In industrial data management, context is everything. Extracting meaningful insights from engineering documentation can make or break operational efficiency. Yet, many companies still rely on fragmented data ecosystems, with critical information locked away in legacy systems and proprietary formats. Cognite is changing that by enabling smart, automated contextualization, which brings structure and accessibility to industrial data, including commonly used document types such as P&IDs, isometrics, and other types of diagrams and schematics.
Operational data extends far beyond P&IDs. While industry often prioritizes these diagrams, there are so many more types of documents that contain critical information. From handwritten documents and data sheets to fluid sample reports and root cause analysis records. Within the category of schematics alone, there are piping and instrumentation diagrams, flow diagrams, isometric diagrams, single line diagrams, assembly diagrams, and more. All vital for operating and maintaining operations. In a world with fewer hands available and more data piling up, it is more crucial than ever to automate the contextualization of information to meet various needs.
The key is to understand the relevancy of the data and establish a means to define contexts relevant for advanced use cases to improve uptime, maintenance, and other workflows. Unlike solutions focusing solely on diagrams, Cognite provides a comprehensive approach that supports a broad spectrum of operational documents, helping companies go beyond a narrow set of data types to unlock the full potential of their information landscape.
One of the key challenges in handling engineering documentation is ensuring that documents retain valuable metadata. That is where Cognite’s innovative approach shines. Cognite can extract information, generate map data, and otherwise process CAD files and reports in an automated way to not only ensure better document quality but also simultaneously extract crucial metadata, such as symbol classes and objects. This capability eliminates the need for tedious reverse engineering, generation, and symbol recognition across engineering diagrams.
Smart object recognition makes previously stale documents come to life
While some data companies focus solely on diagrams, Cognite’s combination of OCR, ML, and AI-powered solution works universally across all document types to help convert static images into machine-readable text and symbols. However, while these technologies are powerful, direct access to source data remains the gold standard. The ability to ingest smart P&IDs and other types of engineering documents and diagrams from all systems greatly enhances contextualization, reducing manual effort and accelerating workflows.
Generating relationships between pipes, instruments, lab data, and work orders can be hard enough. But the real challenge is to do this in a maintainable and scalable manner. On one offshore facility, there can be hundreds to thousands of document changes every month. The ever-green knowledge graph should be the expectation.
In engineering, an effective document management system is critical for ensuring accuracy, compliance, and efficiency across projects. However, beyond simply storing and organizing files, the real value lies in delivering the right document in the right context—precisely when and where the user needs it. Engineers often work in fast-paced environments where delays in accessing design specifications, change orders, or compliance documents can lead to costly errors and inefficiencies. Out-of-the-box interfaces to document systems, or at least, template code to implement support for a given protocol or interface, is a small but vital feature of Cognite Data Fusion.
Cognite Data Fusion eliminates requiring users to open separate source systems and manually search for or download files, and instead, users can directly access the relevant data via a knowledge graph that dynamically connects relevant information across systems. This approach allows engineers to access the right data intuitively through relationships within the graph, enabling them to retrieve insights seamlessly within their existing workflow and make informed decisions without unnecessary friction.
Diagrams and P&IDs that are contextualized make it possible to bring previously siloed data together in one seamless experience to conduct e.g., advanced Root Cause Analysis
In response to these intractable problems of static PDFs and siloed data, a push for open data standards is also gaining traction. However, legacy vendors have historically resisted full adoption of open protocols, opting instead for controlled ecosystems that maintain vendor lock-in. While standards like DEXPI provide a foundation for diagram exchange, the lack of broader industry adoption and limitations of “completeness and correctness” present real challenges. One Cognite customer, for example, can extract raw data from a legacy database but struggles with reassembling P&IDs—a “Humpty Dumpty” problem highlighting the complexity of data rehydration.
Cognite’s customers can use generative AI to ask questions about their diagrams using natural language
Cognite is actively working with customers to help them overcome the limitations of legacy systems and can help assess what is possible and where limitations lie. Interoperability often depends on versioning, deployment environments, and bespoke configurations. Even within a single company, one implementation may support DEXPI while another does not.
Industrial digitalization requires breaking down data silos and bringing all data into a modern, open, and accessible data and AI platform. Cognite’s approach bridges the gap between outdated systems and a data-driven future, making contextualization of all data the key to unlocking operational efficiency. By consolidating all documentation into a single platform, companies gain a seamless foundation for deploying advanced use cases—turning decades of static records into actionable insights. This transformation is not just about modernization; it’s about unlocking new levels of value and efficiency, bringing industrial operations into a data-driven 21st century.