Prepared for the support agent
Prepare a sourced reply.
The approved help article covers this account type. No relevant incident is recorded.
The agent stays responsible.
The agent checks the instructions and tone, then approves the response.
AI for Support
One customer.
Too many searches.
We build AI-assisted support workflows that gather context, retrieve the right knowledge, and prepare the next step.
Review our support workflowThe right next step depends on the evidence
Choose a situation
Customer ticket
“How do I export my account data?”
Approved documentation + account context
Customer ticket
“My export is not working.”
Ticket history · information incomplete
Prepared for the support agent
Ask for the missing detail.
The request does not say which export failed or what happened.
The agent stays responsible.
Prepare a clarifying question for the agent. Do not guess at the cause.
Customer ticket
“The export still fails after those steps.”
Prior conversation + troubleshooting notes
Prepared for the support agent
Prepare an engineering handoff.
The previous troubleshooting did not resolve the issue. The cause is uncertain.
The agent stays responsible.
Summarize the attempts and open questions. The agent approves escalation to the right owner.
The work behind the work
The work before the reply.
Your support team should not have to search five systems before answering one customer.
- read long ticket history
- check account status
- search documentation
- look for known incidents
- review prior cases
- decide whether engineering is needed
- write the same explanation again
Where AI can help
Start with useful work.
Good candidates, grouped by the work they support. The starting point depends on your process, data, and controls.
Understand
- Ticket classification
- Conversation summarization
- Account context
Prepare
- Knowledge retrieval
- Suggested replies
- Incident-aware responses
Hand over
- Engineering handoff summaries
- Escalation routing
How it works
Context first.
A useful response next.
Gather the history, documentation, prior cases, account status, and known incidents before asking an agent to write the same explanation again.
- Ticket
- Intent classification
- Account context
- Approved knowledge retrieval
- Incident check
- Suggested response
- Human approval
- Reply / escalation
Trust & customer impact
The assistant should know when not to answer.
A quick reply is not useful if it sends the customer in the wrong direction.
- Source boundariesRetrieve from the knowledge and account sources the agent is allowed to use.
- Confidence thresholdsDefine when there is enough evidence to prepare an answer and when to ask for more.
- Escalation rulesSend unresolved cases to a named team with a useful summary.
- Restricted actionsKeep account changes and other consequential actions inside explicit permissions.
- Approval requirementsA person checks customer communication before it leaves the workflow.
- Customer-facing tone controlsDraft in the agreed voice, without inventing explanations or promises.
What to measure
Make the improvement visible.
Possible measures, not promised results. Establish your baseline first, then test whether the workflow improves.
- handle time
- time to first useful response
- escalation quality
- knowledge retrieval time
- re-open rate
- agent adoption
Your next move
Start with the tickets that take too long because the information is scattered.
Show us what an agent looks up before answering a customer. We’ll help you bring that context to them, with a person still approving the reply.
Tell us what’s slowing you down.
A few lines is enough. We’ll reply by email with what’s worth doing first.