Ingenero is a process technical consultancy firm headquartered in Houston, Texas. Its services range from developing new production processes to ongoing operational improvement services and tools such as building and operating new plants alongside customers.
What was the problem or gap in the market you identified that led to starting Ingenero in 2002?
I began my career in 1988 in Houston where I developed high-tech software for process manufacturing. Our focus was on improving operations, performance, and energy utilization, and I was part of a team that created the first online shift-wise real-time optimizers.
At that time, computing power wasn't advanced, but we managed to achieve online shift-wise real-time optimization and even remote plant monitoring. This, along with my hands-on role running plants later in my career, gave me a unique perspective that could address specific needs in the refining and petrochemical industries.
What has been the most notable sea change you’ve observed since you started deploying digital technology within the chemical industry?
When Ingenero began, we offered remote high-tech support to improve operations, with specialists in Mumbai analyzing data from US plants and providing shift-by-shift feedback.
Over the years, advancements in computational power, reduced costs of data storage, and faster internet communication revolutionized this process. Tasks that once took days or months can now be completed in seconds, enabling widespread adoption of AI, machine learning, and Gen AI technologies.
These developments allowed us to enhance our services significantly. With better tools, we now provide faster, more efficient, and automated solutions to improve industrial operations. Staying on top of these technological advancements has been crucial to our ability to deliver high-impact results for our clients.
What are the main services that Ingenero offers for its customers today?
Ingenero operates through four main divisions. First, our Digital Solutions division focuses on remote analytics and automated end-to-end solutions. This group evolved from our early work in remote support and is now the fastest-growing segment of our company. The second division, Engineering, specializes in process, brownfield and value engineering. Besides designing new plants, we help translate lab-developed technologies to industrial-scale applications and assist in modifying existing plants to improve safety, production, energy efficiency, or emissions.
The third division is Safety, which we’ve been committed to since 2004. We conduct Process safety management compliance reviews, and risk analysis, particularly in US refineries. Lastly, our Sustainability division focuses on initiatives like carbon capture and utilization, besides providing digital safety solutions. We’re partnering with renowned research labs and piloting processes that use saline solutions and bio-catalysts to convert CO₂ into usable chemicals, an innovation we’re optimistic about as we scale up.
Why do safety issues persist in the chemical industry despite advancements in technology?
Safety often lacks attention at the executive level until an incident occurs, fostering complacency in some organizations. Many facilities fail to prioritize safety in the design stage, treating it as secondary to cost considerations. Once a plant operates, changes to its processes frequently overlook the necessary updates to safety systems, which can lead to accidents. Additionally, human error plays a significant role. Standard operating procedures (SOPs) are often not followed due to inadequate training or a lack of urgency. Root cause analyses reveal operator errors that could have been prevented with proper adherence to protocols.
AI-driven models can detect faulty readings from instruments, which are critical in chemical plants where processes occur within pipes and hidden from plain sight. One notable incident involved a faulty liquid level indicator, leading to a catastrophic explosion in Texas City in 2005. AI could have flagged such an issue by analyzing other parameters and providing early alerts. Beyond operational monitoring, technology also addresses human safety. AI systems can detect when workers neglect to wear required protective equipment, immediately triggering alerts. These tools reduce human error, improve compliance, and help prevent accidents.
The last 5-6 years have increasingly focussed on sustainability. Can you share examples of digital transformation leading to improvements in this regard?
We’ve implemented applied AI solutions that span from data analysis to decision-making and action implementation and have helped plants improve energy utilization by identifying inefficiencies in real time. In one case, we reduced emissions by 10-12%, energy use by 5-10%, and increased production by 2-5%, all of which are significant for large-scale manufacturers.
Reliability is another area where AI excels. By identifying early warning signs of potential equipment failures, we prevent costly shutdowns and maintain operational efficiency. These proactive measures not only enhance reliability but also contribute to safer, more sustainable operations.
Which markets are you seeing the most growth in, and how does technology adoption vary globally?
The US leads in developing foundational AI technologies but shows slower adoption rates in the highly mature process industry due to resistance to change. In contrast, the Middle East, with newer facilities and a hunger for advanced technologies, adopts innovations more readily. Asia-Pacific is also eager for technology but faces greater cost pressures, which affects the pace of adoption.
This disparity also often stems from the established infrastructure in the US versus the Middle East’s opportunity to start with modern technologies. Emerging markets, with fewer legacy systems, can leapfrog to cutting-edge solutions more efficiently.
Going into 2025, supply chains are a growing concern for chemical companies. How can digital solutions mitigate disruptions caused by global events?
Rapidly changing markets demand agility, which digital solutions provide. Historically, planning cycles were monthly due to computational and information communication limitations. Today, AI enables “just-in-time” planning, allowing plants to respond to disruptions within days rather than weeks. This agility is crucial, especially when geopolitical events or protectionist policies create sudden shifts.
Technology ensures that companies can adapt quickly, minimizing losses and maintaining efficiency. The ability to reconfigure operations in response to market changes is becoming increasingly vital in the chemicals industry.
