Mae
Mae sends emails and DMs for you, 90% like you
Mae sends emails and DMs for you by replicating your communication style, tone, and context with over 90% accuracy.
Features
- Mae is an AI assistant that learns your personal writing style and replies to emails, DMs, and messages exactly like you.
- It works across multiple platforms including Gmail, WhatsApp, Instagram, and Slack, handling all your communications in one place.
- Mae is designed to save time while maintaining your authentic voice across every channel.
Use Cases
Based on everything I know about Mae:
High volume professionals Founders, executives, creators who get more messages than they can humanly reply to. Mae handles the volume without dropping the relationship.
Creators with audiences A YouTuber or newsletter writer with 50k followers who gets DMs daily but can only reply to a fraction. Mae replies in their voice so every fan feels heard.
Sales and outreach Following up with leads across email and WhatsApp without sounding like a template. Mae keeps the tone personal even at scale.
Recruiters Responding to candidates quickly and personally across platforms without copying and pasting the same message 40 times.
Community managers Managing Slack communities where members expect real responses. Mae handles routine questions in the manager's voice.
Freelancers and consultants Client communication across email and WhatsApp while actually doing the work. No more "sorry for the late reply" openers.
Comments
The multi-platform angle is what makes this actually useful. Most AI email tools stop at Gmail. Covering WhatsApp and Instagram DMs in the same style layer is genuinely hard to pull off and that's where creators actually live. If the voice replication holds up under pressure this could be a real unlock for anyone with an audience above 10k.
The premise of AI that sends emails and DMs "90% like you" is fascinating. The hardest part of automating outreach is preserving authentic voice — most tools end up sounding generic. Curious about the training process: does it learn from your existing sent messages, or does it ask you to provide writing samples? The personalization accuracy will be the key differentiator here.
The premise of AI that sends emails and DMs "90% like you" is fascinating. The hardest part of automating outreach is preserving authentic voice — most tools end up sounding generic. Curious about the training process: does it learn from your existing sent messages, or does it ask you to provide writing samples? The personalization accuracy will be the key differentiator here.
The 90% accuracy claim is interesting — the hard part with voice replication is usually handling different contexts: a cold outreach email vs a reply to a thread. If Mae can distinguish those and adjust tone accordingly, that would separate it from tools that just mimic writing style without understanding intent.
Hitting that 90% match rate is an impressive benchmark. Typically, the biggest hurdle for AI ghostwriters isn't vocabulary, but relational intelligence—understanding the difference between messaging an old client versus pitching a brand-new lead. If it can actively parse the depth of the relationship and calibrate its warmth accordingly, that’s a massive competitive advantage over standard text generators
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Comments
The multi-platform angle is what makes this actually useful. Most AI email tools stop at Gmail. Covering WhatsApp and Instagram DMs in the same style layer is genuinely hard to pull off and that's where creators actually live. If the voice replication holds up under pressure this could be a real unlock for anyone with an audience above 10k.
The premise of AI that sends emails and DMs "90% like you" is fascinating. The hardest part of automating outreach is preserving authentic voice — most tools end up sounding generic. Curious about the training process: does it learn from your existing sent messages, or does it ask you to provide writing samples? The personalization accuracy will be the key differentiator here.
The premise of AI that sends emails and DMs "90% like you" is fascinating. The hardest part of automating outreach is preserving authentic voice — most tools end up sounding generic. Curious about the training process: does it learn from your existing sent messages, or does it ask you to provide writing samples? The personalization accuracy will be the key differentiator here.
The 90% accuracy claim is interesting — the hard part with voice replication is usually handling different contexts: a cold outreach email vs a reply to a thread. If Mae can distinguish those and adjust tone accordingly, that would separate it from tools that just mimic writing style without understanding intent.
Hitting that 90% match rate is an impressive benchmark. Typically, the biggest hurdle for AI ghostwriters isn't vocabulary, but relational intelligence—understanding the difference between messaging an old client versus pitching a brand-new lead. If it can actively parse the depth of the relationship and calibrate its warmth accordingly, that’s a massive competitive advantage over standard text generators
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