Put artificial intelligence to work in your operations. We bring together industrial expertise, machine learning, and connected systems to build solutions around your real-world challenges.
Models and applications built around your operation.
Engineering grounded in equipment, processes, and people.
Reliable signals, from the factory floor to the cloud.
AI starts with an operational question. We help you identify the opportunity, build the data foundation, and develop a solution your teams can put to work.
Consulting, custom model development, and integration—connecting AI to the equipment, workflows, and people it needs to serve.
Explore our AI services ↗Explore patterns in equipment data to identify signs of degradation and support better maintenance decisions.
Develop machine learning and computer vision solutions to help detect unusual behavior and assess production quality.
Model relationships between process variables and outcomes to support optimization and informed operational decisions.
Build AI assistants around your technical documentation and workflows to help teams find and use relevant information.
A sensor reading. A machine state. A production event. Useful intelligence begins with a reliable connection to the equipment.
KŌJŌ Stack acquires, transforms, and structures industrial data at the edge—adding the context downstream systems need.
Route contextualized data to cloud platforms, historians, and analytics systems, with local buffering and replay to handle interruptions.
Use that foundation for anomaly detection, predictive maintenance, and process optimization—starting with a clearly defined operational question.
Our automation, data, and cloud services connect AI to the physical systems and operational context that make it useful.
Connect machines, controls, and software around the way your operation actually works.
Bring operational data out of isolated systems and make it available where it matters.
Develop and integrate machine learning, AI applications, and cloud services around a defined industrial use case.
The industrial data plane
for physical operations.
Give industrial AI a stronger data foundation. KŌJŌ Stack acquires data from PLCs, sensors, and historians, transforms it at the edge, and adds context before delivering it to analytics, cloud, and AI systems.
Legacy equipment. Different protocols. Disconnected applications. The path forward starts with understanding what is already there.
We work with OT specialists, plant managers, engineering teams, and business leaders to turn those realities into a clear technical direction.
Illustrative project scenarios showing where we can collaborate. These examples are not published client case studies.
Connect generation assets, substations, meters, and field sensors into a contextualized operational data stream.
Explore anomaly detection and equipment-health models to help prioritize investigation.
Bring power distribution, UPS, environmental, and cooling telemetry together for a more complete operational view.
Explore early-warning models and cooling-performance analysis using equipment and environmental data.
Collect machine states, cycle data, and quality measurements across production equipment.
Explore visual quality inspection, predictive maintenance, and process-variation analysis.
Connect conveyors, sortation equipment, scanners, and warehouse systems to understand material movement.
Explore bottleneck detection, equipment-health monitoring, and demand-aware planning models.
Combine process measurements, equipment events, and batch context into data that can be compared and investigated.
Explore abnormal-process detection and models that relate operating conditions to quality outcomes.
Integrate building controls, meters, and environmental sensors to understand how facilities operate.
Explore energy-demand patterns and equipment anomalies to support maintenance and efficiency decisions.
A collaborative approach grounded in your equipment, people, and priorities.
Map the environment, clarify the challenge, and agree on the outcome that matters.
Define the architecture, integration points, and a practical scope for the solution.
Develop, connect, and validate the solution with the people who will use it.
Review the results together and identify the next improvements.
Tell us what you’re working on. We’ll start with your challenge.