Cognite named Marathon Petroleum's Supplier of the Year. Cognite, an industrial artificial intelligence and data technology company, has been named Corporate Supplier of the Year by Marathon Petroleum Corporation at the company's 11th Annual Supplier Recognition Awards. The recognition highlights Cognite's contribution to Marathon Petroleum's business performance and reflects the importance of supplier collaboration, technology innovation, and measurable business outcomes in the energy industry. Marathon Petroleum Corporation sponsors the Supplier Recognition Awards program to recognize suppliers whose products, services, and contributions have positively influenced the company's business throughout the previous calendar year. The annual program acknowledges the role of external partners in supporting operational performance, business objectives, and ongoing improvements across the organization. Cognite's selection as Corporate Supplier of the Year underscores its commitment to delivering practical value for industrial customers. As companies across the energy and manufacturing sectors increasingly adopt digital technologies, artificial intelligence, and industrial data solutions, partnerships with technology providers are becoming an important part of operational improvement strategies. Cognite emphasizes measurable customer value. Girish Rishi, chief executive officer of Cognite, said the recognition reflects the company's emphasis on delivering tangible results for customers. He explained that impact is one of Cognite's core values and that the company's performance is measured by the quantifiable value it creates for the organizations it serves. Rishi described the award from Marathon Petroleum as particularly meaningful because of the company's focus on innovation. He also expressed appreciation for the recognition, noting that the award represents an important achievement for the wider Cognite community. For industrial technology providers, delivering measurable customer outcomes is an important part of demonstrating the effectiveness of digital transformation initiatives. Energy companies operate complex assets, manage extensive industrial data, and face continuing demands to improve efficiency and decision-making. Technology partnerships can help these organizations connect information across operations and apply digital tools to business challenges. The recognition from Marathon Petroleum provides an example of how industrial companies acknowledge suppliers that contribute positively to their operations and broader business performance. Industrial AI and data technologies gain recognition. Cognite's latest award comes during a year in which the company has received several other industry recognitions for its work in industrial artificial intelligence, data operations, and technology innovation. In May 2026, Cognite ranked 15th on CNBC's Disruptor 50 list. The list recognizes venture-backed companies introducing innovative approaches across industries, including businesses experimenting with artificial intelligence and developing ways to implement the technology at scale. The recognition places Cognite among companies attracting attention for their approaches to innovation and the practical application of emerging technologies. Industrial organizations are increasingly exploring AI solutions to help employees work with complex operational information, improve access to data, and support decisions across industrial environments. For the energy sector, these capabilities are particularly relevant because operators must coordinate information from equipment, facilities, engineering systems, and business applications. Making that information accessible and useful can support more informed operational decisions. In April 2026, LNS Research positioned Cognite as a FrontRunner in its Solution Selection Matrix for Industrial AI Platforms. The assessment recognizes Cognite's position within the industrial AI technology landscape and adds to the company's list of industry acknowledgments during the year. Industrial AI platforms are designed to help organizations use data from industrial operations to support analytics, workflows, and decision-making. Their relevance continues to grow as businesses evaluate ways to integrate artificial intelligence into existing systems and operational processes. The recognition from LNS Research provides another indication of Cognite's standing in a market where industrial companies are assessing technology platforms that can support their digital initiatives. Recognition for Industrial data operations. Cognite also received recognition from IDC Research in March 2026. IDC ranked the company as a Leader in its MarketScape assessment for Worldwide Industrial DataOps Platforms. Industrial DataOps focuses on making industrial data more accessible, reliable, and usable across different systems and teams. Organizations often manage large volumes of information generated by operational technology, enterprise applications, equipment, and other industrial sources. Connecting these data sources can help reduce information barriers and improve the ability of employees to use operational insights. For energy companies, effective industrial data management can support asset performance monitoring, maintenance planning, production analysis, and operational coordination. However, realizing these benefits often requires organizations to address fragmented systems and differences in how information is collected, structured, and shared. Industrial DataOps platforms aim to address these challenges by improving the availability and usability of information across business and operational environments. Recognition in IDC's MarketScape highlights Cognite's position in this segment of the industrial technology market. Together, the IDC, LNS Research, and CNBC recognitions demonstrate the range of attention Cognite has received in 2026, spanning industrial data platforms, artificial intelligence, and technology-led business innovation. Supplier partnerships in the energy industry. Marathon Petroleum's Corporate Supplier of the Year award highlights the role suppliers play in supporting the company's business objectives. Large energy companies depend on a network of technology providers, equipment manufacturers, service companies, and other partners to maintain operations and pursue improvements. As the industry continues to evaluate digital transformation opportunities, suppliers offering industrial data and AI capabilities can contribute to initiatives aimed at improving how information is managed and applied. The value of these partnerships depends on their ability to address operational requirements and deliver results that customers can measure. Cognite's recognition reflects the importance of customer-focused performance in industrial technology relationships. Rather than relying solely on technological capabilities, suppliers must demonstrate how their solutions and services contribute to the priorities of the organizations they support. The award also adds to Cognite's broader record of recognition during 2026. Its placement on CNBC's Disruptor 50 list, its FrontRunner position in LNS Research's industrial AI assessment, and its Leader ranking in IDC's industrial DataOps evaluation collectively highlight its presence in several areas of the industrial technology market. Continuing focus on industrial innovation. The Corporate Supplier of the Year recognition from Marathon Petroleum represents a significant milestone for Cognite as industrial companies continue to assess how data and artificial intelligence can support business performance. Energy organizations face complex operational requirements, making the ability to access and use reliable industrial information increasingly important. Technology providers that help customers apply digital capabilities to real-world challenges can play a role in supporting these efforts. For Cognite, the award reinforces its stated commitment to measurable customer value and strengthens a year of recognition from industry and research organizations. The announcement also underscores the importance of collaboration between industrial operators and technology suppliers. As companies continue to explore industrial AI and data management solutions, customer outcomes and demonstrated business impact remain important measures of success. Through the latest recognition from Marathon Petroleum and its other industry distinctions in 2026, Cognite continues to establish its presence in the industrial technology sector, particularly in areas related to artificial intelligence, industrial data operations, and digital innovation.

Cognite earns Corporate Supplier of the Year Award from Marathon Petroleum Corporation. Business Wire Published Oct 21, 2026 PHOENIX - Cognite today announced it has been named Corporate Supplier of the Year winner in Marathon Petroleum Corporation's 11th Annual Supplier Recognition Awards. The Supplier Recognition Awards is a program sponsored by Marathon Petroleum Corporation to honor suppliers that positively impacted the company's business throughout the previous calendar year. "There's a reason 'Impact' is one of Cognite's most important core values," said Girish Rishi, CEO of Cognite. "For us, the ultimate measure of our performance is delivering quantifiable value for our customers. From that perspective, the Corporate Supplier of the Year award from Marathon is particularly meaningful. Marathon Petroleum is an innovator, and to receive this recognition is a great honor to the Cognite community." Story continues below The Supplier of the Year Award from Marathon is the latest honor Cognite has received in 2026: Top Stories Interested in more newsletters? Browse here. * In May, Cognite ranked 15th on CNBC's Disruptor50 list, honoring venture-backed companies innovating across industries, experimenting with AI and making it work at scale * In April, LNS Research positioned Cognite as a FrontRunner in its Solution Selection Matrix for Industrial AI Platforms * In March, IDC Research ranked Cognite a Leader in its MarketScape for Worldwide Industrial DataOps Platforms About Marathon Petroleum Corporation Marathon Petroleum Corporation (MPC) is a leading, integrated, downstream and midstream energy company headquartered in Findlay, Ohio. The company operates the nation's largest refining system. MPC's marketing system includes branded locations across the United States, including Marathon brand retail outlets. MPC also owns the general partner and majority limited partner interest in MPLX LP, a midstream company that owns and operates gathering, processing, and fractionation assets, as well as crude oil and light product transportation and logistics infrastructure. More information is available at www.marathonpetroleum.com. About Cognite Cognite makes AI work for industry. Leading energy, manufacturing, life sciences, and power and renewables enterprises choose Cognite to deliver secure, trustworthy, and real-time data to transform their asset-heavy operations to be safer, more sustainable, and profitable. Cognite provides a user-friendly, secure, and scalable industrial data & AI platform that makes it easy for all decision-makers, from the field to remote operations centers, to access and understand complex industrial data, collaborate in real time, and build a better tomorrow. Visit us at www.cognite.com, and follow us on LinkedIn. View source version on businesswire.com:

Taming Industrial AI Starts with Great Data. October 6, 2026 By Asha Suparna Technology Trends Cognite, a Gold Sponsor of ARC Advisory Group's 24th Annual ARC Industry Forum in Bengaluru, was represented by Ravi N. Mishra, Sr. Director - Sales (India), and Pawan Misra, Principal Designer for Data Integrations, Cognite India. In their presentation, Taming the Wild State of Industrial AI Starts with Great Data, they explored how contextualized industrial data can provide the foundation needed to move from basic AI assistants toward agentic workflows that support real operational tasks. Industrial companies have no shortage of AI models, copilots, and agents to experiment with. The harder problem is giving those systems the right industrial context. Operational information is typically distributed across historians, SCADA and control systems, maintenance applications, engineering documents, enterprise platforms, 3D models, and other repositories. Cognite's central argument is that AI model capability alone is not enough. Industrial AI depends on bringing these different forms of information together in a way that allows AI systems to understand the relationships between assets, processes, events, documents, and operational history. The presentation can be viewed on YouTube or here: Context is the bottleneck for Industrial AI. Cognite describes its own AI journey as progressing from general-purpose chat agents toward increasingly specialized and integrated workflows. An early phase used a single general-purpose chat agent, but the approach lacked the domain context and guardrails required for industrial applications. This progressed to task-specific agents designed for defined use cases, followed by deep research and ambient agents capable of handling more complex analytical tasks. The next step is agentic workflows that combine agents with generated applications and retain humans in the loop. Examples include root cause analysis, work package creation, operations summarization, quality investigation, and batch analytics. However, building the agent itself is only part of the challenge. Cognite identifies context as the bottleneck. Industrial data remains multimodal and siloed, while document-based retrieval-augmented generation and vector search may struggle to find the specific information required for complex industrial questions. The challenge is not simply locating data, but understanding how different pieces of information relate to one another. Cognite identifies grounding and industrial context, rather than AI model capability alone, as a key bottleneck when operational data remains distributed across multiple systems and formats. Building an Industrial Knowledge Graph. Industrial environments generate many different types of information. An individual asset may be represented in an equipment hierarchy, produce real-time time-series measurements, appear in engineering drawings and maintenance records, have associated work orders and inspection histories, and be represented in 3D models or images. These sources frequently use different naming conventions and schemas. Cognite Data Fusion is designed to connect these sources and contextualize them within an Industrial Knowledge Graph. The presentation showed information spanning assets, time series, events, engineering files, maintenance work orders, 2D and 3D information, and visual data being linked into a common industrial context. Cognite also emphasizes governance around that data foundation. Governed access controls determine who can access information, while an open, stable API allows organizations to use their own applications, agents, and AI models against the contextualized data. According to Cognite, its industrial data foundation can connect more than 100 IT, OT, and engineering technology sources, with the knowledge graph providing the layer that ingests, contextualizes, and governs the information. Cognite's Industrial Knowledge Graph connects operational, engineering, maintenance, and visual information to provide applications and AI agents with a common industrial context. From AI assistants to agentic workflows. Once that contextual foundation exists, AI can begin supporting more specific industrial workflows. Cognite identifies root cause analysis, work package generation, and shift handover as three practical starting points. The company says its root cause analysis approach can reduce time-to-cause from hours to minutes, while its shift-handover application can reduce meeting duration by 25 percent or more. The broader goal is not simply to make existing workflows faster. Cognite argues that agentic systems can begin changing how work is organized. Rather than an operator repeatedly searching multiple systems for information, an agent can monitor assets, retrieve relevant context, assemble information, and surface the cases that require human attention. This can also extend to application creation. Cognite Flows is designed to allow domain experts to create workflows, visualizations, and applications using AI, reducing their dependence on separate development teams for every new operational requirement. The human remains part of the process, but the distribution of work can change as agents take on more of the information gathering and orchestration. Root cause analysis in practice. Pawan Mishra demonstrated this approach through an AI-assisted root cause analysis workflow. The investigation began with a specific equipment problem and used multiple agents to retrieve and analyze relevant information. The workflow brought together equipment information, failure modes, time-series data, engineering drawings, maintenance history, work orders, notifications, shift reports, and other contextual data from the industrial data foundation. The agent could then systematically evaluate potential causes, document the supporting evidence, and generate an RCA report. Importantly, the workflow was designed to expose the evidence used in reaching a conclusion. This allows engineers to review the information and determine whether the agent's analysis is appropriate rather than treating the AI output as an unexplained answer. The workflow can also be adapted to an organization's existing RCA methodology, including established investigation and reporting processes. According to Cognite, the RCA demonstrated during the presentation could run in approximately 10 minutes. The company said the customer-specific workflow itself was built in approximately two and a half days once the underlying knowledge graph was already available. That qualification is important: the speed of building the AI workflow depends heavily on having the contextualized industrial data foundation already in place. Building the foundation for Industrial AI at scale. Cognite sees the same data foundation supporting increasingly sophisticated industrial AI. The company is currently collaborating on the training and testing of a time-series foundation model using a large multimodal and contextualized industrial dataset. The presentation cited 93 trillion time-series data points and 4.4 billion data-modeling instances as part of that foundation. The longer-term objective is to enable AI models that can work across different industrial assets while remaining grounded in operational context. For industrial organizations, however, the immediate lesson is more fundamental. The effectiveness of an AI agent depends on the quality of the information available to it and the relationships established between different sources of industrial data. Building additional copilots or choosing more capable models will not by itself solve fragmented asset hierarchies, inconsistent naming, disconnected engineering information, or inaccessible maintenance history. Industrial AI becomes more useful when those sources are connected, contextualized, governed, and made accessible to the systems that need them. As manufacturers and process industries move from isolated AI use cases toward agentic workflows, the competitive advantage may therefore come less from the model itself and more from the industrial knowledge foundation underneath it.