1 Case Management AI Agent, Live in Production.
1 live agent automates case management within customer service. It runs on demand. It publishes the inputs it needs, the steps it works through and what it hands back.
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Case Resolution Guidance
Describe a stuck case and get the resolution paths your own playbooks support, ranked, with what the case has not yet established named rather than assumed.
Naming what the case has not established, instead of assuming it
A case gets stuck for one of two reasons: nobody knows what to try next, or everybody is working from an assumption nobody has tested. The second is more common and much harder to see. The case file records what was reported, what was attempted and what the customer said, and somewhere in that history a plausible interpretation hardened into a fact — the fault is with the integration, the customer is on the old version, the error started after the upgrade. Everything afterwards proceeds from it. Escalation does not necessarily help, because a specialist reads the same file and inherits the same assumption. What would help is someone asking which of these things is actually established.
Case Resolution Guidance does that. Given a stuck case, it returns the resolution paths your own playbooks support, ranked, with what the case has not yet established named rather than assumed. The second half is the valuable output: it turns an invisible assumption into a specific thing to go and check. One agent covers this process, and it is deliberately bounded to paths your playbooks support rather than inventing an approach — a suggestion outside your documented procedures is not something a support agent can safely act on.
What this moves
- Cases stuck without a next step
- Resolution paths that your own playbooks support are ranked, so a stalled case has options rather than needing a specialist to be free.
- Assumptions carried silently through a case
- What the case has not yet established is named explicitly, which is where a stuck case is usually stuck.
Customer Service
How AI agents handle case management
Drawn from the 1 agent above — what they require, how they run, and what comes back.
What they need
- The case as it stands
- Case context
What comes back
- What this looks like
- Guidance
- Resolution paths, ranked
- What the case actually establishes
- Watch out for
- Playbooks used
How they run
- Run on demand
- 1
- Steps per run
- 3
- Credits per run
- 6
- Use a knowledge base
- 1
Where case management fits in customer service
Most tickets are about one customer’s specific order or account. An agent that can read that state actually fixes the problem, instead of replying with a help article the customer already found.
Next Step
Deploying case management agents
These run as-is against the inputs listed above. Most deployments adapt one — a different source system, a different tolerance, a different approval path. The first call establishes which.