AI replies
Draft contextual responses in your voice — never canned, never robotic.
- ·Drafted from full lead + thread context
- ·Trained per-user on your past sent replies
- ·Editable before send — never auto-fired
- ·Tone slider — assertive / friendly / brief
- ·Bring your own AI key — unlimited, no per-credit metering
The detail.
Voice cloning, not template bingo
The model fine-tunes on your last 200 sent replies so the draft sounds like you, not like a SaaS bot. Tone slider lets you nudge a specific draft assertive or friendly without rewriting from scratch.
Always human-in-the-loop
AI drafts; you send. There is no 'auto-send AI replies' button — every draft requires a click, by design. Outbound at scale + compliance gates is the right division of labour.
vs. ChatGPT-in-Gmail / canned templates / Lavender / Smartwriter
The honest comparison — what changes when you switch.
Four things you won’t find elsewhere.
Trained on your sent folder
The per-user fine-tune reads your last 200 sent replies (anonymised, opt-in). Output sounds like you, not like a generic SaaS bot trained on Reddit.
Tone slider, not preset menu
A continuous slider (assertive ↔ friendly · brief ↔ thorough) lets you nudge the same draft until it lands. Most tools force a discrete preset; we give you the dial.
Always human-confirmed
There is no 'auto-send AI replies' switch. Every draft goes through a click. This is non-negotiable for compliance, brand voice, and the 1-in-100 lead the AI misreads.
Budget like AWS, not like SaaS
Per-org credit pool in INR; per-user spend cap; daily/monthly burn graphs in /settings/billing. AI usage is a cost line, not a flat fee.
How teams actually use this.
Founder personalising 30 LinkedIn replies/day
Founder fine-tunes the model on their last 200 LinkedIn DMs. Each new inbound surfaces with a draft pre-written in their voice — short, direct, slightly self-deprecating. They edit 1-2 words, hit send. What used to take 90 minutes a day now takes 25.
8-rep agency with 8 different voices
Each AM gets a per-user fine-tune. Anya's drafts are bullet-point and assertive; Rohan's are conversational with a question hook; Priya's lean empathetic. The shared Unibox auto-routes inbounds to the assigned AM, who sees a draft already in their voice.
Compliance-sensitive enterprise reply
AI drafts a reply that mentions a competitor by name. The SDR catches it (because every draft requires a click), edits the sentence, and sends. The audit log records both the AI draft and the operator's edit — full forensic trail for the compliance officer.
The full story.
AI replies are the highest-leverage automation in modern outbound — but only when they sound like the human whose name is in the From line. Generic LLM drafts (ChatGPT-in-Gmail, Lavender presets, Smartwriter templates) read as SaaS-bot output the moment a buyer reads two of them. Buyers learn the pattern quickly. The reply rate on AI-detected drafts collapses inside a quarter. Autocloz's per-user fine-tune is the answer — the model trains on your last 200 sent replies (with explicit opt-in) so the draft mirrors your sentence rhythm, your tone, your characteristic word choices.
Context is the second leverage point. A reply written from 'subject line + last message' is shallow by definition. Autocloz feeds the model the full lead profile (role, company, custom fields), the sequence step that triggered the conversation, the campaign goal, and the last 10 messages on every channel — not just the most recent email. The result reads like a reply from someone who actually knows the lead, because the model has the same context the operator would have.
Tone control is where most AI-reply tools fail. Discrete presets ('Professional / Friendly / Casual') are too coarse — the difference between a Tuesday morning prospecting reply and a Friday afternoon objection-handle is a slider, not a button. Autocloz's tone control is a continuous dial across two axes: assertive ↔ friendly and brief ↔ thorough. Operators learn within a week which combination lands their replies; the slider then makes the daily inbox triage muscle-memory.
Human-in-the-loop is non-negotiable. There is no 'auto-send AI replies' switch in Autocloz, by design. Every draft requires a click — because the 1-in-100 reply where the AI misreads context (the prospect's name is similar to a competitor's, the lead is asking about pricing the AI doesn't know is custom) is exactly the reply that loses the deal. Outbound at scale needs AI; outbound at scale also needs the operator to remain the final arbiter of what their name signs.