The difference between a yes and a not now is everything.
When you're sending thousands of emails a month, you can't manually read every reply. Our LLM-based classifier reads every response, tags intent, and routes warm leads to your team in minutes.
Why reply classification matters
At scale, cold email generates hundreds of replies per month. Some are interested. Some are "not right now." Some are objections you can overcome. Some are unsubscribes. Without classification, your team wastes hours reading through noise to find the signal. Worse, warm replies rot in the inbox while someone gets around to checking. Our LLM classifier processes every reply in real time, tags it by intent, scores confidence, and routes it to the right person or workflow.
How classification works
- 1
Reply ingestion
Every reply across all sending accounts is captured in real time. The system handles threading, signature stripping, and forward detection to isolate the actual response.
- 2
LLM intent classification
Each reply is classified into categories: interested, meeting request, objection, not now, referral, out of office, unsubscribe, or do-not-contact. Confidence scores are attached to every classification.
- 3
Routing & automation
Interested replies trigger instant notifications. Objections feed into rebuttal workflows. OOO replies schedule follow-ups. Unsubscribes are suppressed automatically. Every category has a defined action.
- 4
Feedback loop
Your team can flag misclassifications. These corrections feed back into the model to improve accuracy over time. Classification accuracy benchmarks at 95% across the standard intent set and climbs from there as your team's corrections train the model.
What's included
- Real-time reply classification across all inboxes
- 8+ intent categories with confidence scoring
- Instant Slack or email notifications for warm replies
- Automated CRM status updates
- OOO detection and follow-up rescheduling
- Unsubscribe and DNC compliance automation
- Objection categorization and rebuttal routing
- Classification accuracy dashboard
- Human-in-the-loop correction workflow
Frequently asked questions
How accurate is the classification?
Starting accuracy benchmarks at 95% across the standard intent set (interested, objection, not now, OOO, DNC). With the feedback loop from your team's corrections, accuracy climbs above 97% within the first month of use.
What happens when the AI isn't confident?
Low-confidence classifications (below 80%) are flagged for human review rather than auto-routed. We'd rather your team spend 10 seconds confirming than miss a deal.
Can I customize the categories?
Yes. We start with standard intent categories and add custom ones based on your sales process. If you need to distinguish "pricing objection" from "timing objection," we can do that.
Does this work with replies from non-email channels?
We classify cold email replies only. We don't run LinkedIn outreach or any other channel, so there is nothing else to classify. If you forward replies into your campaign inbox, the classifier handles them.
Never miss a warm reply again.
Book a call and we'll show you a live demo of the classifier on real campaign replies.