A 60-second crash course on Snowglobe and simulation testing.
Snowglobe is a high-fidelity simulation engine that generates thousands of realistic, diverse conversations to stress-test your AI chatbots. It creates synthetic users with different goals and personalities that interact with your chatbot’s endpoints across various scenarios, helping you identify potential risks, edge cases, and performance issues before deployment.
Snowglobe generates AI personas that create test scenarios for user applications, then iteratively focuses on the highest-risk personas based on test results.
AI chatbot: The AI chatbot that Snowglobe will stress-test. In order to stress-test a chatbot, you need to provide a connection to the chatbot (e.g. a URL to an API endpoint or start a local server) as well as a short description of the chatbot’s purpose and behavior.
Simulations: One run of Snowglobe is called a simulation. During a simulation, Snowglobe will generate a set of personas that will interact with the chatbot’s endpoints to create simulated conversations.
Personas: Synthetic user that Snowglobe creates during a simulation. Personas have their own goals, personality, and behavior, and they maintain their own state as they interact with the chatbot’s endpoints.
Scenarios: Each simulated conversation is called a scenario. Snowglobe will generate scenarios at scale during simulation.
Metrics: Judgements on the chatbot’s performance on each scenario. Users select the metrics that they want to track during simulation.