AI Agent for Chat Support — Built for Pipefy
Automate Chat Support for teams using Pipefy. 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 Pipefy
Link Pipefy to Arahi AI in one click. Your tasks, projects, and documents sync automatically.
Set Up Workspace Automation
Define triggers in Pipefy — new tasks, status changes, due dates — and the AI actions that follow.
Work Smarter, Not Harder
Your AI agent keeps Pipefy 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
The Pipefy integration automates end-to-end chat support — including data capture from Pipefy, validation, routing, follow-up actions, and status updates. Every chat support step that touches Pipefy can be handled by the AI agent.
Yes. You can create parallel chat support workflows that respond to different Pipefy events or conditions. For example, one chat support flow for new Pipefy records and another for updated ones — each with independent rules and actions.
Yes. The chat support agent connected to Pipefy simultaneously interacts with 1,500+ other apps — CRMs, databases, email platforms, and more. A single chat support workflow can pull data from Pipefy, process it, and push results to multiple destinations.
All data exchanged between Pipefy and Arahi AI during chat support processing is encrypted in transit and at rest. We use OAuth tokens for Pipefy access, never store raw credentials, and maintain full audit logs of every chat support action.
No coding required. The no-code builder walks you through connecting Pipefy and configuring chat support rules visually. Your team can set up, modify, and manage Pipefy-based chat support workflows without any developer involvement.
The chat support agent scales automatically as your Pipefy activity grows. Whether you process 10 or 10,000 chat support tasks per day from Pipefy, the AI handles the volume without slowdowns or additional configuration.
When the AI hits an edge case during chat support processing in Pipefy, it escalates to your team with full context — the Pipefy record, what was attempted, and why it needs review. Your chat support pipeline never stalls or loses data.
The dashboard shows chat support-specific metrics for your Pipefy integration — tasks processed, average handling time, success rates, and escalation frequency. You can track how Pipefy-triggered chat support workflows perform over time.
Arahi AI connects to Pipefy via one-click OAuth, then runs chat support workflows that read and write Pipefy data on a schedule or in response to triggers. You configure the rules once; the agent executes chat support across every relevant Pipefy record without developer involvement.
Pipefy 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 Pipefy-adjacent work that genuinely needs human attention.
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