Canvas Category Software : Information Technology : Asset Performance Management
We’re an industrial software company headquartered in Oslo, Norway, with offices in Tokyo, Japan, and Austin and Houston, Texas. We create software for oil and gas, power and utilities, renewable energy, manufacturing and other asset-heavy industries. Our products turn industrial data into customer value by liberating it, contextualizing it, and making it actionable for users.
Cognite and ANYbotics Driving Innovation Within AI Robotics And Safe Operations
Cognite, a globally recognized leader in industrial software, and ANYbotics, a globally leading robotics company specializing in the development of advanced four-legged robots for industrial inspection, have signed a Memorandum of Understanding (MoU) where they will enter a non-exclusive collaboration aimed at delivering cutting-edge products and services to global customers. The parties seek to leverage the unique strengths of both companies to offer customers an integrated robotics inspection solution, enabling unmanned operations by providing real-time autonomous data collection in industries such as Oil & Gas, Power & Utilities, Chemicals, and Metals.
ANYbotics’ autonomous robotic inspection, driven by an automated end-to-end workflow, and Cognite’s specialized industrial DataOps platform, Cognite Data Fusion®, complement each other seamlessly and will fuel AI robotics innovation and deployment across current and prospective customers to improve the safety of operations and reduce operational expenditures.
Microsoft and Cognite extend partnership to build industrial data operations platform on Microsoft Fabric and Azure OpenAI Service
Long-time partners Microsoft and Cognite have successfully delivered digital transformation value to industrial customers in energy, industrial carbon management, manufacturing, and renewables globally. In a landmark new collaboration, Cognite and Microsoft are excited to announce an expansion of their strategic partnership to bring enterprise data operations to the generative AI era, from the shop floor all the way to the top floor. For the first time, enterprise and industrial—information technology (IT), operational technology (OT), and engineering technology (ET)—converge for data operations and AI value.
Cognite Announces Beta Launch of Generative AI-Powered Remote Operations Control Room for Celanese Clear Lake Facility
Cognite, a globally recognized leader in industrial software, today announced the beta launch of a generative AI-powered Remote Operations Control Room (ROCR) at the Celanese facility in Clear Lake, Texas. Celanese, a global chemical and specialty materials company, plans to use the ROCR to deliver full visibility into the real-time operation of its sites worldwide, thereby expediting workflows and gaining operational insights orders of magnitude more efficiently.
By integrating generative AI into a Remote Operations Control Room, Cognite will increase visibility to our site leaders and their teams and enable a multitude of possibilities – from monitoring equipment performance to enhancing root cause analysis to streamlining and enhancing our processes,” said Brenda Stout, vice president of Acetyls Manufacturing at Celanese.
ANYmal Closes the Remote Inspection Loop with Aker BP and Cognite
Aker BP, Cognite, and ANYbotics partner in pioneering offshore remote inspections with ANYmal X on the Valhall platform in the North Sea. ANYmal X, the only Ex-certified legged robot, was tested for integrated robotic inspections in offshore Ex-rated zones, showcasing the benefits of Cognite’s real-time digital twins and comprehensive AI-powered data platform. This is a significant step in Aker BP’s aim to implement remote inspections as an enabler for unmanned operation of complex offshore processing platforms by 2027-2029.
Celanese's Vision for an Autonomous, Self-Optimizing Plant Powered by Generative AI
One of the key things we’ve been planning to do in 2023 is scaling the (Cognite) platform, bringing all the data together, putting the right context, the right meaning to it, getting it contextualized and modeling it. As part of that investment, we’re using artificial intelligence and generative AI capabilities. But our artificial intelligence journey or generative artificial intelligence is only as good as our underlying data. So, the biggest effort for us has been to standardize the data on common data models, bring it all together, contextualize it and then start leveraging AI capabilities on top of that.
You have to make sure that whatever you’re architecting actually is intuitive and works and addresses the needs of the people. For example, you have this phone, right? I don’t need a user manual or training for this. It just works, and I am married to it. I can’t live without it. So we have to find the balance of making the right solutions for the people and keeping that in mind. Also, we have developed what we call a Digital Manufacturing Academy that is now available globally for all our users. And that academy is really around giving people the ability to upskill, have more data literacy, more digital literacy skills, and even give people the opportunity to start learning how to code, if they need to.
The treacherous path to trustworthy Generative AI for Industry
Despite the awesome first impact ChatGPT showed and the already significant efficiency gain programming copilots are delivering to developers as users2, making LLMs serve non-developers – the vast majority of the workforce, that is – by having LLMs translate from natural language prompts to API or database queries, expecting readily usable analytics outputs, is not quite so straightforward. Three primary challenges are:
- Inconsistency of prompts to completions (no deterministic reproducibility between LLM inputs and outputs)
- Nearly impossible to audit or explain LLM answers (once trained, LLMs are black boxes)
- Coverage gap on niche domain areas that typically matter most to enterprise users (LLMs are trained on large corpora of internet data, heavily biased towards more generalist topics)
Demo: Cognite Data Fusion's Generative AI Copilot
What does it take to talk to your Industrial Data in the same way we talk to ChatGPT?
The vast data set used to train LLMs is curated in various ways to provide clean, contextualized data. Contextualized data includes explicit semantic relationships within the data that can greatly affect the quality of the model’s output. Contextualizing the data we provide as input to an LLM ensures that the text consumed is relevant to the task at hand. For example, when prompting an LLM to provide information about operating industrial assets, the data provided to the LLM should include not only the data and documents related to those assets but also the explicit and implicit semantic relationships across different data types and sources.
An LLM is trained by parceling text data into smaller collections, or chunks, that can be converted into embeddings. An embedding is simply a sophisticated numerical representation of the ‘chunk’ of text that takes into consideration the context of surrounding or related information. This makes it possible to perform mathematical calculations to compare similarities, differences, and patterns between different ‘chunks’ to infer relationships and meaning. These mechanisms enable an LLM to learn a language and understand new data that it has not seen previously.
Will Generative AI finally turn data swamps into contextualized operations insight machines?
Generative AI, such as ChatGPT/GPT-4, has the potential to put industrial digital transformation into hyperdrive. Whereas a process engineer might spend several hours performing “human contextualization” (at an hourly rate of $140 or more) manually – again and again – contextualized industrial knowledge graphs provide the trusted data relationships that enable Generative AI to accurately navigate and interpret data for Operators without requiring data engineering or coding competencies.
Industrial Asset Performance Management has a data problem
Historically, the solution for solving Asset Performance Management use cases has been to invest in siloed systems (e.g., ERP systems), niche solutions (e.g., IoT Applications), or run multi-year “lighthouse” projects with little-to-no ROI to show after months or years of data wrangling and deployment effort. If it takes two years to deploy an APM application at your lighthouse facility, do you really have 100 years to wait until the same solution is deployed across the remaining 50 sites?
When people are spending 90% of their time searching, preparing, and governing data, there’s little time left to invest in gaining better, data-driven insights. Without a coordinated and collaborative data management strategy, APM initiatives will continue to fall short of their ROI expectations.
Using Data Models to Manage Your Digital Twins
A continuously evolving industrial knowledge graph is the foundation of creating industrial digital twins that solve real-world problems. Industrial digital twins are powerful representations of the physical world that can help you better understand how your assets are impacting your operations. A digital twin is only as useful as what you can do with it, and there is never only one all-encompassing digital twin. Your maintenance view of a physical installation will need to be different from the operational view, which is different from the engineering view for planning and construction.
How Celanese uses Cognite Data Fusion to power Digital Factories of the Future
Ignos by Aarbakke is pioneering Smart Factory as a Service
Moelven | Optimizing timber production with Industrial DataOps and Cognite
Equinor and Cognite Enter Long-term Collaboration to Further Accelerate Equinor’s Digitalization Program
Cognite, a global leader in industrial software, today announced a long-term frame agreement with Equinor (OSE: EQNR, NYSE: EQNR), a world-leading energy company. The collaboration will expand Equinor’s data capabilities and further strengthen its digital program focused on global energy security and energy transition.
The objective for the Equinor and Cognite cooperation is to support Equinor in securing faster value capture from its ambitious digitalization program, using Cognite Data Fusion® as a module in Equinor’s OMNIA data architecture. OMNIA is built on the Microsoft Azure cloud, and the Equinor and Cognite collaboration will progress the deployment of digital solutions on OMNIA.
Clean Connect AI Collaborates with Cognite to Provide Vision-Based Autonomous Operation and Emissions Applications
Clean Connect AI Inc, a Colorado-based hardware-enabled SaaS software company serving the energy and industrial automation industry, today announced a strategic partnership with Cognite, a global leader in industrial software, to provide vision-based autonomous operation and emissions applications that will optimize industrial operations and enable manage-by-exception efficiencies at scale.
Industrial DataOps: The data backbone of digital twins
What is needed is not a single digital twin that perfectly encapsulates all aspects of the physical reality it mirrors, but rather an evolving set of “digital siblings.” Each sibling shares a lot of the same DNA (data, tools, and practices) but is built for a specific purpose, can evolve on its own, and provides value in isolation.
The data backbone to power digital twins needs to be governed in efficient ways to avoid the master data management challenges of the past—including tracking data lineage, managing access rights, and monitoring data quality, to mention a few examples. The governance structure has to focus on creating data products that may be used, reused, and collaborated on in efficient and cross-disciplinary ways. The data products have to be easily composable and be constructed like humans think about data ; As a graph where physical equipment are interconnected both physically and logically. And through this representation select parts of the graph may be used to populate the different digital twins in a consistent and coherent way.
Rockwell Automation and Cognite Form a Strategic Partnership to Develop a Unified, Edge-to-Cloud Industrial Data Hub Offering for the Manufacturing Industry
Rockwell Automation, Inc. (NYSE:ROK), the world’s largest company dedicated to industrial automation and digital transformation, and Cognite, a global leader in industrial data software, today announced a strategic partnership to further unlock the value of manufacturing data and accelerate technological change for the industry. The partnership combines Rockwell’s FactoryTalk® software offering of next-generation edge connectivity to plant assets, operations management applications, and industry-tailored analytics with Cognite’s leading Industrial DataOps platform, Cognite Data Fusion®, to create an industrial data hub ready for enterprise-wide scaling.
With one of the largest footprints in industrial automation, Rockwell products create and process data worldwide. The partnership between Rockwell and Cognite will bring to market a unique, unified, edge-to-cloud industrial data hub that makes operational, engineering, enterprise, and visual data understandable and comparable for manufacturing across industries. The offering will transform raw data into high-impact applications for real-time decision making and improved workflows that ensure safe, productive, and sustainable operations. With Cognite’s proven success in the Energy industry, this partnership will further enhance the edge-to-enterprise capabilities from Sensia, Rockwell’s joint venture with Schlumberger.
Schlumberger and Cognite to Deliver Data-Driven Solutions at Scale for the Global Energy Industry
Schlumberger (NYSE: SLB) and Cognite, two leaders in technology innovation, today announced a strategic partnership to integrate Schlumberger’s Enterprise Data Solution for subsurface with Cognite Data Fusion®, Cognite’s leading open industrial DataOps platform. Through this partnership, customers can integrate data from reservoirs, wells, and facilities in a single, open platform, and leverage embedded AI and advanced analytics tools to optimize production, reduce costs and decrease operational footprint.
Aramco and Cognite join forces in new data venture
Aramco and Cognite, a global leader in industrial software, have launched CNTXT, a joint venture based in the Kingdom of Saudi Arabia. Headquartered in Riyadh, CNTXT aims to support the Kingdom’s industrial digitalization, and the wider MENA region.
CNTXT will provide digital transformation services enabled by advanced cloud solutions and leading industrial software. These solutions and services aim to help public and private sector companies to future-proof their data infrastructure, increase revenue, cut costs and reduce risks while enhancing operational sustainability and security. CNTXT is Google Cloud’s reseller for cloud solutions in the Kingdom and the exclusive reseller of Cognite Data Fusion in MENA region. Additionally, Google Cloud is expected to launch a “Center of Excellence” later this year to provide training to developers and business leaders in how to use cloud technologies.
Industrial dataOps capabilities to truly scale Simulation Digital Twins
For some time, the notion of digital twins has been ubiquitous in exemplifying the potential of digital technology for heavy-asset industries. With a digital representation of a real-world system of assets or processes, we can apply simulation and optimization techniques to deliver prescriptive decision support to end-users.
Simulation Digital Twins help industries to make decisions in an increasingly complex & uncertain environment, to balance competing constraints (revenue, cost, efficiency, resiliency, carbon footprint, ++), and to react quickly and adapt with agility to real-world changes.
In this article we are describing solutions that combine the capabilities of Microsoft Azure Digital Twins, Cognite Data Fusion and Cosmotech Simulation Digital Twins. In an integrated solution, Azure Digital Twins provides a digital twin model that reflects real time state from sensors and other real time source and orchestrates event processing. Cognite Data Fusion (CDF) delivers integration of schemas and metadata from IT, OT and ET data sources, including the generation of models and twin graphs for Azure Digital Twins. The Cosmotech Simulation Digital Twin platform adds deep simulation capabilities in a scalable, open framework.
Aarbakke + Cognite | Boosting production, maintenance, and quality
Cognite Secures $150 Million Investment from TCV to Accelerate Digitalization of Global Industries
Cognite, a global leader in industrial software innovation, announced today that it has signed an investment round of $150M with leading global growth equity firm TCV, valuing the company at $1.6B. This investment marks one of the largest funding rounds for a SaaS company in Europe and confirms industrial digitalization as a global megatrend. The new valuation round constitutes unicorn status for Cognite.
“Cognite is on a strong trajectory to help transform industry, and since our founding four years ago, we have managed to attract top global talent, and partner with top industrial companies to accelerate modern industrial data management worldwide,” said Dr. John Markus Lervik, CEO and co-founder of Cognite. “The partnership with TCV allows us to amplify our software solutions to empower asset-intensive businesses to improve their sustainability and profitability of operations, and perfectly complements the extensive industrial knowledge brought in by our majority shareholder, Aker.”
Cognite Collaborates With Microsoft to Transform Industry Through Digitalization and Becomes Global Independent Software Vendor (ISV)
Cognite announced it is working with Microsoft to catalyze the full-scale digital transformation of heavy-asset industries. The Cognite Data Fusion platform, hosted on Microsoft Azure, will deliver industrial data operations and OT/IT data contextualization for hybrid AI development, combining human and Artificial Intelligence to collectively achieve superior results and create faster time to value.
This collaboration builds on the common goal to create transformation through digitalization as demonstrated by Microsoft’s recent commitment to The Center for Fourth Industrial Revolution for the Ocean (C4IR), and the Ocean Data Platform (ODP), which is also powered by Cognite technology. ODP is the open and collaborative platform that harnesses the power of data liberation and contextualization connecting data, people and technology for a healthy ocean and is run on Cognite Data Fusion. ODP is a cornerstone of Microsoft’s water sustainability commitment. Both companies are committed to technology-based systems to improve ocean health.
Cognite Partners with Accel to Transform Industry and Define New Industrial Software Category
Coupled with Accel’s broad network and expertise in successfully scaling software companies, the partnership enables Cognite to accelerate its global growth initiatives across industrial verticals, expand go-to-market activities and product development. As part of the agreement, Accel is gaining a seat on Cognite’s Board of Directors.
Aker BioMarine Digitalizes its Operations in Houston Plant to Improve Sustainability Efforts, Maintenance and More
“Aker BioMarine has more than 3 billion data points in Cognite Data Fusion,” said Ole Thoresen, Director Digitalization & Improvements, Aker BioMarine. “Big data is the next wave of technology in the krill oil market. By utilizing this platform, we are able to solve issues before they arise. We also have the ability to be more sustainable and safe, and that is extremely important in our industry.”
“This data acquisition and data visualization platform is a unique tool that allows us to visualize any trend with time and even superimposed trends with time, something impossible to do before,” said Laurent David, Director of Technology Development Engineering, Aker BioMarine. “With data processing, we will benefit from the huge quantity of mass flow-meter we have in the Houston plant. In the future, we will be able to make daily mass balance, meaning that we will be able to master our daily consumption. In the past we had to wait a month to detect problems and now we have access to daily data. Finally, we will soon have the capability of connecting info from our vessel in Antarctica to the Houston plant.”