How to organise information for better AI Employee answers
Summary
Structure your knowledge sources using clear headings, bullet points, and direct Question & Answer formats to help the AI extract accurate information quickly.
Who this article is for
This article is for content managers and administrators responsible for the quality of the AI Employee's training data.
Overview
Before you begin
- Review current knowledge documents
- Break down long paragraphs into bullet points
- Rewrite complex policies into simple Q&A format
Step 1: Step 1: Use Clear Headings
Step 2: Step 2: Format as Q&A Whenever Possible
Step 3: Step 3: Keep Sentences Short and Direct
Step 4: Step 4: Remove Fluff and Marketing Speak
Step 5: Step 5: Consolidate Information
Configuration note
We do not guarantee AI accuracy, lead conversion, bookings, customer satisfaction, response quality, revenue, support resolution, or business outcomes. The AI Employee does not fully replace human staff. AI behaviour depends on knowledge sources, instructions, handoff rules, enabled features, connected channels, permissions, configuration, testing, and ongoing monitoring. AI-generated responses should be reviewed before relying on them for sensitive, urgent, legal, financial, medical, billing, or policy matters. The AI Employee may need human handoff for these situations. Knowledge sources must be reviewed, updated, and tested regularly. Usage charges, feature access, fair use rules, or add-on requirements may apply depending on your account setup. Always test before going live. Contact support if an option is not visible. The AI interprets information literally. If a rule has exceptions, you must explicitly list those exceptions in the knowledge source.
Important clarification
Uploading a 100-page employee handbook full of internal jargon and expecting the AI to perfectly answer simple customer questions. Always curate the data specifically for customer-facing interactions.
Resolution guidance
The AI is combining answers from two different services. Why?
Your source documents likely lack clear separation between the services. Use stronger headings or separate the services into different custom text snippets.
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