Agent responsibility
Retrieve relevant knowledge
Retrieve relevant guidance and draft an answer with source references, escalating gaps instead of guessing.
Grounded service answer
Customer operations / Customer service / Solution blueprint
Service knowledge answers
Prepare grounded answers from approved support guidance.
Business problem & expected outcomes
The challenge behind
service knowledge answers.
Common enquiries receive different answers when staff rely on memory or outdated documents.
What this workflow is designed to deliver
Grounded service answer
Retrieve relevant guidance and draft an answer with source references, escalating gaps instead of guessing.
How to measure the improvementAnswer grounding; reviewer corrections; appropriate escalations.
Start with the right information.
Approved support articles, product versions, and the incoming question.
Interactive workflow diagram
From service question
to a clear next step.
Retrieve relevant guidance and draft an answer with source references, escalating gaps instead of guessing.
Customer operationsSelect a stage to explore
Context
Service question
Approved support articles, product versions, and the incoming question.
Prepared outputGrounded service answer
Designed around the work
A focused agent. The right capabilities.
Give the agent the context and tools this process needs, with an explicit output and an accountable owner.
Connected tools & context
Bind only the operations this workflow needs. Keep credentials in ART and choose the permitted tools explicitly.
Knowledge Base
Project & environment scopeRetrieve approved guidance and attach source references to the prepared answer.
Agent Skills
Project & environment scopePackage the checklist, instructions, and expected output as a reusable skill.
The decision boundary
Sensitive account requests and unsupported answers require staff review.
ART product mapping
Components used.
Chosen for this case.
Agent Lab prepares the work described below. These are the capabilities that support this workflow.
Agent Lab
Knowledge Base
Retrieve approved guidance and attach source references to the prepared answer.
Agent Lab
Agent Skills
Package the checklist, instructions, and expected output as a reusable skill.
The implementation, step by step
From source context
to a reviewed result.
- 01
Service question
Approved support articles, product versions, and the incoming question.
Agree the trigger or manual request, record identifiers, and the process owner. - 02
Retrieve relevant knowledge
Retrieve relevant guidance and draft an answer with source references, escalating gaps instead of guessing.
Define instructions, permitted tools, and the expected output. Keep missing information explicit. - 03
Check source coverage
Sensitive account requests and unsupported answers require staff review.
Keep the pilot in preparation mode and use the team’s existing review process. - 04
Grounded service answer
Answer grounding; reviewer corrections; appropriate escalations.
Compare outputs with reviewed examples and test incomplete, conflicting, and unauthorized inputs.
Before you build
What this implementation needs.
Knowledge Base
An approved document set, content owners, and retrieval access boundaries.
Agent Skills
A process checklist, example inputs, and a reviewer-approved output format.
Also prepare an ART project and environment, the model configuration appropriate to your agent, an accountable process owner, and approved sample data.
Authority stays with your team
Define the boundary
before enabling the action.
Sensitive account requests and unsupported answers require staff review.
Explore execution governanceConnect deliberately.
Map the source material and responsible owners first. Where the selected components require system access, configure scoped APIs or tools. A document-based pilot can start with approved material already available in the workspace.
Make each handoff inspectable.
Keep source references with the prepared output and review representative results before expanding scope. If the implementation includes executable actions, define their required facts and authority first. Apply retention to any stored records, files, or memory used by the case.
Build evidence from your own work
Start small.
Agree what good looks like.
What to measure for this case
Answer grounding; reviewer corrections; appropriate escalations.
Establish a baseline
Choose a bounded sample of completed cases, record the current process, and agree review criteria with the process owner.
Run in review mode
Use approved sample data and read-only connections. Compare prepared outputs with reviewer expectations, including incomplete and conflicting inputs.
Expand with approval
Enable a limited set of actions only after the team accepts the results. Check approvals, failures, and handoffs before increasing scope.
Make it your workflow
Try this approach
in Agent Lab.
Start with service question. Connect your approved tools, configure the review boundary, and adapt the output to your team's process.
Try Workflow in Agent Lab
Open your ART workspace to configure this use case.
Discuss the setup with usIndustry & department library
Find your next use case.
3 use cases in Customer operations
Customer operationsWorkflow design
- ContextRefund request
- Agent LabCheck order & policy
- Your teamAuthorized review
Prepared outputRefund recommendation
Solution blueprint
Customer refund reviews
Prepare a refund decision with the order history and policy in view.
Used in this case
Explore the implementation - Connectors & MCP
- Knowledge Base
- Execution governance
- Human approvals
Customer operationsWorkflow design
- ContextCase history
- Agent LabSummarize prior work
- Your teamSpecialist handoff
Prepared outputContext-rich case brief
Solution blueprint
Support case handoffs
Give the next specialist the context to continue the conversation.
Used in this case
Explore the implementation - Knowledge Base
- Agent memory
- Agent Skills
Customer operationsWorkflow design
- ContextActive service case
- Agent LabShare current context
- Your teamSpecialist collaboration
Prepared outputConnected case handoff
Solution blueprint
Live service collaboration
Keep the service team aligned while a complex case is being resolved.
Used in this case
Explore the implementation - Secured channels
- Agent memory
- Agent Skills
Customer operations / Let’s explore the fit
Discuss your
industry use case.
Tell us where work slows down. We’ll discuss how ART could fit your process, your systems, and the decisions your team needs to own.
