AI for preparing a post-incident review
The service is running again, but everyone brings a different account to the incident review. The on-call engineer remembers a phone call, the ticket records an alert, and team messages describe several recovery attempts. An AI agent can assemble a working timeline with questions for the participants. The meeting lead gets material the team can correct together.
Syntalith
At Syntalith, we propose connecting the incident ticket to selected conversation channels and participants' notes. The result is preparation for a post-incident review: a concise, source-linked timeline and unresolved questions. The facilitator uses it to discuss what happened and what the organization wants to learn. This scope begins after service restoration; it does not control the response to an active outage.
What happened before recovery?
Suppose access was restored after a settings change. Earlier, someone wrote that a restart helped; a later message reported continuing errors. A summary saying the restart resolved the incident would lose part of the story. The agent brings both messages together and drafts a question about what was actually observed after the restart. The engineer's reply adds context for the meeting.
The timeline distinguishes observations from explanations offered afterward. A change followed by recovery does not establish causation by itself. Participants assess the conclusions, and the meeting lead approves the account to be shared. Source links let them reopen a conversation when a short sentence leaves out an important condition.
A native draft is a real alternative
Atlassian describes post-incident reviews in Jira Service Management, including Rovo-generated drafts containing incident details and a timeline for people to review. Availability depends on the plan. Check this option if your team's material already lives in that environment.
A separate project is worth discussing when important context sits outside the ticket or the facilitator must repeatedly ask participants to fill gaps. An agent can draft questions tied to particular records and retain the replies. It need not create another incident-management system. The useful result belongs where the team conducts its review.
Differences between accounts are not necessarily mistakes. People may have observed different parts of the service. A useful note preserves that distinction instead of turning every statement into one confident narrative. The team can spend the meeting clarifying events and deciding what to do next.
Choosing the initial scope
Start with one team and a type of incident. The company identifies available sources and the review lead. We agree which conversations may appear in the summary and who assesses its accuracy. The destination for actions agreed at the meeting is a separate discussion; assembling a timeline does not complete those actions.
A resolved incident provides a useful comparison between the proposed note and the participants' account. Does it surface a question the meeting needed to resolve? Can the reader open the record behind an important statement? That shows the work being supported without promising to prevent every future outage.
Discuss an agent for review preparation. Describe the last meeting that required someone to reconstruct events from several places. Naming those places and the facilitator is enough to start. See Syntalith pricing for billing information.
Find the right role for an agent in your process
Describe the work that currently needs repeated manual action. We will discuss the agent’s responsibilities, system connections and an initial delivery scope.
Explore AI agent development