Vantiq founder and CEO Marty Sprinzen opens the summit with a candid read on where AI actually stands — what it does well today, what is being oversold, and what separates organizations running AI in production from those still cycling through pilots. He closes on the question the rest of the summit is built around: which problems are worth solving first, and what it really takes to put a system in front of real people and real consequences.

In the first hours and days of life, a newborn’s condition can change in the blink of an eye — a shift so subtle that even experienced clinicians can miss it until it becomes an emergency. This session tells the story of how artificial intelligence is being brought into the NICU not to replace the instincts of nurses and doctors, but to give them something they’ve never had before: a quiet, ever-watchful partner that notices the small warning signs before they become crises. Drawing on real use cases, we’ll explore how connecting the scattered signals in a newborn’s care — heart rate, oxygen levels, breathing patterns, and clinical notes — into one intelligent system can mean the difference between a close call and a tragedy.

This is ultimately a story about time — the minutes that matter most when a baby’s life is at risk — and about giving that time back to the people fighting to save it. We’ll share how this approach has helped care teams move from reacting to crises to anticipating them, turning overwhelming streams of information into clear, trustworthy guidance at the bedside. Attendees will come away with a human understanding of what’s possible when technology is built around the people it’s meant to serve, and why this work — protecting the most vulnerable patients at the most vulnerable moment of their lives — represents one of the most meaningful applications of AI today.

Each year the Hajj brings more than two million pilgrims through a confined environment where crowd density, environmental conditions, EMS, hospital capacity and disease surveillance all shift continuously. Dr. Hisham Ali Dinar of the Kingdom of Saudi Arabia’s Ministry of Health sets out how AI is being applied across the full health emergency management cycle, the work underway with Vantiq to connect it to live data, systems and responders, and the questions that decide whether it works when seconds matter: who validates a recommendation, and who acts on it.

Border operations generate more signal than any team can watch: sensors, cameras, vehicle and vessel movements, personnel reports and intelligence feeds, spread across agencies that rarely share a single picture. Seeing what is happening is only half the problem; acting on it in time is the other.

This session looks at what it takes to move from situational awareness to coordinated action across contested borders — how disparate sensing is fused into one operating picture, and how that picture drives a response across the organizations that have to carry it out.

Cities run some of the most demanding operational systems anywhere — mobility, utilities, emergency response, permitting, public space management — under fixed budgets, election cycles and full public scrutiny. A growing number are now moving AI out of pilots and into daily service delivery, and the ones that succeed share a recognizable set of success factors.

This panel brings together city leaders who have put AI into production and the advisors who have spent decades helping them do it. Together they set out what separates a deployment that lasts from one that dies with the budget cycle: how cities choose, fund and procure the problems they use AI to solve; why the ones that succeed treat data as civic infrastructure rather than a project asset; how political and institutional support is built so a system survives a change of administration; and how impact is measured in terms a council, a regulator and a resident will each accept.

As AI expands beyond digital systems into the physical world, organizations need to connect real-time data, AI, devices, and operational systems to turn information into timely and meaningful actions. This session presents three examples of how Vantiq enables real-time, event-driven operations.

The first is a Physical AI use case integrating Vantiq with a quadruped robot and heterogeneous operational systems. Sensor and camera data from the robot are analyzed by AI, while Vantiq processes real-time events and orchestrates task, movement, and inspection commands across robots, connected devices, and external systems.

The second introduces a real-time tunnel safety monitoring concept that integrates heterogeneous sensor and system data to detect abnormal conditions and support faster operational responses.

The third presents a digital care use case that combines user context with disaster and environmental data to identify individuals at risk in real time and support timely response.
Together, these examples demonstrate how Vantiq can connect data, AI, physical systems, and people through real-time event-driven orchestration, enabling more intelligent, responsive, and safer operations.

Violence usually announces itself before it happens. The language shifts first — in a thread, a post, an exchange between people who know each other — and the people closest to a community can often hear it coming. What they have lacked is a way to catch it at any scale.

Partnering with Vantiq, the Crime Commission is developing a threat assessment tool that draws on psycholinguistic and sociolinguistic research to identify the patterns that precede violent incidents, and puts what it finds in the hands of community violence interrupters who can step in before planning turns into action. The intervention is deliberately not prosecution: the aim is to reach someone early enough to change their course, without building a case against them.

In this session from Richard Aborn of the Citizens Crime Commission of New York City, hear what community-led violence prevention makes possible, and why the same signals that could build a surveillance apparatus can instead be used to build community-driven support.

Korea’s AI market is at an inflection point. Enterprise AX initiatives are moving rapidly beyond pilots into production, reinforced by the Korean government’s substantial investment in AI as a number one national strategy. This session explores the pain points enterprises face along the way: fragmented tools, integration complexity, and the gap between AI experiments and real business outcomes.

We then introduce DAOL Fusion, an all-in-one AI platform built to close that gap, demonstrated through proven customer use cases in manufacturing, engineering, education, finance and the public sector.

Finally, we share how our partnership with Vantiq — combining real-time, event-driven intelligence with DAOL Fusion’s platform capabilities — is expanding the DAOL Fusion ecosystem and opening new paths for joint business growth across markets.

As AI agents increasingly discover, evaluate, and transact on behalf of consumers, the rules of retail and consumer products competition are being rewritten. The brands and retailers who wait to respond risk becoming invisible at the exact moment a purchase decision is made.

This session explores how agentic commerce is reshaping the path to purchase for both retailers and consumer products organizations, and the strategic implications for each. It walks through the agentic commerce spectrum — from AI-assisted discovery to fully autonomous agent-to-agent transactions — and examines where the market is today, where it is heading, and what that means for how you compete.

NTT ExC runs HR operations for 180,000 NTT Group employees in Japan. To address declining expertise and the volume of employee inquiries, the company developed “Your Navi-QAI” solution, a generative AI chatbot powered by VANTIQ.

In this session, Yousuke Takiguchi of NTT ExC explains how HR programs can be transformed with AI by leveraging historical analysis, real-time knowledge retrieval, and generative AI recommendations to improve HR support for worker transfer, benefits, and career coaching. The program is already showing significant accuracy gains, adoption progress and opportunities to expand collaboration into HC data and analytics.

One of Brazil’s largest financial institutions, in collaboration with Accenture, set out to change how it competes in the market: not by selling more products, but by repositioning itself around the client. Instead of a product lens, where teams, data, and offers are organized around what the bank sells, the institution needed a client lens, where everything starts from who the customer is and what they need. The result was a platform built to reshape the institution’s understanding of its customers at the client level and deliver AI-powered hyper-personalized mapping, targeting, and content at scale.

The approach combines Traditional AI, GenAI, and Agentic AI, including an agent-based simulation layer that models customer behavior with synthetic personas before a single real communication goes out. The results were significant (come see for yourself!). Since then, the approach has been deployed at other institutions and is now shaping a major Cognitive CRM engagement at one of the largest banks in the Americas.

Join Robert Duque-Ribeiro of Accenture as he walks through how the solution was built and scaled, and what it takes to operationalize AI in banking when the business objective drives the technology choices, not the other way around. Attendees will leave with a practical framework for sequencing Traditional AI, GenAI, and Agentic AI around a real business outcome.

Most of what happens to a patient happens outside the clinic. Between appointments, the signals that matter — a change in vitals, a missed medication, a slow decline — go unseen until someone ends up in an emergency room.

Wearables and in-home devices can close that gap, but only if what they produce reaches a clinician as something actionable rather than as more data to triage. That means continuous monitoring connected to the systems care teams already use, and warnings early enough to act on.

In this demo from Walt Pistor of Empowered-Home, see a platform built on Vantiq that turns real-time data from home devices into early intervention for seniors, rural patients and new mothers, and hear what it takes to make continuous care work outside hospital walls.

AI can now write much of a system itself. What it cannot invent is the context that system has to operate inside — the policies, processes and lines of decision authority that determine what it is permitted to do and who approves what.

This conversation looks at how the two fit together: reactive, event-driven architectures that let software act as events unfold, and managed domain knowledge that tells it what is allowed. Healthcare makes the stakes plain, where clinical workflow, regulation, privacy and liability are all context a system must carry before anyone trusts it near a patient. The panel discusses what it takes to build systems that arrive already knowing the rules of the domain they are joining.

Security and public safety comes down to spotting a threat and acting before it lands, or responding as rapidly and effectively as possible after an incident occurs. AI widens what can be anticipated, rehearsed, planned, learned and seen and speeds up what can be done, across nations (D-Resilio), borders, water treatment plants, power grids and dispatch centers. It also moves faster than the people who are supposed to be in charge of it, or responding to it.

Anticipation and detection were the easy parts. The harder question is what happens after the alert: who gets told, what moves, which agencies act together, and whether any of that can be coordinated at the speed of the threat without losing track of who authorized what. After the fact, how can AI help us learn from incidents and develop new tactics, techniques, procedures and equipment.

In this panel we will discuss the challenges and opportunities for security and public safety in a post-AI world. How do we navigate safety against privacy, authority against speed, and decision making in a field that still writes “a human remains in the loop” into policies where the loop has already outrun the human? Most importantly, how do we do this in a time of constant competition and crisis and rapidly expanding capabilities by our adversaries to harness AI and other systems against us.

As AI becomes embedded in how we work and in the fabric of the world around us, the pressing question is not which jobs it replaces. It is what structures let people and AI work together well.

The answer has less to do with smarter models than with what gets built around them. Organizations don’t need one monolithic AI; they need specialized agents that share a common memory of the business and are precise, efficient and safe enough to be trusted against real systems, operating alongside the people who remain accountable for the outcome.

In this fireside chat with the CEO of DevRev and co-founder of Nutanix, hear why the winning architecture is hybrid rather than model-alone, how the economics of software shift when customers pay for outcomes instead of seats, and what it takes to make machines work harder so that people can work softer.

In this session, we proudly announce a new strategic partnership with Vantiq, established to accelerate digital transformation and technological innovation across the manufacturing sector. By seamlessly integrating real-time, event-driven architecture with cutting-edge capabilities such as Physical AI and engineering Digital Twins, we achieve unprecedented operational visibility and enable highly responsive, dynamic automation for complex development environments.
As a long-standing, trusted technology partner serving numerous leading Japanese automotive OEMs and Tier 1 suppliers, our primary mission is to empower research and development teams by delivering immediate, high-impact value. In this presentation, we will demonstrate how combining Physical AI with real-time Digital Twins fundamentally transforms and streamlines core automotive R&D processes, specifically focusing on advanced virtual simulation, physical test data validation, and dynamic model-based systems engineering.

Why the enterprises winning at AI stopped counting agents and started connecting them.

Salesforce mentions “agent” 46 times on its homepage. Ask ten enterprise leaders to define one and you’ll get eleven answers. Yet every board is demanding an agent strategy, while often fretting about existential security risks in the same meeting. Meanwhile, the real value is already inside your company and nearly impossible to see: individual efficiencies that never reach a dashboard, “agents” shared by Slacking a skill file, and a growing pile of credentials and data access nobody has inventoried.

This talk argues the instinct to stop the sprawl is exactly backwards. Sprawl is a growth signal, proof your people found value faster than your architecture could absorb it. The answer isn’t standardizing on one agent platform; it’s standardizing the network between agents: discovery, identity, permission, revocation, evidence, and making that network so easy that every employee, not just IT, takes the governed path by default. And because most useful agents eventually get web apps built on top of them, Greene will confront the sprawl wave nobody’s discussing yet: your security model has to survive the moment someone gives an agent a UI.

Some of the most useful clinical signals are the ones nobody has time to measure. NeuroSync’s FDA-cleared EYE-SYNC platform uses eye tracking in virtual reality to assess brain health in under a minute, producing objective measurements where clinicians have traditionally relied on judgment and observation — in concussion diagnosis, vestibular therapy, CNS drug trials, athlete safety and military readiness, at institutions including Massachusetts General Hospital and Houston Methodist. In this session, Gary Gregory of NeuroSync looks at what changes when that kind of objective data arrives in real time rather than after the fact, and what it takes to turn a fast, portable assessment into decision support a clinician will actually act on.

Cities and large-scale infrastructure generate vast volumes of heterogeneous data, yet fragmented systems, inconsistent data quality, and disconnected AI models often prevent that data from driving real-world action.

This session introduces KMAC’s Urban Intelligence Platform (UIP), a full-stack AI architecture that integrates trusted data management, real-time event processing, and multi-AI orchestration. At the data foundation layer, Fabric One — jointly developed by KMAC and Teradata — collects, processes, stores, and governs heterogeneous data across legacy systems, IoT devices, cameras, and enterprise platforms. Built on this trusted data foundation, Vantiq’s event-driven architecture enables real-time situational awareness and orchestrates predictive, generative, and agentic AI into coordinated operational workflows.

UIP completes the end-to-end intelligence cycle — from data collection and quality management to AI analysis, decision-making, and automated action. The session will demonstrate how this architecture can support mission-critical use cases across public safety, mobility, energy, healthcare, and smart infrastructure while enabling flexible deployment across edge, on-premises, and cloud environments.

KMAC will present how organizations can move beyond fragmented AI pilots toward a scalable, governed, and autonomous operating model for AI-ready cities.

As AI moves from experimentation into mission-critical environments, regulated industries face a fundamental challenge: how to innovate while navigating a complex, unpredictable, and increasingly politicized regulatory landscape. Moderated by Mike Parrish, former Chief Acquisition Officer for the U.S. Department of Veterans Affairs, this panel will explore how organizations are approaching AI governance, privacy, liability, security, and accountability—and how these considerations should shape system design from the outset. Panelists will also examine the evolving role of AI as a tool to augment human decision-making versus a technology intended to replace human roles, and the different implications each approach creates. The discussion will offer practical perspectives on deploying AI responsibly and reliably in environments where the stakes are high and the rules continue to evolve.

Organizations cannot predict every operational shock or prebuild every response. The advantage is the ability to turn changing context into governed action — and then to preserve what is learned as reusable capability.

This session makes that concrete through a simulated crisis response. The proof environment is the Francis Scott Key Bridge collapse and the closure of the Port of Baltimore, told through the cascading decisions that followed across terminals, carriers, rail, trucking, government agencies and alternate ports. The audience watches a real crisis break the plan; sees AI join the response as a partner, interpreting context and proposing options while accountable humans retain authority; and follows a governed operational capability as it takes shape, with policy, protocol and accountability traveling alongside it.

The payoff is what happens after the event. The workflows, policies and components created under pressure become assets for the next one — one crisis producing coordinated operational capability rather than a return to the previous state. A resilient organization has a plan for the last crisis; an antifragile organization has a way to learn during the next one.