Put digital employees to work on operating tasks

#Let the task define how people and AI cooperate

For an operating handover, first define the records needed, who follows up exceptions and where an owner must approve. During recruitment and training, a new factory can translate these task requirements into both staff capabilities and product configuration.

A digital employee is an AI application organized around these tasks. It uses the required knowledge and memory, invokes models and authorized tools, and follows configured workflows to produce analysis, recommendations or work within its authority. Define human handover points for the task.

#Let your existing AI use specialist capabilities

Customers can keep their AI assistant or agent platform and connect selected capabilities through the existing API/MCP foundation. The integration provides industrial objects, operating data, specialist models and workflows without requiring a new AI interface.

For example, ask an existing AI to compare yesterday’s efficiency across three boilers. It uses an authorized identity to find the equipment and properties, retrieves data for the relevant periods, invokes an existing model or workflow, and returns results with calculation conditions and source evidence. The task depends on the model’s inputs and interface coverage.

Callable work

Discover objects and relationships, retrieve suitable data, run specialist calculations or workflows, and query results and status.

Integration conditions

Interface and tool coverage for the selected version, identity and access, input and output definitions, units, applicability and exception handling.

How to start

Choose one concrete task for the existing AI, connect it through the available interfaces, check the full result, then extend its use.

#Connect professional computation and authorized tools

In an exception-follow-up example, a digital employee retrieves asset records, invokes a suitable model and organizes results for the owner, including outstanding checks. Expertise comes from our products, suitable partners or customer specialists. Configure records, tools and approvals for the task.

#Maintain capabilities as records and work change

Digital employees receive new records at the task’s cadence, invoke suitable models and authorized tools, and perform analysis, recommendations or work within configured authority. Execution results return to the task. Knowledge, interfaces and configuration are updated as equipment, procedures and tasks change.

The product design uses feedback to improve capability: specialist models recalibrate parameters and calculations within their applicable ranges, while rules and knowledge are updated through validation and authorization. New AI models can improve understanding and tool use; continuing value also comes from accumulated site experience and clearer supervision, collaboration and handover.

Confirm before adoption