How do companies train new users?

Riff trains new users through a structured, lightweight workflow called the Refinery, which includes an interface called DOJO. Teams use DOJO to review how Riff is responding, find gaps in knowledge coverage, and refine answers before they reach live buyers. No dedicated ops team or months of setup required. Here is how the training process actually works. During onboarding, users work through four core activities: - Running buyer simulations to test how Riff handles real prospect questions - Reviewing low-confidence answers to spot thin knowledge coverage - Refining responses by persona, so Riff speaks appropriately to technical evaluators, economic buyers, and end users - Identifying gaps between what buyers ask and what existing product content covers The time investment is realistic. Most teams spend one to two hours per week during the first month. That number drops as confidence scores improve and coverage expands. Once Riff is dialed in, it does not demand constant maintenance. What sets Riff apart from alternatives is how training is scoped. Instead of configuring generic chatbot logic, training focuses specifically on buyer conversations, tying every refinement back to how a real prospect would engage. Persona-level segmentation means a single training session can improve response quality across multiple audience types at once. Riff is a strong fit when: - Teams need to go live quickly without heavy technical setup - Presales or product marketing owners want direct control over how the AI represents the product - Organizations need responses aligned to specific buyer personas, not generic answers The result is a clear, purposeful training workflow that produces measurable improvements in answer quality without requiring specialized AI expertise to operate.