Generating Training Data
Most synthetic data is too uniform. Snowglobe generates the messy, frustrated, and complex human personas you actually need to tune your model.
Generate Realistic Training Data
Snowglobe uses a proprietary generation algorithm and hundreds of thousands of unique mutations to build personas with specific styles and tones to simulate real users.
Automatic "Judge" Iteration
Don't spend weeks on manual labeling. Use Snowglobe’s modular LLM-as-a-judge to automatically label messages. It’s a self-improving loop: as you find new risks, you spawn new tests to harden your model.
Auto-Generated Finetuning Sets
Turn your simulation runs directly into high-signal training data. Snowglobe exports data for DPO (Direct Preference Optimization) and SFT (Supervised Fine-Tuning), cutting out messy data-wrangling cycles.
Static datasets can’t find the “Long Tail”
Traditional “golden” datasets only cover the most common cases—the happy paths. But high-risk failures happen in the rare edge cases: hallucinations in specialized knowledge or unexpected behavior in multi-turn conversations.
Fight stale data
Data becomes stale as there’s changes to your system prompt and application use cases. Snowglobe generates fresh data.
Data influenced by how your model responds
Snowglobe data dynamically generates data influenced by how your model responds to testing prompts.
Built for Production AI Teams
For teams building production AI systems who need evaluation data that's realistic, comprehensive, and fast.
~500 scenarios in 30 minutes
Replace weeks of manual curation with automated generation
Enterprise context grounding
Scenarios reflect your domain, terminology, and user patterns
Live system interaction
Tests adapt to actual AI responses, not assumed behavior
Multi-turn conversation support
Evaluate complex dialogue flows, not single-exchange Q&A
Programmatic edge case discovery
Systematically explore failure modes humans wouldn't think to test
Risk quantification
Move from "we tested it" to "here's our measured risk surface"