Tone & Knowledge Base
Tone examples and the knowledge base are the two tools you use to control how the AI communicates on your behalf. Tone examples teach the AI how to sound. The knowledge base teaches the AI what to say.
Which Should You Set Up First?
Both matter eventually, but they solve different problems:
Start with the Knowledge Base if your offer has nuanced positioning, common objections, or details the AI needs to get right (pricing tiers, specific case studies, technical answers). Without it, the AI improvises — and improvisation on cold facts is risky. Even a single well-written 1-page positioning doc dramatically improves response quality.
Start with Tone Examples if your AI replies sound technically correct but feel robotic or off-brand. Tone examples are the fastest way to make the AI sound like you.
Most users get the most value from a small Knowledge Base (2-3 documents) plus 5-10 tone examples. AutoReach also auto-captures tone examples from conversations that lead to booked meetings, so this library grows over time without manual work.
If you're brand new and not sure where to start: skip both, let your sequence run for a week, then come back here. AutoReach will have auto-captured your first tone examples by then, and you'll know which knowledge gaps the AI keeps stumbling on.
Tone Examples
Tone examples are conversation samples that teach the AI how you want to sound. They are the most effective way to make AI responses feel authentic to your voice and sales style.
How They Work
Tone examples are stored per-sequence. Each example contains:
A label describing the scenario
A stage classification (Opener Reply, Discovery, Objection Handling, etc.)
A conversation with message pairs showing the exchange
A source type indicating how it was created
When generating a response, the AI retrieves the most relevant tone examples based on the current conversation context. Examples cover all conversation stages including a dedicated "Not a Fit" category for gracefully handling leads that are not a match.
Auto-Capture from Conversations
Tone examples are automatically captured from real conversation outcomes:
Winning Conversations - When a conversation reaches Meeting Booked status, the system extracts the best exchanges and saves them as examples, automatically classified by conversation stage. Duplicate examples are detected and skipped.
Tone Summary
A tone summary is a style guide automatically extracted from your tone examples by AI. It captures your vocabulary, communication style, and common patterns. You can regenerate it from the tone examples section to keep it current with your evolving voice.
Managing Tone Examples
Open your sequence's Settings tab and scroll to the Tone Examples section to:
View examples organized by stage
Edit text to better match your voice
Delete examples that don't fit your style
Add custom examples from conversations that went well
Use contractions (I'm, you're, they've) in your examples. Non-contracted language sounds robotic in DMs.
Knowledge Base
The Knowledge Base stores your sales documents so the AI can reference them when generating responses. Upload playbooks, case studies, FAQs, and objection handling docs to make the AI smarter and more context-aware.
How It Works
Documents are uploaded per-offer. After uploading, AutoReach automatically processes and indexes your documents so the AI can search them for relevant content when generating responses.
Knowledge base is scoped per-offer, so different offers can have different knowledge bases. This ensures AI responses are tailored to each target audience.
When Knowledge Base Is Used
Cold DM generation: References your value proposition, metrics, and case studies
Response generation: Finds relevant objection handling scripts, product details, or case studies based on the conversation topic
Offer-specific context: Ensures Enterprise case studies do not appear in SMB conversations
Uploading Documents
Supported file formats:
PDF: Sales decks, case studies, whitepapers, one-pagers
DOCX: Playbooks, sales guides, process documents
TXT: FAQs, objection handling scripts, notes, quick-reference sheets
You can upload up to 10 documents per offer. Quality matters more than quantity. A few well-written documents outperform a large collection of vague or overlapping content.
How to upload:
Navigate to your Offer and open the Knowledge Base section
Click the upload area or drag a file onto it
Select a file from your computer (PDF, DOCX, or TXT)
Processing takes a few seconds per document. Once complete, your knowledge base is ready to use.
What Makes a Good Knowledge Base Document
Strong candidates:
Case studies with concrete results: "We helped Company X reduce churn by 40% in 3 months" gives the AI a specific proof point to reference
Objection handling scripts: Common pushbacks with your proven responses
Pricing and packaging guides: So the AI can speak accurately about what you offer
Product or service overviews: Feature descriptions, use cases, and differentiators
Implementation and onboarding docs: Timeline, process steps, and what the customer can expect
FAQ documents: Answers to the questions your sales team hears most often
Documents to avoid:
Generic marketing copy with no specifics
Internal engineering or technical documentation not relevant to sales conversations
Excessively long documents where key points are buried (break these into focused sections instead)
Tips for Better AI Responses
Be specific with numbers and outcomes: "Reduced onboarding time from 6 weeks to 10 days" is far more useful to the AI than "We speed up onboarding"
Use clear section headings: Processing works best when your documents have logical sections with descriptive headers
Write in the voice you want the AI to use: If your knowledge base documents are formal, the AI will lean formal. If they are conversational, responses will reflect that
Cover common objections explicitly: Write out the objection and your ideal response. The AI will adapt this to each conversation
Update after wins: When you close a deal, add the story as a case study. Fresh, specific examples improve response quality over time
Remove outdated content: Old pricing, discontinued features, or stale case studies can cause the AI to reference information that is no longer accurate
Next Steps
AI Response Engine: How the AI uses tone examples and knowledge base during generation
Conversation Analyzer: AI suggestions for improving your conversations
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