AI Meets Live Plant Data in a Single Workspace
Industrial app development has long been slowed by fragmented data and siloed tools. Cognite Flows tackles this by placing AI recommendations, live operational data and task-specific applications into a single workspace for factory and plant teams. Built on Cognite’s Industrial Knowledge Graph, the platform keeps every dashboard, alert and workflow tied to real operating context rather than static data extracts. Front-line staff no longer need to jump between SCADA screens, spreadsheets and maintenance systems to understand what is happening and what to do next. Instead, Flows prioritizes a user-centric view, presenting contextualized data and AI-suggested actions tailored to each role. This reflects a broader shift in industrial app development: moving AI from central data-science teams directly into refineries, production lines and utilities so that operators, engineers and technicians can act on it in day-to-day work.
From Months to Days: Low-Code, AI-Native Industrial App Development
Cognite Flows rethinks industrial app development with an AI-native architecture and agentic AI coding tools that automate much of the build process. Instead of writing bespoke code for every use case, developers and power users assemble applications using low-code components that already understand equipment, processes and tags through the underlying knowledge graph. Cognite reports that some customers have compressed implementation timelines from months to days, including a pharmaceutical project where a prototype that once required more than 20 people and several months was delivered in four days. User acceptance timelines were also cut to about one-third of traditional schedules. These gains mirror a growing trend in manufacturing software acceleration: industrial teams are using AI workflow automation to turn ideas for monitoring, optimization and safety into live applications quickly, then iterating based on feedback from operators on the plant floor.
Capturing Expertise and Modernizing Asset Visibility
The impact of AI-driven industrial app development goes beyond faster coding. Idemitsu is using Cognite Flows to turn decades of plant know-how into digital tools, aiming to preserve specialist expertise and expose it through AI-based assistants. By tying that knowledge to real-time data in a knowledge graph, the company expects applications to evolve into proactive AI agents capable of managing complex operations, not just visualizing trends. Medical manufacturer B. Braun is focusing on operational transparency and asset health. Within four weeks, it used Flows to overhaul how asset data is contextualized and displayed, refining user experience with near-instant updates based on operator feedback. These examples highlight how AI-powered platforms can embed best practices, standardize decision support and give maintenance and production teams a clearer picture of equipment performance across multiple sites.
Low-Code SCADA Visualization Without Ripping Out Legacy Systems
While Cognite Flows focuses on AI-native workflows, Advantech’s EdgeView targets a related challenge: modernizing visualization without replacing entrenched control systems. Positioned as a low-code SCADA visualization layer, EdgeView sits above existing SCADA, production databases and IoT platforms, leaving control logic and communication architectures intact. It connects via OPC UA, major databases and REST APIs, pulling together scattered operational data into unified dashboards. System integrators can design monitoring interfaces using low-code SCADA tools with built-in industrial components and live data preview, testing layouts without disrupting running equipment. Advantech indicates that typical projects can go live in as little as two weeks, significantly reducing custom engineering effort for HMI upgrades. With deployment options spanning Windows, Linux, web browsers and mobile devices, EdgeView helps companies extend real-time visibility to managers and field technicians without a full-scale SCADA replacement.
Toward End-to-End AI Workflow Automation in Manufacturing
Taken together, Cognite Flows and Advantech EdgeView illustrate how industrial operators are accelerating manufacturing software by layering AI and low-code tools onto existing environments. Flows emphasizes AI workflow automation, enabling partners such as Radix and other integrators to build and maintain mission-critical applications faster, from the plant floor through supply chain and fulfilment operations. EdgeView complements this trend by simplifying the visualization of those workflows on top of legacy SCADA and databases. The result is a new approach to industrial app development: instead of multi-year modernization projects, operators can deploy targeted monitoring, optimization and knowledge-capture applications in weeks or days, then scale what works. As more plants adopt these AI-powered platforms, the bottleneck shifts from coding to defining the right use cases and ensuring that front-line workers are equipped to act on the insights delivered in real time.