Arahi AI

Q: How does Arahi AI automate workflow directly inside ChatBot?

Arahi AI connects natively with ChatBot to handle the full workflow workflow. The AI agent monitors ChatBot events, processes workflow tasks automatically, and writes results back to ChatBot — no copy-pasting or tab-switching required.

Q: What specific workflow tasks can the ChatBot integration automate?

The ChatBot integration automates end-to-end workflow — including data capture from ChatBot, validation, routing, follow-up actions, and status updates. Every workflow step that touches ChatBot can be handled by the AI agent.

Q: How long does it take to set up workflow automation with ChatBot?

Most users connect ChatBot and launch their first workflow automation within 10 minutes. The guided wizard handles OAuth authorization, and you configure workflow-specific rules through a visual no-code builder.

Q: What happens when the workflow agent encounters an issue in ChatBot?

When the AI hits an edge case during workflow processing in ChatBot, it escalates to your team with full context — the ChatBot record, what was attempted, and why it needs review. Your workflow pipeline never stalls or loses data.

Q: What kinds of ChatBot workflows can the agent automate?

Anything that follows repeatable rules — approvals, document routing, multi-system handoffs, scheduled tasks, and the chatbot-specific cross-departmental processes that today rely on email follow-ups and tribal knowledge.

Q: Do we need engineers to build workflow for ChatBot?

No. Workflows are built in a visual no-code builder by your chatbot ops or business teams. Most workflows go from idea to live in under a day without any developer involvement.

Q: How does ChatBot data stay secure during workflow automation?

All data exchanged between ChatBot and Arahi AI during workflow processing is encrypted in transit and at rest. We use OAuth tokens for ChatBot access, never store raw credentials, and maintain full audit logs of every workflow action.

Q: Can I run multiple workflow workflows with different ChatBot triggers?

Yes. You can create parallel workflow workflows that respond to different ChatBot events or conditions. For example, one workflow flow for new ChatBot records and another for updated ones — each with independent rules and actions.

Q: How does AI-powered workflow via ChatBot compare to manual processing?

Manual workflow in ChatBot requires constant tab-switching, copy-pasting, and follow-up tracking. Arahi AI eliminates this by handling workflow tasks in real-time as ChatBot events occur — running 24/7 with consistent accuracy and zero fatigue.

Q: How does workflow automation scale with increased ChatBot volume?

The workflow agent scales automatically as your ChatBot activity grows. Whether you process 10 or 10,000 workflow tasks per day from ChatBot, the AI handles the volume without slowdowns or additional configuration.

Smarter Workflow for ChatBot Teams

Turn Workflow into a background job. Arahi AI agents use ChatBot to execute on your behalf, 24/7.

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When a deal closes in @HubSpot, have @ChatBot kick off the post-sale handoff: notify CS in @Slack, create the project in @Notion, and book kickoff in @Calendar.

Working

Brightlane closed-won. Handoff fired:

Handoff · Brightlane · Closed-won $86KGranola · Auto-captured

Meeting notes

• Slack: #cs-brightlane channel created · Marco assigned.
• Notion: project workspace cloned from template.
• Calendar: kickoff booked Tue Mar 12, 2:00 PM PT (45 min).

Salesforce · Closed-wonRow added

Account

ACV

Kickoff

Brightlane

$86K

Marco

Mar 12 2pm

Eliminated

Manual Handoffs

across connected systems

How you tell it what to do

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.

Your instruction

“When a deal closes in @HubSpot, have @ChatBot kick off the post-sale handoff: notify CS in @Slack, create the project in @Notion, and book kickoff in @Calendar.”

What the agent will do

1Read the meeting transcript end-to-end
2Extract decisions, commitments, and next steps
3Update the deal record and advance the stage if criteria met
4Notify the right teammate with the relevant context

Touches

How it works

Get started in three steps

Step 01

Connect ChatBot

Add ChatBot to your Arahi AI workspace in seconds. The AI immediately starts listening for messages and events.

Step 02

Configure Message Workflows

Choose which ChatBot channels, threads, or DMs trigger AI actions — and what happens next.

Step 03

Automate & Stay in the Loop

The AI handles routine messages and tasks in ChatBot while escalating anything that needs your attention.

Review queue

3 pending

Meeting log · Handoff · Brightlane · Closed-won $86Kjust now

Slack: #cs-brightlane channel created · Marco assigned.

Meeting log · weekly sync2 min ago

Action items extracted; assignees notified in Slack.

Meeting log · pipeline review5 min ago

Three deals moved to next stage; risks flagged for the AE.

Human in the loop

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.

Governance

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.

Activity log

Last 30 minutes

Agent2:47 PM
Updated Salesforce · Closed-won with the meeting outcome.
Agent2:46 PM
Advanced deal stage; the criteria for Proposal were met.
Reason: Budget confirmed and decision-maker identified per stage definition.
Agent2:45 PM
Wrote meeting notes for Handoff · Brightlane · Closed-won $86K.
Agent2:44 PM
Read the transcript and extracted action items.
Agent2:30 PM
Triggered by call end event in Granola.

FAQ

Frequently asked questions

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