AI Agent for Chat Support — Built for Bugsnag
Automate Chat Support for teams using Bugsnag. 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 Bugsnag
Authorize Bugsnag and Arahi AI immediately starts monitoring incoming tickets and support events.
Configure Ticket Workflows
Set up AI triage rules — classify tickets by type, assign priority, and route to the right agent in Bugsnag.
Resolve Faster & Track Results
AI handles routine tickets and drafts responses in Bugsnag. Monitor resolution times and satisfaction scores live.
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
Yes. You can run chat support workflows in test mode using sample Bugsnag data before activating on live records. This lets you verify every chat support rule works correctly with your Bugsnag setup before processing real data.
Manual chat support in Bugsnag requires constant tab-switching, copy-pasting, and follow-up tracking. Arahi AI eliminates this by handling chat support tasks in real-time as Bugsnag events occur — running 24/7 with consistent accuracy and zero fatigue.
All data exchanged between Bugsnag and Arahi AI during chat support processing is encrypted in transit and at rest. We use OAuth tokens for Bugsnag access, never store raw credentials, and maintain full audit logs of every chat support action.
The chat support agent scales automatically as your Bugsnag activity grows. Whether you process 10 or 10,000 chat support tasks per day from Bugsnag, the AI handles the volume without slowdowns or additional configuration.
Yes. You define exactly which Bugsnag 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 Bugsnag.
When the AI hits an edge case during chat support processing in Bugsnag, it escalates to your team with full context — the Bugsnag record, what was attempted, and why it needs review. Your chat support pipeline never stalls or loses data.
The Bugsnag integration maintains a persistent real-time connection for chat support automation with automatic retry logic and continuous monitoring. If Bugsnag experiences downtime, queued chat support tasks process automatically once connectivity resumes.
The dashboard shows chat support-specific metrics for your Bugsnag integration — tasks processed, average handling time, success rates, and escalation frequency. You can track how Bugsnag-triggered chat support workflows perform over time.
Arahi AI connects to Bugsnag via one-click OAuth, then runs chat support workflows that read and write Bugsnag data on a schedule or in response to triggers. You configure the rules once; the agent executes chat support across every relevant Bugsnag record without developer involvement.
Bugsnag 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 Bugsnag-adjacent work that genuinely needs human attention.
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