AI Agent for Chat Support — Built for Avaza
Automate Chat Support for teams using Avaza. Arahi AI agents handle the workflow end-to-end — no code, set up in minutes.
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 Avaza
Link Avaza to Arahi AI in one click. Your tasks, projects, and documents sync automatically.
Set Up Workspace Automation
Define triggers in Avaza — new tasks, status changes, due dates — and the AI actions that follow.
Work Smarter, Not Harder
Your AI agent keeps Avaza 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
Manual chat support in Avaza requires constant tab-switching, copy-pasting, and follow-up tracking. Arahi AI eliminates this by handling chat support tasks in real-time as Avaza events occur — running 24/7 with consistent accuracy and zero fatigue.
All data exchanged between Avaza and Arahi AI during chat support processing is encrypted in transit and at rest. We use OAuth tokens for Avaza access, never store raw credentials, and maintain full audit logs of every chat support action.
Yes. You define exactly which Avaza events start chat support workflows — new records, status changes, messages, or custom triggers. Each trigger can have conditions so chat support actions only fire when your specific criteria are met in Avaza.
Yes. The chat support agent connected to Avaza simultaneously interacts with 1,500+ other apps — CRMs, databases, email platforms, and more. A single chat support workflow can pull data from Avaza, process it, and push results to multiple destinations.
No coding required. The no-code builder walks you through connecting Avaza and configuring chat support rules visually. Your team can set up, modify, and manage Avaza-based chat support workflows without any developer involvement.
When the AI hits an edge case during chat support processing in Avaza, it escalates to your team with full context — the Avaza record, what was attempted, and why it needs review. Your chat support pipeline never stalls or loses data.
The chat support agent scales automatically as your Avaza activity grows. Whether you process 10 or 10,000 chat support tasks per day from Avaza, the AI handles the volume without slowdowns or additional configuration.
The Avaza integration maintains a persistent real-time connection for chat support automation with automatic retry logic and continuous monitoring. If Avaza experiences downtime, queued chat support tasks process automatically once connectivity resumes.
Arahi AI connects to Avaza via one-click OAuth, then runs chat support workflows that read and write Avaza data on a schedule or in response to triggers. You configure the rules once; the agent executes chat support across every relevant Avaza record without developer involvement.
Avaza 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 Avaza-adjacent work that genuinely needs human attention.
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