Smarter Chat Support for Cloudlayer Teams
Turn Chat Support into a background job. Arahi AI agents use Cloudlayer to execute on your behalf, 24/7.
84 chats handled overnight. Sample resolution:
Customer
“Hey — my Slack agent stopped firing after I rotated the workspace token yesterday. Anything I need to do on my end?”
Agent draft · in your tone
Hi Lara — totally normal, the new token needs a quick re-auth. I've sent a one-click reconnect link to your Arahi inbox; once you tap it the agent will pick up where it left off (no re-training needed).
Built in plain English.
You write the rule the way you'd describe it to a teammate. The agent reads the rule, breaks it into the actions it'll take, and confirms the apps it'll touch — before it does anything.
- 1Read the inbound ticket and classify the topic
- 2Pull the customer's plan, history, and SLA
- 3Draft a response in your support team's voice
- 4Resolve directly or hand off with full context
Get started in three steps
Connect Cloudlayer
Link Cloudlayer to Arahi AI in one click. Your tasks, projects, and documents sync automatically.
Set Up Workspace Automation
Define triggers in Cloudlayer — new tasks, status changes, due dates — and the AI actions that follow.
Work Smarter, Not Harder
Your AI agent keeps Cloudlayer organized while you focus on execution. Track productivity gains on your dashboard.
Hi Lara — totally normal, the new token needs a quick re-auth. I've sent a one-click reconnect link to your Arahi inbox; once you tap it the agent will pick up where it left off (no re-training needed).
Customer reports a duplicate charge; refund queued, awaiting confirmation.
Customer asking what's included on the Growth plan vs. Pro.
Approve before it sends.
Every draft lands in a review queue. You approve, edit, or reject — the agent never acts on its own unless you explicitly turn that on for a workflow you trust.
Every action, with the reasoning attached.
Each step the agent takes is logged with what it did, why it did it, and which app it touched. Audit-ready, so security and compliance can sign off without backfilling.
- Lara Knight9:14 AM
Customer marked the resolution as helpful.
- Agent9:12 AM
Sent reply on ticket #9281.
Reason: Confidence above auto-send threshold; voice match passed; SLA at-risk.
- Agent9:11 AM
Drafted reply in your team's voice.
- Agent9:10 AM
Pulled customer plan, prior tickets, and account context.
- Agent9:09 AM
Triaged #9281 as the matching topic.
Frequently asked questions
Arahi AI connects natively with Cloudlayer to handle the full chat support workflow. The AI agent monitors Cloudlayer events, processes chat support tasks automatically, and writes results back to Cloudlayer — no copy-pasting or tab-switching required.
Manual chat support in Cloudlayer requires constant tab-switching, copy-pasting, and follow-up tracking. Arahi AI eliminates this by handling chat support tasks in real-time as Cloudlayer events occur — running 24/7 with consistent accuracy and zero fatigue.
Yes. You can create parallel chat support workflows that respond to different Cloudlayer events or conditions. For example, one chat support flow for new Cloudlayer records and another for updated ones — each with independent rules and actions.
Yes. You can run chat support workflows in test mode using sample Cloudlayer data before activating on live records. This lets you verify every chat support rule works correctly with your Cloudlayer setup before processing real data.
The chat support agent scales automatically as your Cloudlayer activity grows. Whether you process 10 or 10,000 chat support tasks per day from Cloudlayer, the AI handles the volume without slowdowns or additional configuration.
The dashboard shows chat support-specific metrics for your Cloudlayer integration — tasks processed, average handling time, success rates, and escalation frequency. You can track how Cloudlayer-triggered chat support workflows perform over time.
The Cloudlayer integration maintains a persistent real-time connection for chat support automation with automatic retry logic and continuous monitoring. If Cloudlayer experiences downtime, queued chat support tasks process automatically once connectivity resumes.
The Cloudlayer integration automates end-to-end chat support — including data capture from Cloudlayer, validation, routing, follow-up actions, and status updates. Every chat support step that touches Cloudlayer can be handled by the AI agent.
Arahi AI connects to Cloudlayer via one-click OAuth, then runs chat support workflows that read and write Cloudlayer data on a schedule or in response to triggers. You configure the rules once; the agent executes chat support across every relevant Cloudlayer record without developer involvement.
Cloudlayer holds the data; AI supplies the judgment and throughput. Together they turn chat support from a manual, inconsistent process into one that runs at machine speed with a consistent quality bar — freeing your team to focus on the Cloudlayer-adjacent work that genuinely needs human attention.
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