A ChatGPT agent that scores every inbound lead against your ICP.
It reads each form fill or enriched contact from your CRM, scores it against the criteria you define, and writes a one-line context note your AE sees before they pick up the phone.
32 leads scored. Here's the top-ranked one queued for outreach:
How does OpenAI ChatGPT work for lead qualification?
OpenAI ChatGPT works for lead qualification by acting as the reasoning model behind an Arahi AI agent that scores every inbound form fill and enriched contact against the rubric your team actually uses — not a generic ICP template. The agent reads the lead record in your CRM (HubSpot, Salesforce, Pipedrive, Attio, or Close), pulls enrichment from Clay, Apollo, ZoomInfo, or LinkedIn Sales Navigator, and assigns a score together with the reasoning the AE will see before picking up the phone. The rubric is calibrated from six to twelve months of your past closed-won and closed-lost deals, then editable in plain English at any time. High-confidence leads route to the right AE instantly; ambiguous ones queue for a human review with the missing signal called out. Every score is logged and reversible, so the agent improves with each correction.
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 trigger event and pull the contact's context
- 2Draft the message in your team's voice
- 3Cite each personalized line's source
- 4Queue for your review or auto-send by confidence
Get started in three steps
Connect OpenAI (ChatGPT)
Authorize OpenAI (ChatGPT) in your Arahi AI dashboard. The secure connection takes less than 60 seconds.
Configure Your AI Agent
Set up triggers, actions, and conditions specific to how your team uses OpenAI (ChatGPT).
Deploy & Monitor Results
Your AI agent goes live immediately. Track tasks automated, time saved, and accuracy metrics in real-time.
Northwave + Arahi · 15 min next week?
ChatGPT flagged your account as a 92/100 ICP fit — Series B SaaS, 80 FTE, hiring two ops roles this quarter.
Personalized using LinkedIn activity from the last 30 days.
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.
- Marco11:42 AM
Approved the draft to jordan.lee@northwave.io.
- Agent11:41 AM
Drafted the email and queued it for review.
Reason: High-confidence personalization but recipient is C-level — escalating per policy.
- Agent11:40 AM
Pulled LinkedIn activity and HubSpot deal context.
- Agent11:40 AM
Triggered: Score every new @ChatGPT inbound lead in @HubSpot against our ICP, then push the
- Agent11:38 AM
Confirmed sender domain DKIM is healthy.
Frequently asked questions
It scores the lead and proposes the next action (route to AE, drop into nurture, disqualify with reason). The action is configurable: auto-execute for high-confidence cases, ask a human for review on the rest.
From your past closed-won and closed-lost deals. The agent reads 6–12 months of CRM history, asks you to confirm the patterns it finds, and uses that as the rubric. You can edit it any time.
HubSpot, Salesforce, Pipedrive, Attio, and Close out of the box. Custom CRMs work via REST or our 1,500+ app library.
Every score comes with the reasoning the agent used. You can spot-check, accept, or override — and the agent learns from each correction. After ~50 reviewed leads it usually plateaus at the level your best SDR would score them.
Half a day. Most of it is mapping your existing fields and confirming the agent's first-pass rubric. No engineering required.
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