As the energy industry continues facing increasing pressure to improve reliability, reduce operational risk, optimize inspection efficiency, and manage aging infrastructure, digital transformation is rapidly becoming one of the most important drivers shaping the future of asset integrity.
Within this evolving landscape, Ooga Technologies is developing a technology- driven approach focused on integrating AI-enabled inspection tools, cloud-based collaboration, real-time decision infrastructure, and advanced NDT workflows for safety-critical industries.
Leading this vision is Ajay Pasupuleti, whose background combines engineering, digital innovation, and inspection-focused technology development aimed at modernizing how industrial operators manage integrity programs and field inspection data.
In this exclusive interview for the 8th edition of Inspenet Brief, Dr. Ajay Pasupuleti shares his perspective on AI-driven inspection ecosystems, the growing importance of real-time decision-making, and how intelligent digital platforms may redefine the future of mechanical integrity and industrial inspections.
- The industry continues discussing digital transformation, but many inspection workflows remain fragmented and heavily manual. What do you believe is preventing faster modernization across asset integrity programs?
For many organizations, the challenge is not a lack of technology. The challenge is that inspection processes evolved over decades around individual systems, manual workflows, and organizational silos. As a result, data often exists in multiple locations, decisions depend on individual interpretation, and critical information is difficult to access when it is needed most.
Modernization becomes difficult when technology is applied to isolated workflows rather than to the decision-making process itself. Simply digitizing paper forms or moving existing applications into the cloud does not fundamentally change how integrity decisions are made. Real transformation occurs when data, engineering expertise, inspection results, and operational context are connected into a unified environment that supports consistent and traceable decision-making.
At Ooga, we believe modernization accelerates when organizations focus on engineering the systems that support decisions in addition to digitizing activities.
- Ooga Technologies is focused on integrating AI-enabled inspection tools, cloud collaboration, and real-time decision infrastructure. How do these technologies change the way operators approach mechanical integrity and inspection management?
Historically, inspection programs have been organized around collecting data and generating reports. We see the future differently. The objective is not simply to collect information but to transform information into timely, actionable decisions.
By combining cloud-enabled collaboration, AI-assisted analysis, and real-time access to inspection information, operators gain visibility across assets, teams, and locations. Engineers, inspectors, and subject matter experts can collaborate within the same operating environment regardless of geography.
AI further strengthens the process by helping identify patterns, surface anomalies, reduce duplication, and prioritize areas requiring attention. The result is a more connected and responsive integrity program where decisions can be made with greater consistency, confidence, and speed. Ultimately, better decisions reduce the likelihood of incidents, minimize operational disruption, and give organizations greater confidence in how they manage risk.
- Inspection data is becoming increasingly critical for operational decision-making. Why is real-time accessibility and collaboration now so important for safety-critical industries?
In safety-sensitive industries, the value of information is directly tied to how quickly and effectively it can be used. Delays between inspection, analysis, and decision-making can introduce unnecessary risk and reduce the time available to respond appropriately.
Real-time accessibility allows stakeholders to work from the same information at the same time. Engineers, inspectors, reliability teams, and operations personnel no longer need to wait for information to move between disconnected systems or organizational boundaries.
Collaboration is equally important because asset integrity decisions often require expertise from multiple disciplines. When experts can work together in a connected environment, organizations reduce ambiguity, improve consistency, and accelerate the path from evidence to action. Decisions made from inspection data often determine whether an organization can continue operating confidently or whether a potential issue requires immediate attention.
- As industrial assets continue aging, operators face growing pressure to improve reliability while controlling costs. How can AI-driven inspection ecosystems help companies make smarter integrity decisions?
The challenge is not simply collecting more data. Most operators already possess large volumes of inspection and operational information. The challenge is extracting meaningful insights from that information.
As infrastructure continues to age, operators must make increasingly complex decisions that balance reliability, operational continuity, risk, and cost. AI helps organizations identify relationships, trends, and emerging conditions that may not be immediately visible through traditional analysis. It can help prioritize risk, highlight anomalies, identify duplicated efforts, and focus engineering attention where it delivers the greatest value.
When AI operates within a structured decision environment, it becomes a force multiplier for engineering expertise. Rather than replacing human judgment, it enhances the quality and consistency of the information used to support decisions where the cost of getting it wrong can be significant.
- The API Summit strongly emphasizes inspection, NDE, monitoring, and asset integrity. How do you see artificial intelligence reshaping the future of nondestructive testing and inspection technologies over the next decade?
We believe AI will augment the inspection ecosystem rather than replace it.
Over the next decade, AI will improve signal interpretation, automate repetitive analysis, assist with anomaly detection, and help organizations correlate information across multiple data sources. As inspection volumes continue growing, AI will become increasingly valuable in helping experts focus on what matters most.
The most significant impact, however, may not be within the inspection itself. It will be in how inspection results are transformed into decisions. AI will help create systems that learn from outcomes, improve consistency and continuously refine decision pathways over time.
- One of the industry’s biggest challenges is transforming inspection data into actionable intelligence. What role will predictive analytics and intelligent workflows play in reducing operational risk?
Predictive analytics and intelligent workflows help organizations move from reactive responses toward proactive decision-making.
Rather than waiting for reports to be reviewed manually, intelligent workflows can continuously evaluate information against predefined criteria, standards, and risk thresholds. Predictive models can identify emerging trends and provide earlier visibility into conditions requiring attention.
Earlier visibility allows organizations to act while options still exist. The outcome is not simply faster decisions. It is better decisions that are supported by evidence, aligned with engineering requirements, and consistently applied across the organization.
- Remote collaboration and digital inspection platforms are rapidly evolving. How important is connected decision-making in modern inspection environments, especially during critical operations or turnaround events?
Connected decision-making is becoming essential.
During turnaround events, outages, and critical operations, decisions often need to be made quickly while coordinating multiple teams and disciplines. Traditional approaches can create delays because information, expertise, and approvals are distributed across different locations.
Connected environments allow teams to collaborate in real time while maintaining traceability, accountability, and consistency. The ability to rapidly align expertise around a common operating picture can be the difference between a measured response and a rushed decision.
Organizations gain access to the right expertise at the right time while preserving governance and confidence in the decision-making process.
- Many organizations still struggle integrating technology with field execution and engineering teams. What separates companies successfully adopting digital inspection strategies from those still operating reactively?
The organizations that succeed understand that technology alone does not create transformation.
Successful adoption occurs when technology aligns with operational workflows, engineering practices, and business objectives. The most effective organizations focus on solving real operational problems and involve field personnel, inspectors, engineers, and leadership throughout the process.
Organizations that remain reactive often implement isolated tools without addressing how decisions are made. The companies achieving the greatest value are building connected ecosystems where technology supports collaboration, consistency, and execution across the entire integrity lifecycle
- Looking ahead, what is your long-term vision for Ooga Technologies and the future of AI-enabled asset integrity management across the global energy industry?
Our vision is to help transform asset integrity from a collection of disconnected activities into a connected decision ecosystem.
We believe the future will be defined by how effectively organizations convert information into action. Inspection data, engineering expertise, operational context, and AI-enabled insights will increasingly operate within a unified environment that supports consistent, traceable, and scalable decision-making.
The purpose of that transformation is not technology for its own sake. It is helping organizations make better decisions earlier, with greater confidence and accountability.
For Ooga, the goal is to continue building the technology, collaboration models, and decision infrastructure that enable organizations to improve reliability, strengthen operational resilience, and make better decisions at scale.
The organizations that lead the next decade will not be the ones collecting the most data. They will be the ones most effectively converting information into action.
As industrial operators continue to navigate aging infrastructure, rising reliability expectations, and growing operational complexity, the future of asset integrity will increasingly depend on intelligent systems capable of transforming inspection data into faster, more accurate, and more strategic decisions.
The perspectives shared by Ajay Pasupuleti reflect a broader industry transition toward connected, AI-driven inspection ecosystems designed to improve reliability, collaboration, and operational performance across safety- critical industries.
This article was developed by Ajay Pasupuleti of Ooga Technologies and published as part of the eighth edition of Inspenet Brief magazine (July 2026), dedicated to technical content in the energy and industrial sectors.
