Agent responsibility
Summarize prior work
Summarize what has been tried, retrieve relevant knowledge, and prepare a handoff with unresolved questions.
Context-rich case brief
Customer operations / Customer service / Solution blueprint
Support case handoffs
Give the next specialist the context to continue the conversation.
Business problem & expected outcomes
The challenge behind
support case handoffs.
A customer repeats the issue whenever a case changes hands. Important troubleshooting details stay buried in the conversation.
What this workflow is designed to deliver
Context-rich case brief
Summarize what has been tried, retrieve relevant knowledge, and prepare a handoff with unresolved questions.
How to measure the improvementRepeated requests for the same information; handoff completeness; time to the next meaningful response.
Start with the right information.
Conversation history, troubleshooting notes, product references, and case ownership.
Interactive workflow diagram
From case history
to a clear next step.
Summarize what has been tried, retrieve relevant knowledge, and prepare a handoff with unresolved questions.
Customer operationsSelect a stage to explore
Context
Case history
Conversation history, troubleshooting notes, product references, and case ownership.
Prepared outputContext-rich case brief
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 memory
Project & environment scopeKeep the conversation record and useful agent memory within the case’s scope and retention policy.
Agent Skills
Project & environment scopePackage the checklist, instructions, and expected output as a reusable skill.
The decision boundary
Limit tools and data to the assigned support role; require review before sensitive account changes.
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.
Datalake
Agent memory
Carry useful context across interactions without reconstructing the entire conversation.
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
Case history
Conversation history, troubleshooting notes, product references, and case ownership.
Agree the trigger or manual request, record identifiers, and the process owner. - 02
Summarize prior work
Summarize what has been tried, retrieve relevant knowledge, and prepare a handoff with unresolved questions.
Define instructions, permitted tools, and the expected output. Keep missing information explicit. - 03
Specialist handoff
Limit tools and data to the assigned support role; require review before sensitive account changes.
Keep the pilot in preparation mode and use the team’s existing review process. - 04
Context-rich case brief
Repeated requests for the same information; handoff completeness; time to the next meaningful response.
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 memory
A defined memory scope, permitted context, retention, and rules for updating or removing memory.
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.
Limit tools and data to the assigned support role; require review before sensitive account changes.
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
Repeated requests for the same information; handoff completeness; time to the next meaningful response.
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 case history. 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
- ContextService question
- Agent LabRetrieve relevant knowledge
- Your teamCheck source coverage
Prepared outputGrounded service answer
Solution blueprint
Service knowledge answers
Prepare grounded answers from approved support guidance.
Used in this case
Explore the implementation - Knowledge Base
- 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.
