an era where we may face zero-day threats with no immediate solutions. In this environment, weak security isn’t just risky—it’s catastrophic.

The solution lies in shifting towards proactive security management, and SOC services offer the most effective path forward. When security is managed proactively and holistically, businesses are not just protected—they’re resilient. In an age where tomorrow’s threats may be unknown and even unstoppable by conventional means, SOC services act as your frontline defense and long-term safeguard. For organizations seeking to grow securely and sustainably, embracing this model isn’t just smart—it’s essential.

In the face of today’s escalating cyber threats, SOC services are built on five strategic pillars critical to modern cyber defense: Real-Time Threat Monitoring and Incident Response, Continuous Vulnerability Management, Security Policy Enforcement, Threat Intelligence–Driven Recovery Planning, and User Behavior Monitoring and Training. These components work together to form a centralized, always-on security command hub that detects, analyzes, and neutralizes threats in real time.

The 2021 Maersk ransomware attack is a powerful example of what can happen in the absence of such integrated security operations. When NotPetya struck, it spread uncontrollably across Maersk’s global IT environment. With a SOC in place, real-time monitoring tools could have immediately flagged the anomalous activity, triggering an instant response to isolate affected systems. A proactive vulnerability management process would have identified and patched the flaw in the Ukrainian accounting software before exploitation. Policy enforcement and access controls managed by the SOC could have restricted the malware’s lateral movement.

Moreover, SOC-driven disaster recovery playbooks—backed by real-time alerts and forensic data—would have enabled faster, more coordinated system restoration. Employee awareness training, guided by SOC-generated insights into phishing trends and user behavior, could have also helped detect the intrusion earlier. In short, SOC services wouldn’t just have minimized the impact—they could have altered the trajectory of the attack entirely.

To build true resilience, companies must shift from a patchwork defense to a complete cybersecurity protection strategy—and SOC Services are at the core of this transformation.

SOC Services offer more than just IT support; they provide a strategic partnership to continually monitor, optimize, and secure an organization’s digital ecosystem. A comprehensive security strategy begins with real-time threat monitoring and incident response, where Managed IT Service (MITS) providers use advanced tools like SIEM (Security Information and Event Management), AI-driven analytics, and behavioral detection to identify and respond to threats as they emerge. This proactive surveillance is crucial, especially in cases like the Maersk ransomware attack, where early detection could have prevented network-wide compromise.

Another pillar is vulnerability management and patching. Cybercriminals often exploit known software flaws that remain unpatched. SOC service providers ensure routine scans, patch deployment, and compliance checks are performed without delay—minimizing the attack surface. For instance, the infamous Equifax breach, which compromised the data of over 147 million individuals, was linked to a missed Apache Struts patch. A robust MITS framework would have flagged and closed that gap promptly.

Security policy enforcement is equally critical. Managed IT partners help define and implement access controls, password policies, multi-factor authentication, and encryption standards—creating a consistent security baseline. These policies are regularly audited and updated in response to evolving regulations and threat patterns. When coupled with employee cybersecurity training, this fosters a culture of security awareness. Considering that over 90% of breaches begin with human error, training employees to recognize phishing, suspicious links, or poor data handling practices can significantly reduce exposure.

A complete protection strategy also accounts for the “when,” not just the “if.” This is where backup and disaster recovery services come in. SOC Security Services ensure that critical data is backed up securely—both on-premises and in the cloud—and that a tested disaster recovery plan is in place. In the event of a ransomware attack or hardware failure, businesses can swiftly restore operations with minimal disruption. During the 2022 Colonial Pipeline cyberattack, it was their preparedness and system redundancies that enabled quick recovery after a major ransomware hit.

Finally, the scalability and expertise of Managed IT Services allow companies to keep pace with emerging threats without the burden of building large internal security teams. As threat actors continue to innovate, so must defenses—and MITS offer the agility and specialization needed to stay ahead.

Crafting a complete cybersecurity protection strategy comes through expertise, exposure, and experience. That’s why choosing the right Managed IT Services partner is key to preparing your business for future challenges. In an ever-evolving digital landscape, where new threats and technologies emerge constantly, your IT partner must do more than manage systems—they must help you anticipate change.

A provider with broad industry exposure and deep technical expertise brings valuable insight, enabling your business to adapt swiftly and strategically. From building a scalable, secure IT infrastructure to proactively managing cyber risks, the right partner aligns technology with your long-term vision. Their ability to deliver real-time threat monitoring, compliance support, and tailored innovation helps ensure your organization is resilient, agile, and future-ready. In essence, a strong Managed IT Services partner becomes more than just a vendor—they become a trusted advisor, equipping your business to face tomorrow’s challenges with confidence and clarity.

At Utthunga, cybersecurity is at the core of our Managed IT Services. Our integrated Security Operations Center (SOC) services are customized to ensure your digital infrastructure remains secure, compliant, and resilient. These SOC capabilities are seamlessly woven into our broader managed IT framework, combining proactive protection with operational excellence.

With deep experience across industries such as manufacturing, industrial automation, pharma, healthcare, energy, and utilities, we provide tailored, end-to-end protection that evolves with today’s dynamic threat landscape.

Talk to our experts to discover how our SOC services can strengthen your cybersecurity while optimizing IT performance.

In today’s heavily regulated business landscape, staying compliant is no longer just a requirement—it’s a strategic priority. Organizations face mounting pressure to meet evolving standards while maintaining operational efficiency. This is where Quality Management Solutions (QMS) serve as a strategic enabler. By automating workflows, centralizing documentation, and ensuring real-time visibility, QMS tools help organizations stay ahead of compliance demands. A well-implemented QMS not only improves quality but also significantly simplifies and streamlines compliance—turning a complex burden into a manageable, efficient process.

This blog explains how a well-defined QMS process solutions help industries streamline regulatory compliance.

Despite varying by sector, compliance requirements often share common burdens. These include maintaining up-to-date documentation, capturing detailed audit trails, managing non-conformances and corrective actions (CAPA), and proactively identifying risks. Compliance teams must not only implement these measures but also demonstrate them during audits—adding layers of administrative complexity.

The cost of non-compliance or gaps in compliance can be significant. Penalties, product recalls, operational shutdowns, and legal action are tangible risks. Just as critical is the reputational damage, which can erode customer trust and stakeholder confidence. For these reasons, organizations are turning to digital solutions that not only maintain compliance but embed it into daily operations—transforming it from a burden into a value driver.

Quality Management Solutions (QMS) have evolved from manual, paper-based systems to intelligent, cloud-based platforms. Today’s QMS integrates automation, real-time analytics, and AI to streamline quality processes, enhance compliance, and enable proactive decision-making—transforming quality management from a reactive function into a strategic, data-driven advantage across the enterprise.

Thanks to these advanced capabilities, critical compliance requirements—such as document control, CAPA (Corrective and Preventive Action), audit management, training and competency tracking, and risk management—have become significantly more manageable. These modules work together to provide end-to-end visibility and control across all quality-related activities, from handling non-conformances to maintaining compliance documentation.

Equally important is choosing a vendor that provides ongoing support and regular updates in response to regulatory changes. This ensures your system remains compliant without requiring major overhauls. A well-chosen quality management solution not only simplifies compliance but also future-proofs your organization against evolving quality and regulatory demands.

Click here to know more about our services.

Industrial software engineering is becoming increasingly complex due to the demands of automation, connectivity, and real-time data processing. In this landscape, Low-Code/No-Code (LCNC) platforms have emerged as transformative tools that allow users to build applications with minimal or no coding. These platforms align perfectly with Industry 4.0 and digital transformation goals, accelerating innovation while reducing development bottlenecks. By enabling “citizen developers” — professionals without traditional programming backgrounds — to contribute, LCNC democratizes software creation and offers a faster route to solving industrial challenges. This blog explores how LCNC platforms are redefining industrial software development and whether they hold the key to faster, smarter digital transformation.

Low-Code platforms allow users to develop applications using minimal hand-coding, while No-Code platforms enable complete application creation through visual tools alone. Both empower teams to build solutions quickly but differ slightly in user skill requirements—Low-Code suits developers looking to accelerate delivery, while No-Code targets non-technical users.

• Reusable Components: Prebuilt modules reduce redundancy and coding effort.

• Drag-and-Drop Interfaces: Intuitive design environments for building UIs and workflows.

• Visual Modeling: Logical flows and data structures can be mapped visually, reducing complexity.

• Built-in Integrations: Seamless connectivity with ERP, MES, IoT platforms, and cloud services.

While full-stack development requires deep programming knowledge, LCNC platforms reduce the learning curve and time-to-market, enabling rapid prototyping and deployment without extensive IT involvement. While full-stack development like building custom furniture with raw materials and tools—it offers maximum control but requires time, skill, and effort, LCNC platforms are like assembling IKEA furniture: faster, guided, and accessible even to non-experts.

Did You Know

Organizations using low-code platforms report up to 70% faster development cycles compared to traditional methods.

— Forrester Research

Traditional software engineering in industrial environments often involves long development cycles, heavy coding, and deep integration efforts. LCNC platforms, however, offer a compelling alternative by addressing key operational challenges:

• Speed: LCNC enables the rapid development and deployment of custom applications—ideal for real-time decision-making, quick fixes on the shop floor, or launching pilot projects without months of lead time.

• Agility: Industrial operations frequently face shifting compliance requirements, production demands, or supply chain disruptions. LCNC platforms allow businesses to pivot fast by modifying workflows or interfaces without overhauling entire systems.

• Cost-Efficiency: By reducing the need for large development teams and minimizing time spent on custom coding, LCNC significantly lowers development overhead and helps clear IT backlogs.

• Shortage of Skilled Developers: With a growing gap in available software engineers, LCNC platforms empower OT engineers, process experts, and citizen developers to create their own tools—bridging the talent gap and decentralizing innovation.

• Integration: Modern LCNC platforms offer built-in connectors for seamless integration with existing MES, ERP, SCADA, and IIoT systems—ensuring that new applications enhance, rather than disrupt, the digital ecosystem.

In essence, LCNC is transforming software engineering in industrial settings from a bottleneck into a business enabler. The next section will explore how these platforms are being used in real-world industrial scenarios and the measurable benefits they’re delivering.

Did You Know

By 2026, 80% of low-code users will be non-IT professionals — Gartner

Low-Code/No-Code platforms are revolutionizing industrial software engineering by enabling faster, more adaptive solutions across various use cases:

• Rapid Prototyping for New Machines or Production LinesLCNC tools allow quick app creation to test and validate new production workflows or machine interfaces. These apps can also integrate with digital twins to simulate and refine processes before full implementation.

• Streamlining Maintenance and Service WorkflowsIndustrial teams can build tailored mobile apps for field technicians to manage maintenance logs, access remote diagnostics, and report issues in real-time—vital for smart factory efficiency.

• Compliance and Quality Tracking DashboardsOrganizations can create intuitive dashboards to track compliance with ISO, GMP, and OSHA standards. Role-based access ensures that only the right personnel manage or view critical quality data.

• Legacy System ExtensionInstead of replacing outdated systems, LCNC platforms enable modern UI layers and API-driven integrations that enhance functionality—without the cost and risk of full system rebuilds.

Did You Know

75% of large enterprises will be using at least four low-code tools by 2026.
— Gartner

Low-Code/No-Code platforms offer significant business and technical advantages, making them a strategic asset in modern industrial software engineering.

Together, these benefits make LCNC a game-changer for scalable, agile industrial innovation.

The future of Low-Code/No-Code in industrial software engineering is promising, with advancements that will deepen its impact and reach.

• AI/ML Integration: LCNC platforms will increasingly leverage artificial intelligence and machine learning to auto-generate smarter, context-aware applications.

• Stronger Industrial Connectors: Support for protocols like OPC UA, MQTT, and Modbus will improve, enabling seamless integration with shop floor systems and IIoT devices.

• Hybrid Development Models: Expect a rise in environments that blend LCNC with traditional coding—offering flexibility for both citizen developers and professional engineers.

• Unified IT-OT Platforms: LCNC will play a key role in IT-OT convergence, allowing cross-functional teams to build, deploy, and manage solutions from a single platform.

• Mainstream Citizen Developer Programs: Enterprises are formalizing LCNC adoption with structured training and governance, making citizen development a core part of digital transformation.

This evolution positions LCNC as a long-term strategic enabler.

As industries increasingly adopt Low-Code/No-Code solutions to accelerate digital transformation, the right technology partner becomes critical. Utthunga, with its deep expertise in industrial software engineering and system integration, plays a pivotal role in enabling successful LCNC adoption across complex industrial environments.

Expert Services in Software Engineering & System Integration
Utthunga delivers end‑to‑end software engineering, including application development, middleware, and IIoT system integration—backed by deep experience in industrial-grade solutions.

OT/IT Interoperability & IIoT Expertise
Leveraging a strong track record in OT/IT convergence, edge computing, industrial protocols (OPC‑UA, MQTT), and IIoT, Utthunga’s teams build seamless, high‑performance integrations.

Secure, Scalable LCNC Architecture
Utthunga architects LCNC‑based solutions with robust security (ZTA, SIEM, DevSecOps) and modular design—ensuring scalability and compliance with industrial standards.

Industry‑Tailored Case Experience
With proven solutions like IIoT accelerators (Javelin), device integration stacks, and CMMS/mobile maintenance apps, Utthunga has empowered manufacturers to deploy LCNC applications rapidly and efficiently

By combining software engineering rigor with domain‑specific knowledge and cutting‑edge integration services, we position industrial firms to succeed with low‑code transformation.

Looking to simplify software delivery across your industrial operations? Explore our software engineering services.

In an era where every organization—from startups to Fortune 500 companies—is pledging climate commitments, the reality of meeting net-zero goals still feels elusive. Only 18% of companies are on track to hit their 2050 targets, according to a recent Accenture report. So, what’s missing?

In this insightful discussion, Mr. Majunath Rao, Director, Utthunga, and Dr. Shankar, Co-founder & Director, GyanData Pvt. Ltd. sat down to unpack how engineering can create scalable, sustainable impact across industries. Here’s a seamless Q&A-style recap that dives deep into challenges, practical solutions, and industry use cases.

Mr. Manjunath Rao, Director, Utthunga

The common perception that “energy” refers only to electrical energy is inaccurate. In reality, electrical energy accounts for just 8% of the total energy usage. It’s important to distinguish between the different contributors that make up electrical energy.

Beyond electricity, there are various forms of energy such as thermal energy, hydraulic (water) energy, and internal energy. Each of these plays a significant role in the broader energy system, especially in industries like oil and gas, petrochemicals, and chemicals.

The oil and gas sector is highly mature in terms of energy management. These industries not only generate energy but are also accountable for how it is consumed. They are experienced in collecting data and optimizing energy use efficiently.

In contrast, the petrochemical sector represents a medium level of investment in energy conservation and management practices. The chemical industry, however, faces greater challenges. It is highly fragmented, consisting of many small sectors, which makes implementing uniform energy practices more difficult.

To address this, Utthunga is developing a simplified and accessible energy management approach tailored for the chemical sector, helping them manage energy more effectively with minimal complexity.

It’s important to note that we do not physically shift energy from one place to another. Utthunga’s primary goal is to decarbonize energy systems, which means replacing fossil fuel-based energy with renewable and alternative energy sources. This is essential because, regardless of the form energy takes, the carbon footprint remains unless the source changes.

Energy management should be approached systematically. While many claim to manage energy, in practice, their efforts often stop at basic measures like installing LED bulbs. Our approach goes much deeper — we focus on comprehensive energy conservation across all energy types.

Utthunga’s core strategy begins with an energy audit, which we divide into four distinct phases to ensure thorough and actionable insights.

We break energy down into four phases to provide an actionable roadmap. These include:

1. Data Collection: Gathering relevant data about energy use in the plant or facility.

2. Baselining and Benchmarking: Analyzing equipment efficiency, often comparing older assets like 30–40-year-old compressors with current industry standards.

3. Finding Opportunities: Using simulations and scientific methods, we identify where energy can be saved—whether by tweaking processes or optimizing utilities.

4. Implementation Roadmap and ROI Analysis: Building a clear plan showing investments needed, expected savings, and return on investment (ROI), which is crucial for decision-making.

Mr. Manjunath

During a visit to a petrochemical plant, Utthunga discovered that the plant was incurring a monthly energy loss of ₹1.78 crore. This revelation served as a major eye-opener for the management.

They promptly reached out to us for support, and we carried out a comprehensive energy audit. One of our key findings was that their largest thermic heater was operating at just 18% of its actual capacity. While the company believed the heater’s efficiency to be 88%, our assessment revealed it was only 55%.

In addition, we noticed that chillers and water monitoring systems were poorly managed, contributing to further inefficiencies.

Over a two-week audit period, Utthunga developed and delivered a solution with a return on investment (ROI) within 12 months. Our intervention included process optimization, such as reducing batch reaction times by 10% to 15%, resulting in significant performance gains.

Utthunga also benchmarked their equipment against industry standards. Some of their machines were decades old, creating a substantial performance gap when compared to modern industry best practices.

Mr. Manjunath

Everything Begins with Plant Design

The foundation of sustainability in any industrial setup lies in its plant design. This is where the seeds of long-term efficiency and sustainability are sown. It’s not about building a large facility and then operating it at a reduced scale — rather, designing a plant that is fit-for-purpose is what truly matters.

Design Stage: The Ideal Moment for Sustainability Planning

Maximum sustainability value can be achieved during the design phase. Unfortunately, many companies wait until after construction to conduct an energy or sustainability audit — by then, significant investments have already been made, and the opportunity to embed sustainable practices from the start is lost.

This critical planning falls under basic engineering, which then transitions into detailed engineering and construction. This stage demands maximum attention, as any oversight here can lead to long-term inefficiencies and missed sustainability goals across the plant’s lifecycle.

Operations: The Heart of Sustainability

Once the plant is operational, the operations phase plays a massive role — contributing nearly 60% to 70% of a facility’s overall sustainability. This includes factors such as:

• Energy use
• Waste recovery
• Environmental impact

Operational inefficiencies such as poorly configured control valves, ineffective process logic, unnecessary shutdowns, and frequent startups all add up, negatively affecting both performance and sustainability.

Maintenance: A Key Driver for Sustainable Plant Life

Maintenance practices are equally vital. Today, with the rise of predictive and prescriptive maintenance, we can anticipate equipment failures and arrange necessary logistics in

advance, significantly reducing unplanned downtime and increasing operational efficiency.

The Digital Edge in Sustainable Engineering

With the advent of digitization, the scope and effectiveness of sustainable engineering have grown exponentially. Digital tools and data analytics now enable better decision-making, smarter maintenance strategies, and optimized resource use throughout a plant’s lifecycle.

Dr. Shankar, Co-founder & Director, GyanData Pvt. Ltd.

Process Design Changes Offer the Highest Gains

One of the most impactful ways to improve energy efficiency is through changes in process design. This may involve rerouting pipelines, adding a few heat exchangers, or making other system-level adjustments. While these modifications do require some investment, the payback period is typically between 6 months and 1 year. The energy savings, especially in thermal energy consumption, can be significant — ranging from 10% to 30%.

Shifting Focus: Thermal and Electrical Energy Utilization

Over the past 5 to 10 years, the industry’s focus has expanded beyond just thermal energy to include a more integrated view of both thermal and electrical energy usage. The challenge now is: how can we optimize combined energy consumption within a process?

In chemical processes, approximately 80% of energy consumption is thermal, while the remaining 20% is electrical. This presents an opportunity: if a portion of thermal energy usage can be shifted to electrical energy — in a cost-effective way — we can replicate the energy transition seen in the automotive industry, where internal combustion engines are being replaced by battery-powered electric vehicles.

Partial Shift Toward Electrification

While it’s not feasible to fully shift a chemical process from thermal to electrical energy, a partial transition is possible. If the electrical energy is sourced from renewables, this shift becomes not only technically viable but also sustainable and economical.

Evolving Tools: Modified Pinch Technology

To support this integrated approach, Pinch Technology — traditionally used for optimizing thermal energy — is now being adapted to also consider electrical energy. This evolution allows for more comprehensive energy integration strategies, enabling industries to maximize efficiency across both thermal and electrical domains.

Example:

A power plant boiler where hot flue gas exits containing leftover heat. Instead of wasting it, we transfer this heat to two places: the air used for combustion and the water fed into the steam tubes. You have two choices:

• Heat the air first, then the water, or
• Heat the water first, then the air.

It’s due to thermodynamics—heat transfer depends on temperature differences between streams, not just flow. So, if you heat the water first when the flue gas is hottest, you get more heat recovery. This subtle change in configuration can significantly reduce thermal energy consumption.

This approach is broadly applicable to any plant where heat recovery matters. By reviewing existing heat exchanger setups, plants can often identify simple configuration changes that yield significant energy savings. Tools like pinch technology help formalize this analysis, identifying where savings are possible, estimating costs, and calculating payback times.

Example:

In vapor recompression technology, the vapor leaving the top is compressed to raise its temperature, then used to supply heat at the bottom. This heat integration reduces the external heat needed.

Does Compressing Vapor Mean Using More Electricity

Yes, but this is a trade-off—sacrificing some electrical energy to save a larger amount of thermal energy. Given the increasing availability of renewable electricity, this approach improves both cost-effectiveness and sustainability.

Common Use of Vapor Recompression Technology

Vapor recompression technology is used in over 20 distillation processes involving close boiling mixtures, such as:

• Splitting C2 (ethylene/ethane) and C3 (propylene/propane) streams in refining and petrochemicals
• Methanol-water separation
• Benzene-toluene separation

Evaluating the Economic Viability of Using Such Technology

Using pinch analysis and simulation tools, engineers estimate energy savings, electrical power needs, investment costs (like compressors), and calculate payback periods, often around 6 months, ensuring decisions are financially sound.

Which Chemical processes are Prime Candidates for Electrification now?

These include processes involving low temperatures and high pressures, such as:

• Energy liquefaction
• Air separation
• Liquid air energy storage

These processes can realize significant cost and carbon savings today by integrating electrical technologies.

What Should the Chemical Industry do Right Now?

The industry shouldn’t wait for 100% renewable electricity. It can start by:

• Optimizing thermal systems through pinch analysis
• Selectively shifting from thermal to electrical energy use
• Implementing technologies like vapor recompression

These steps reduce costs, cut emissions, and position companies well for a renewable-powered future.

This webinar highlighted how smart process design and technologies like pinch analysis and vapor recompression can significantly cut energy use and costs in the chemical industry. Even simple changes can yield big savings, while electrification offers a path toward greater sustainability today.

For a deeper dive, watch the full webinar here

Feel free to share your questions or connect with us on LinkedIn!

Cyberattacks targeting OT environments have surged sharply. Recent data shows that 73% of organizations reported intrusions affecting OT systems in 2024, up from 49% just a year before. What’s more concerning is the rise of AI-enhanced attacks—threats that leverage automation and machine learning to carry out operations faster and on a larger scale. These AI-powered attacks now cut the time needed to deploy sophisticated ransomware from hours down to mere minutes.

Traditional cybersecurity strategies are struggling to keep up, especially given the unique challenges OT environments face—outdated equipment, limited patching options, and the need to avoid operational downtime at all costs. Against this backdrop, AI-driven threat detection has become a crucial pillar of modern OT security.

• Reduced Alert Fatigue: AI filters out false alarms and focuses attention on genuine threats. For example, Siemens Energy reported a 40% drop in false alerts after deploying AI-based detection.

• Faster Threat Detection: In mature environments, AI has cut average breach detection times from over 200 days to under 40, giving teams a crucial time advantage.

• Augmented Human Expertise: Automating routine investigations and triage lets security staff focus on strategic tasks. Some manufacturing clients have seen a 25% reduction in incident management time after introducing AI tools.

Across industries like manufacturing, energy, utilities, and logistics, organizations are quietly but steadily adopting AI-driven OT security solutions. Drawing from both our client work and wider industry observations, here’s how AI is being used effectively to secure OT environments in critical sectors:

• At a major European logistics hub, an AI system correlates data from OT equipment—such as crane controllers and fuel systems—with IT security signals. This enables the security team to significantly reduce investigation times and proactively block credential misuse attempts before they escalate into operational disruptions.

• A large utility provider in the Middle East uses passive network monitoring powered by AI to safeguard legacy SCADA systems that cannot be patched. We’ve supported a similar client in deploying this approach, achieving near real-time threat detection across hundreds of substations while keeping systems online.

• In North America, one manufacturer’s AI-driven analytics flagged an unusual pattern in robotic arm movements—not as a mechanical error, but a possible cyber manipulation. Several of our manufacturing clients have since adopted similar AI capabilities to deepen their visibility and response.

• Organizations operating under European NIS2 and GCC’s NCA and NDMO frameworks are increasingly turning to AI not only to enhance security but also to meet regulatory expectations and lower cyber insurance costs.

But putting AI to work in OT isn’t just about adopting new technology. It’s about knowing where it fits, how it behaves around legacy systems, and what risks actually matter on the plant floor or control room.

That’s where Utthunga’s cybersecurity solutions make a real difference. Working with leading industrial clients, we deliver AI-powered threat detection capabilities built specifically for complex OT environments. From passive monitoring of legacy systems to intelligent threat correlation across IT and OT, our cybersecurity solutions are helping organizations stay a step ahead of threats while keeping operations secure and resilient.