AI Agent for Chat Support — Built for Chargify
Automate Chat Support for teams using Chargify. 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
Link Your Chargify Store
Connect Chargify in one click. Arahi AI imports your products, orders, and customer data automatically.
Define E-Commerce Workflows
Set up automation for orders, abandoned carts, inventory alerts, and customer communication in Chargify.
Grow Revenue on Autopilot
AI handles the operational work inside Chargify while you focus on strategy. Track recovered revenue and cost savings 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
The Chargify integration automates end-to-end chat support — including data capture from Chargify, validation, routing, follow-up actions, and status updates. Every chat support step that touches Chargify can be handled by the AI agent.
Arahi AI connects natively with Chargify to handle the full chat support workflow. The AI agent monitors Chargify events, processes chat support tasks automatically, and writes results back to Chargify — no copy-pasting or tab-switching required.
Yes. You can run chat support workflows in test mode using sample Chargify data before activating on live records. This lets you verify every chat support rule works correctly with your Chargify setup before processing real data.
No coding required. The no-code builder walks you through connecting Chargify and configuring chat support rules visually. Your team can set up, modify, and manage Chargify-based chat support workflows without any developer involvement.
Yes. You define exactly which Chargify 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 Chargify.
When the AI hits an edge case during chat support processing in Chargify, it escalates to your team with full context — the Chargify record, what was attempted, and why it needs review. Your chat support pipeline never stalls or loses data.
The Chargify integration maintains a persistent real-time connection for chat support automation with automatic retry logic and continuous monitoring. If Chargify experiences downtime, queued chat support tasks process automatically once connectivity resumes.
The dashboard shows chat support-specific metrics for your Chargify integration — tasks processed, average handling time, success rates, and escalation frequency. You can track how Chargify-triggered chat support workflows perform over time.
Arahi AI connects to Chargify via one-click OAuth, then runs chat support workflows that read and write Chargify data on a schedule or in response to triggers. You configure the rules once; the agent executes chat support across every relevant Chargify record without developer involvement.
Chargify 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 Chargify-adjacent work that genuinely needs human attention.
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