SnowglobeTranslation site

What is Snowglobe?

Snowglobe is a specialized AIchatbotand big language modeling to build theDialogue simulationand evaluation platform. It simulates real interaction scenarios on a large scale through thousands of virtual user personalities (Personas) to help teams identify potential risks and boundary issues before the model goes live. The platform not only automatically generates evaluation reports to reveal failure modes, but also outputs high-quality training data (e.g., judgment labels, preference pairs, and revision examples), which can be directly applied to the training process such as SFT and DPO.

At the same time, Snowglobe supports the rapid construction of regression test suites, integrating testing into continuous integration and making model iteration more secure and efficient. It has been proved in cases of education and content platforms that it can significantly shorten the test cycle and improve reliability, which is suitable for teams that want to improve the stability and security of AI systems.

Snowglobe's core functionality

1. Large-scale dialog simulation
   Thousands of virtual personalities (personas) are used to simulate real user conversations with different interaction styles, covering a wide range of scenarios and intentions.
2. Detailed analysis report
   Automatically generate reports with granular insights that include failure modes, boundary cases, and differences in performance across user groups.
3. Evaluation set and training data generation
   Generate judge-labeled datasets from simulated conversations, preference pairs for DPO or reward model training, and critique-and-revise examples for SFT in an export format compatible with the training process (e.g., JSONL).
4. Quick Build & Regression Testing
   A test suite of hundreds of conversations can be run quickly for continuous regression to detect trends in error rates.

Scenarios for Snowglobe

• Pre-launch QA and Regression Testing
  Automatically detect misbehavior that may occur in rare scenarios before the model goes live.
• Enhancing Dialogue Coverage and Security
  Simulate different user roles and behaviors to cover rare edge scenarios and reduce post-launch risks.
• Data generation and enhancement
  Used to generate high-quality training data, including judgment, preference, and example correction content.
• Cross-team collaboration support
  Visualization tools help non-technical people (product, operations, security teams) understand conversation performance and support broad team collaboration.
• Actual customer cases
  • MasterClassWith Snowglobe, synthetic user personas are more "real" and the generation process is modular, supporting the visualization of running simulations, generating data and analysis.
  • Thailand SCB10 Educational ChatbotThe test cases run in a single day: 400+ test cases are run in a single day, and tasks that would take 2-3 people a week to complete are dramatically accelerated, with near-zero error rates, to ensure security and stability for thousands of students.

How do I use Snowglobe?

1. Access Preparation
   Access the Chatbot's API endpoint or local service to Snowglobe and provide its functional description and behavioral expectations.
2. Configuring Simulation Scenarios
   Define multiple personas (e.g., different ages, intentions, tone of voice) and predicted behaviors to test interactions with the accessed Agent.
3. running simulation
   A simulation is performed and the system automatically generates the corresponding dialog flow and user responses.
4. Generate and export data
   Includes judge-label, preference-pair, and critique-revise training samples, which are suitable for SFT, DPO, and other model training processes.
5. Analysis and Visualization
   Use the UI tools provided by Snowglobe to see which personas are performing poorly and failing at high rates, making it easy to create remediation plans.
6. Continuous Integration & Regression Monitoring
   Incorporate mock test suites into the CI process and run them regularly to track changes in error rates and prevent regressions.

Why do you recommend Snowglobe?

• Risk visualization: The simulation process covers different user trajectories, predicts potential problems, and effectively reduces go-live risks.
• Efficiency and scale: Run hundreds of simulations in seconds/minutes, tens of times more efficient than manual testing.
• Training data output: Provides high-quality training samples directly for fine-tuning and reward models.
• Experimentation and continuous improvement: Supports reruns, regression testing, and helps optimize the product for agile iteration.
• Wide range of application scenarios and user recognition: Real-life examples of its benefits in education, high-fidelity conversations, security testing, and cross-team collaboration.