SAS world headquarters felt charged with momentum as Jason Mann, VP of IoT, welcomed a room full of curious minds to the 10th annual IoT Slam Live.

“We are in the midst of a technology boom unlike anything we’ve seen before,” Mann said in his opening remarks. “In this environment, the ability to make fast, confident, data-driven decisions isn’t just a competitive advantage – it’s a necessity.”

Virtual and in-person attendees represented a diverse mix of industries and institutions – from startups to academia – all united by a shared interest in cutting-edge topics like AI-powered IoT ecosystems, cybersecurity and digital twins.

Eyes on the horizon

The opening panel, “Driving the Future: How AI and IoT are Powering Smarter Transportation,” tackled a topic practically everyone could relate to: traffic.

Tyson Echentile, SAS Sr. Manager of Business Development, IoT, moderated a lively discussion featuring:

• Katy Salamati, Global Principal Consultant, IoT, SAS
• Kelly Wells, Traveler Information Engineer, NC Department of Transportation
• Elizabeth Young, VP and Deputy Practice Lead, Asset Management and Data Analytics, Halff

Wells highlighted the complexity of managing traffic data across multiple systems, including dash cams, crash reports, speed sensors, and signage. “Geospatial conflation is the single biggest challenge we face,” she said. She also pointed to the promise of autonomous vehicles, which could reduce crashes and fatalities by eliminating simple human errors like blind spots. (Echentile added another advantage: “No tipping required!”)

Young spoke about the potential of digital twins – virtual models of physical infrastructure – to revolutionize traffic planning. “We can design as much as we want, but we need to be able to test different scenarios,” she said, noting the high cost and labor demands of building roads and infrastructure.

Salamati shared a real-world success story from a major UAE city, where SAS is helping to optimize traffic light timing using AI and IoT data. “Our goal was to reduce the number of stops along the corridor and improve flow without disrupting minor streets,” she explained. The result? A 15–20% reduction in congestion between the airport and downtown. She’s also excited about the growing role of AI in multi-modal transportation, especially in enhancing maintenance, safety and the traveler experience.

Inclusion by design

A later panel moderated by Emily Dilday, SAS Principal Business Solutions Manager, IoT Commercial, brought to life a powerful idea from Mann’s opening remarks: “the best insights often come from the most unexpected conversations.”

“If you don’t design for inclusion, you’re automating for exclusion,” said Mahesh Tomar, VP of Engineering at Oracle. He encourages teams to regularly ask, “Whose voice is missing?” and to embrace what he called “the awkward pause” – a deliberate moment of silence in meetings to give quieter voices space to speak. “If these actions are practiced consistently, we will see change,” he said.

Erika Franco, Senior Solutions Architect at Cisco, shared how her upbringing in Latin America during a tumultuous time shaped her approach to problem-solving. “When you feel you are being underestimated, you look for unique conclusions,” she said. “That background made me more resourceful—and it shaped how I work and how I lead.” Franco believes that while policies against bias are important, empathy and support truly unlock people’s potential.

Niyati Doshi, Sr. Program Manager, Global AI and IoT at SAS, highlighted the company’s commitment to responsible innovation. “At SAS, we have AI training to avoid bias and consider how we can make it more trustworthy, fair, and equitable,” she said. Doshi stressed the importance of reinforcing learning – not just in AI and technology, but in team development – to improve how solutions are developed and deployed.

Modeling the future of safety: Inside the SAS Industrial AI Center

IoT Slam guests had the opportunity to step inside the newly unveiled Industrial AI Center at the SAS campus warehouse – a dynamic, real-world environment where innovation meets safety. Bobby Shkolnikov, SAS Principal Business Development Specialist, led them through a short presentation on some of SAS’ work in this area.

This immersive lab has been transformed into a live manufacturing theater, purpose-built to develop, test and refine AI-driven safety models. Designed to reflect the complexity of real industrial settings, the lab showcases how SAS is accelerating the journey from data to value.

Visitors experienced firsthand how configurable geo-fences, multi-angle camera systems, and the authentic, sometimes chaotic nature of a working warehouse come together to simulate real-world scenarios. These simulations replicate the challenges faced by workers around machinery and conveyor belts (and soon to include forklifts), offering a powerful demonstration of how SAS and AI can proactively identify risks and enhance protection.

The Industrial AI Center is a proving ground for the future of workplace safety. By modeling behavior in realistic settings, SAS is helping industries move beyond reactive safety measures to predictive, intelligent solutions that prioritize people.

Powering efficiency through AI

Sacha Fontaine, SAS Principal Industry Consultant, IoT, opened the second day of IoT Slam with a promising session on how AI and analytics are making energy use smarter.

Fontaine highlighted the growing energy challenges facing industries, particularly in manufacturing. “The energy cost has been outpacing inflation. Since 2000, gas prices have quadrupled, and electricity prices have risen by 26%,” Fontaine noted. Today’s manufacturers deal with thin profits, shifting production conditions and scattered data, he added.

The solution? “AI is going to be a must,” Fontaine said. He explains AI-driven energy cost optimization (ECO) as a game-changer, with a faster, cheaper and more adaptable system than traditional methods.

ECO gives manufacturers the insights they’ve been missing through three key tools: the automated explainer, shift explainer and setpoint optimizer. Together, they pinpoint where the biggest energy losses occur, reveal need-to-know patterns and recommend precise settings to operators. As Fontaine describes it: With one “golden shift,” you can get “the biggest bang for your buck.”

And ECO delivers real results, fast. In one standout case, Fontaine shared how a polymer manufacturer leveraged AI-driven optimization to cut energy use by 26% and boost yield by 6% – all in three months. “The data was already there,” Fontaine said. “It’s by bringing that data together beyond what your operator or control system might see that led to this kind of benefit.”

Transforming data interaction with Retrieval-Augmented Generation (RAG)

The final session, “Unlocking Knowledge: RAG For Industrial Intelligence,” led by Craig Foster, SAS Sr. Manager of Business Development, IoT, brought together panelists from SAS, Energective and KMS Technology. Together, they explored the transformative power of Retrieval Augmented Generation (RAG) – a generative AI framework helping industries unlock the full value of their data.

How Retrieval Augmented Generation (RAG) works

Colin Frost, CEO of Energective, shared how RAG analyzes an immense volume of data in the oil and gas industry to drive decision-making. “The amount of discovery you can do to uncover value is powerful,” Frost said, describing how RAG surfaces insights buried in decades-old documents. He highlighted RAG’s role in his company to find economic opportunities, reduce safety risks and replicate successful well designs.

Saurabh Mishra, SAS Director of Product Strategy, IoT, took a closer look at what sets SAS’ RAG approach apart. “It’s really about being able to talk to your data,” he said. The SAS system empowers users to work directly with their information. Mishra described the model’s built-in flexibility and semantic search, so that users can focus on insights, not infrastructure.

“We sometimes get involved in a false sense of security and say, oh well, this data is now trustworthy because this is my company’s data,” said Guy Merritt, Chief Technology Officer of KMS Technology, discussing how to make RAG systems more reliable. He emphasized the need for well-managed internal data and crafting prompts that guide the RAG model to trusted sources. Mishra added that the SAS RAG system uses citations to back every response, building transparency and user confidence.

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