Industrial agents
AI agents for industrial work
Give them a task. They gather context, use approved tools and prepare work your team can review.
Company knowledge Useful action
Explore the capabilitiesStart with something useful
See what an agent can prepare
Choose a task. See what an agent could prepare. Look at the information behind the answer.
Your request
Which drawing belongs to order #1042?
Use revision D.
The order and engineering update point to the approved P-204 drawing.
See the details
- Drawing
- P-204 · Revision D
- Order
- #1042 · 120 pump housings
- Evidence
- Drawing, update and order agree
Check the source records before use.
Inspect the source records
- Approved drawing
P-204, revision D. Marked approved in the sample drawing record.
- Engineering update
Use revision D for order #1042.
- Order #1042
120 P-204 pump housings. References the engineering update.
Illustrative examples · sample records
See how context connectsBuilt around the task
Explore how agents work
Start with a defined piece of work. Test the result before extending the responsibility.
Follow the work, step by step.
See how a request becomes focused checks, gathered evidence and a result for review.
Connect what your company knows.
Bring the right drawing, message and business record into the same context.
Explore the next possibilities.
Computer use and longer assignments, evaluated in supervised trials. Scope and availability are agreed individually.
Start with one useful task.
A focused pilot puts agents to work with your team, using your information. Find out where they make a difference.
Explore a first deploymentWhat to expect from an agent
Is an agent the same as a chatbot?
A chat window can be how you give it a task. Behind that, an agent can retrieve records, use connected tools and work through several steps to prepare a result.
Can an agent make mistakes?
Yes. It can miss a requirement, misread a document or take a wrong step. Useful workflows include checks, visible sources and a way to ask a person for help.
Can it act without our approval?
The workflow defines that. Some actions can be allowed within a clear scope; others, such as placing an order or releasing a change, can require review. We agree those boundaries before implementation.
Will it work with our existing systems?
We check which information and connections your systems provide. Some tasks need selected documents; others need an integration. The workflow is scoped around what your systems can actually support.
Does our information stay private?
That depends on the architecture. Local models can run in your environment. An approved external-model request sends selected information to a provider. We make that choice and its data rules explicit.
Explore the architectureHow do we know an agent is useful?
Choose recurring work with a result your team can judge. Compare time spent, output quality and review effort with the current process. Sometimes a simple rule or integration is the better answer.