1. Capture your knowledge
Start with your courses, playbooks, frameworks, and recordings you have permission to use. We organize that material into a knowledge foundation and identify gaps. Remove client information that should not be included. Label material that is outdated, conflicts with a newer lesson, or requires context.
2. Calibrate the answers
Examples of how you teach help shape the language and guidance. You review sample conversations so we can refine the tone, the application of your frameworks, and the boundaries. Include difficult questions and questions outside your expertise in the review, not just questions with obvious answers.
3. Plan the launch
The client experience and access model are defined around your audience and offer. Before launch, agree on what the AI should handle and how clients reach a human when it cannot help. Any requested integrations, setup costs, and ongoing costs need to be scoped before work begins.
What should you have ready?
Bring a short description of your audience, your main offer, representative teaching materials, and a list of recurring client questions. The application asks about your business, available content, goals, and timeline. Submitting it is the start of a scope discussion; it is not a purchase or an instant AI deployment.