The article further explains the process of product adoption. Users can train their model by adding sources to create a custom model. They can add actions such as navigation, tours, API calls, and more. Finally, they can build the AI assistance into their app using SDKs and APIs. The toolkit also allows users to monitor usage and understand AI response quality.
Key takeaways:
- The toolkit allows users to build AI-powered personalized and contextual experiences.
- It offers pre-built components and flexible SDKs for easy customization and building of any type of assistance.
- The AI assistance is contextually aware, providing relevant help based on in-app context and custom LLM.
- The toolkit provides insights on how users are using AI, allowing for monitoring of usage and understanding of AI response quality.