Alan Baratz
Analyst · Cantor Fitzgerald
Good morning, everyone, and thank you for joining us. The quantum computing market is reaching an important inflection point. Scientific progress is accelerating, customer interest is expanding and a growing number of companies are entering the public markets. That increased visibility is good for the industry, but it also means investors need to separate measurable progress from rhetoric. In a market increasingly crowded with claims, investors should ask three simple questions. First, does the company have differentiated technology with a credible path to scale? Second, can the company translate that technology into reliable enterprise-ready systems? And third, can it execute and produce measurable customer value. At our recent Investor Day, we demonstrated why we believe that D-Wave stands apart on each of these three criteria. We have a differentiated technical foundation, deep expertise building and operating commercial quantum systems, a growing portfolio of production applications and clear road maps across our dual platform strategy. This quarter added further evidence. IDC recently named D-Wave as one of only two companies in the leaders category in the IDC MarketScape: Worldwide Quantum Computing 2026 Vendor Assessment. We believe this recognition is significant because IDC evaluated companies not simply on a single performance metric or future road map, but on both their current capabilities and their ability to execute. IDC highlighted D-Wave's production deployment footprint, our mature framework for enterprise access and hybrid adoption and our work extending annealing quantum computing beyond optimization and into scientific simulation. It also observes that competition in quantum computing is shifting away from raw qubit counts and towards broader platform maturity. That includes software, hybrid integration, deployment flexibility and integration with existing HPC, AI and enterprise computing environments. In other words, the industry is increasingly being judged on whether companies can deliver complete usable quantum platforms, not simply announced ambitious road maps, and that plays directly to D-Wave's strengths. Quantum computing leadership requires far more than a promising processor. It requires hardware, cryogenics, control systems, software, cloud infrastructure, developer tools, professional services and the operating discipline to make the entire stack perform reliably. We have spent more than 15 years doing that hard work. Let me now turn to the technical developments announced this quarter and the road maps they support. Our objective for D-Wave's Gate-Model program is clear: to deliver a fast, scalable and commercially useful fault-tolerant quantum computer. The threshold for commercial relevance is high. We believe that initial commercial applications will require approximately 100 logical qubits and the ability to perform more than 1 million operations reliably. A system that cannot reach both sufficient scale and sufficient reliability may be scientifically interesting, but it is not yet capable of addressing commercially meaningful problems. That is the standard investors should apply when evaluating gate-model road maps. Reaching that threshold requires much more than increasing physical qubit counts. A system must have computational capacity, fast gate operations and an error correction architecture that can scale efficiently. Error correction is essential because physical qubits are inherently susceptible to errors. Without effective error correction, a gate-model system cannot reliably execute the long and complex computations required to solve meaningful problems. That's why we believe investors and customers should evaluate gate-model architectures using three fundamental measures. How quickly can the system perform gate operations and error correction cycles? How efficiently do errors decline as error correction capability is added? And when will the system support enough reliable operations on enough logical qubits to address commercially relevant applications. At our Investor Day, we detailed how D-Wave's superconducting dual-rail architecture is designed to address these requirements. Superconducting technology provides an important speed advantage with gate operations and error correction cycles performed on microsecond time scales. At smaller system sizes, differences in speed may appear less consequential. At commercial scale, when a system must execute enormous numbers of operations and error correction cycles, speed becomes fundamental to whether it can solve a problem within a commercially relevant time frame. The other critical measure is Lambda, which describes how rapidly logical errors decline as the size of the error correcting code increases. A higher Lambda means each additional increment of error correction produces a greater reduction in errors, lowering the number of physical qubits required to create a reliable logical qubit. Leading superconducting approaches have demonstrated a Lambda of approximately two, meaning errors decline by roughly a factor of two with each increment in the error correcting code. Our gate-model road map targets a Lambda of 10. This target is grounded in the inherent error detection characteristics of our dual-rail architecture. The performance that we have already demonstrated on our system and the recent peer-reviewed results validating that those advantages are preserved during high fidelity entangling operations. Taken together, this evidence gives us confidence in our ability to achieve significantly more efficient error correction as the architecture scales. A Lambda of 10 would reduce errors by a factor of 10 with each increment in error correcting code. At scale, that level of efficiency could enable approximately 100 to 200 physical qubits to produce one reliable logical qubit rather than the many thousands that may be required by less efficient superconducting approaches. That is not a marginal improvement. It is transformational. It fundamentally changes the size, complexity and hardware overhead required to reach fault tolerance. We believe this combination of superconducting speed and highly efficient error correction is the core differentiation behind D-Wave's gate-model architecture and an important reason we believe our approach offers an efficient and achievable path to commercial fault tolerance. The peer-reviewed research that we announced yesterday provides important validation of that foundation. Published in Nature, the research demonstrates a fast, high fidelity two-qubit entangling gate designed to support efficient quantum error correction. The research demonstrated approximately 99.9% fidelity during two qubit operations with fast gate times of about 500 nanoseconds, all enabled by native hardware-level error detection and no additional error correction. So why is this significant? The results address one of the industry's most consequential challenges by reducing the immense quantum and classical hardware overhead typically required to detect and correct quantum errors as systems scale. It also addresses a long-standing challenge for superconducting quantum computers, which are known for their speed, but have historically struggled to achieve the high fidelity required for scalable fault-tolerant systems. The Nature paper validates that our dual-rail architecture combines fast superconducting operations with high fidelity performance while preserving native hardware-level error detection. Our simulations indicated that our dual-rail architecture could reduce the logical error rate by as much as a factor of 10 for each increment in error correction, significantly reducing the physical overhead required for fault-tolerant quantum computing. We believe these results provide strong technical evidence that the architectural principles underlying our road map can support faster, more hardware-efficient fault-tolerant quantum computing than any other approach to gate-model quantum computing. Importantly, this is not isolated laboratory work. The entangling gate demonstrated in the research was done on our 8-qubit dual-rail processor, creating a direct line from peer-reviewed validation to road map execution. That architectural foundation supports the gate-model road map that we presented at our Investor Day, which is designed to progressively demonstrate more effective error detection and correction, lower logical error rates and increased scale on the path to commercial fault tolerance. Specifically, later this year, we expect to deliver a 17 physical qubit system designed to support logical error rates approximately 2x lower than the underlying physical error rates. Next year, we expect to complete a 49 physical qubit system designed to deliver an approximately 20-fold error reduction factor. In 2028, we expect to complete a 181 physical qubit system designed to deliver an approximately 2,000-fold error reduction factor. We expect that system to provide the scalable architectural blueprint for the fault tolerance systems that follow. Then by 2030, we expect to complete a system with 10 logical qubits capable of supporting the first fault tolerant algorithms. And by 2032, we expect to scale to 100 logical qubits and more than 1 million reliable operations, creating a system capable of supporting initial commercial applications in areas such as quantum chemistry and quantum AI. We have given investors a clear basis for evaluating our progress, faster performance, more efficient error reduction and a growing number of reliable operations. Achieving those milestones is what will move gate-model quantum computing from technical progress to commercial utility. We're also building the developer ecosystem required to support adoption as the hardware advances. We are now waiting for the final fault tolerance system to begin creating the customer and developer base around our architecture. During the quarter, we announced our forthcoming gate-model simulator, which we expect to make available in our Leap Quantum Cloud platform later this year. We believe it will be the first simulator designed specifically for error-aware quantum programming. We expect it will enable developers to prototype, test and validate applications and error correction routines based on realistic dual-rail error detecting system behavior before executing them on the actual quantum hardware. Rather than treating errors as an abstract hardware issue, we expect developers will be able to understand how errors occur and then design applications and workflows that respond to actual processor behavior. We believe that capability can accelerate the development of error correction techniques and applications. Our technical road map extends across both gate-model and annealing quantum computing. At Investor Day, we provided additional details on our plans to scale annealing systems using advanced packaging and superconducting interconnect technologies that can connect multiple quantum processing units in a multi-chip fabric. Our product road map targets a 20,000 qubit Advantage3 system in 2029 and a system reaching 100,000 qubits by 2031. We also announced a scalable I/O prototype design intended to support significant QPU expansion without a corresponding increase in the number of control lines. Together, these advances reflect the breadth of our technical ambition and the strategic value of our dual platform approach. Customers face different classes of computational problems and no single quantum computing architecture is best suited to all of them. Our strategy is built around a straightforward premise. Customers should have access to the quantum computing technology best suited to the problem they need to solve. We believe D-Wave is uniquely positioned to provide that ground. Our technical leadership is translating into expanding commercial momentum. Let me highlight several recent customer engagements. First, AT&T. Last week, we announced an expanded agreement with AT&T focused on applying D-Wave's technology to complex optimization challenges across its network operations. The initial work will integrate our annealing quantum computing capabilities with the Agentic AI tools AT&T already uses to improve network performance and reduce customer disruption. In one early application, D-Wave's technology reduced processing time from approximately one hour to less than 15 seconds. Building on that result, AT&T plans to evaluate additional applications, including outage response, technician routing and network planning and traffic management as it expands its fiber and 5G infrastructure to support rising AI-driven demand. Second, Optum. At Qubits Europe last month, Optum, a major subsidiary of UnitedHealth Group, discussed its experience applying our Quantum hybrid technology to difficult optimization problems involving thousands of variables, hundreds of thousands of constraints and multiple competing business objectives. Optum had worked on these mature problems for years, but classical approaches struggled to consistently produce sufficiently strong solutions. The initial proof of technology produced results strong enough for Optum to move directly to a production application, bypassing the traditional proof-of-concept stage. We believe that accelerated move to production reflects both the strength of the results and the value of D-Wave's approach. After launching the application in May, Optum had already run approximately 30,000 jobs by mid-June, the team is now evaluating additional opportunities within Optum and across the broader UnitedHealth organization. And third, NTT DOCOMO. NTT DOCOMO has similarly expanded its production use of D-Wave technology. Its first application optimized paging signals across its Japanese mobile network, reducing paging signals by 15% and contributing to meaningful infrastructure efficiencies. The second application addresses the more complex trade-off between location registration signals and paging signals. Using D-Wave's technology, NTT DOCOMO reduced location registration signals by approximately 65%, while also reducing paging signals by 7% during peak periods. These improvements can reduce computational load across the network, improve operational efficiency and help lower infrastructure requirements. NTT DOCOMO described the optimization results as exceeding expectations and has indicated that it intends to continue identifying additional areas where D-Wave quantum optimization can create value. The takeaway here is that the one successful production deployment led NTT DOCOMO to identify and implement another application. And that is how individual use cases begin to develop into broader enterprise adoption. We now have six customer applications in production with many others advancing through the development process. Based on publicly available information, we are not aware of another quantum computing company with a comparable production application portfolio. These are not demonstrations or laboratory experiments. They are applications operating within customer environments. In our view, this gives D-Wave a significant head start in the customer relationships, application expertise, software capabilities and enterprise infrastructure required to scale commercialization. Our progress in transitioning customers like Optum and NTT DOCOMO into production applications is underscored by the fact that over 37% of our first half QCaaS revenue was derived from production applications compared to just 9.8% in the first half of 2025. Our on-premises system business also continues to progress, supported by a strong pipeline of opportunities. As previously stated, we expect to deliver a system to Florida Atlantic University in 2026, and we continue to expect to book two to three systems deals annually going forward, including two system deliveries in 2026. Let me now turn to government activity. We are seeing increasing recognition from U.S. government agencies that our quantum computing is a strategically important technology and that D-Wave has a meaningful role to play in strengthening domestic quantum leadership. During the quarter, D-Wave was selected to receive approximately $1.57 million from the U.S. National Science Foundation through its National Quantum Virtual Laboratory Program. The funding supports our participation in the ERASE project, which is developing foundational technologies for fault-tolerant quantum computing. The current phase is expected to span two years and includes development of hardware system designs for feasible fault tolerant gate-model quantum computers. Successful completion could create an opportunity to participate in a third larger phase of the program. We were also awarded second year funding for the improved materials for superconducting qubits with scalable fabrication or SQ Fab project through NORDTECH. The project is 1 of 4 programs selected for continued funding after achieving key first year technical milestones. Taken together, these programs reflect growing government confidence in D-Wave's technical expertise, our ability to execute and the strategic relevance of our technology. And finally, D-Wave received Great Place to Work certification for 2026 based entirely on employee feedback. Building and scaling a commercial quantum computing company requires exceptional people and a culture focused on collaboration and execution. As we expand our commercial operations and advance both our annealing and gate-model technology road maps, our ability to attract and retain that talent will remain critical. I want to thank the entire D-Wave team for the expertise, commitment and hard work they bring to our customers and our mission every day. With that, I'll turn the call over to John.