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ExploreAI agent use case
AI agents for customer support
Resolve routine tickets end-to-end, draft replies for the rest, and escalate the cases that genuinely need a human.
Most support volume isn't hard — it's repetitive. Where's my order, how do I reset this, can you change my plan. A support agent handles that long tail end-to-end, grounded in your own knowledge base and order data, and hands the genuinely tricky cases to your team with the context already gathered.
What it actually does
The agent reads the incoming ticket, looks up the customer and their order or account, checks your docs and policies, and either resolves the issue directly or drafts a reply for an agent to approve. It works inside your existing helpdesk, so your team's workflow doesn't change — the queue just gets shorter.
Safe by design
Refunds, plan changes and anything that moves money or touches an account stay behind a guardrail — proposed by the agent, approved by a human until the track record earns more autonomy. Every resolution is logged with the reasoning and the sources used, so quality is auditable.
Where it fits
Best for teams with steady ticket volume and a knowledge base worth grounding answers in. We start the agent in draft mode, measure resolution quality against your real tickets, then graduate the safe categories to full autonomy.
Zendesk / Intercom / FreshdeskYour CRMOrder & billing systemsKnowledge base / docs
Customer support agents — FAQs
Will it replace our support team?
No — it removes the repetitive long tail so your team focuses on the complex, high-value cases. Anything sensitive stays human-approved.
Does it work with our existing helpdesk?
Yes. The agent plugs into tools like Zendesk, Intercom or Freshdesk and works inside your current queue and workflow.
How do you stop it giving wrong answers?
Answers are grounded in your knowledge base and account data, constrained by policy, and measured with evals. Low-confidence or sensitive cases escalate to a human.
Other use cases
Deploy a customer support agent.
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