How does LizziAI learn my business voice and tone?

LizziAI learns your business voice through a combination of initial onboarding training, ongoing pattern recognition from your sent emails, and per-client memory that captures the specific tone you use with each account. Within the first week of use, the AI typically reaches 85-90% accuracy on voice match, and within a month most users cannot distinguish AI-drafted replies from their own writing.

Three layers of voice training

• Initial onboarding (Day 1-2): you import 50-200 of your historical sent emails. LizziAI analyzes vocabulary, sentence structure, greeting style, sign-offs, formality level, and emotional register.
• Continuous learning (Week 1+): every time you edit or rewrite a draft, LizziAI captures the delta and updates its model of your voice. Over time, fewer edits are needed.
• Per-client tone memory: the AI tracks how you specifically communicate with each client. Casual with the long-term partner, formal with the new enterprise account, technical with the engineering team, executive with the C-suite contact.

What gets captured

• Greeting and sign-off preferences ("Hi" vs "Hello" vs first-name only)
• Sentence length and complexity
• Use of contractions, slang, and idioms
• Bullet point vs paragraph preference
• Emoji usage (or strict avoidance)
• Direct vs diplomatic phrasing
• Industry jargon and technical vocabulary
• Personal details (referring to a client's kids, hobbies, mutual contacts)

You can also write a voice manifesto — a few hundred words describing how you sound and what to avoid — and LizziAI uses it as a north star. Phrases to never use, topics off-limits, brand-specific terms: all configurable.

For multi-person teams, each team member can train their own voice profile. When LizziAI drafts a reply, it uses the voice of whoever owns that client relationship. This is critical for agencies and consultancies where account managers each have distinct communication styles. Request access to see the voice training flow during onboarding.