Ship AI that actually works
Build reliable AI workflows by combining LLMs with specialist models and validators. Vibe training creates custom models from plain English - no PhD required.
Stop Fighting Hallucinations
Three steps to reliable AI: Find quality data, train specialist models, orchestrate with validators
Search millions of datasets with built-in uncertainty scoring. Know which data is reliable before training starts.
Describe what you want in plain English. We synthesize data and train specialist models that are 3x cheaper than GPT.
Combine LLMs with ML classifiers and validators. Add thresholds, voting, and fallbacks to eliminate hallucinations.
How It Works
From idea to production API without the ML PhD
Step 1: Find Quality Data
Search datasets with uncertainty scores to know what's reliable
- Search Hugging Face, Kaggle, APIs, your files
- Uncertainty scoring shows data reliability
- Auto-normalization and schema detection
- Synthetic data generation to fill gaps
Step 2: Train Without Code
Describe the behavior you want - we create the data and model
- Vibe training: describe behavior, not datasets
- Automatic data synthesis and augmentation
- 3x cheaper than gpt-5 for specific tasks
- Export models that run anywhere
Step 3: Orchestrate Reliably
Chain LLMs + ML + validators with built-in error handling
- Mix LLMs, classifiers, and programmatic checks
- Uncertainty thresholds and majority voting
- Automatic retries and fallback paths
- Deploy as production API instantly
Why Builders Choose Monostate
Whether you're a ML researcher or a full stack developer - ship realiable workflows.
80% Fewer Hallucinations
Specialized model workflows with validators catch errors before users see them. Ship with confidence.
3x Cheaper Than gpt-5
Specialist models for specific tasks cost less and run faster. Stop overpaying for general intelligence.
Works With Your Tools
Deploy as APIs that work with Cursor, Claude, or any stack. From prototype to production seamlessly.
Ready to ship reliable AI?
Join engineers and builders deploying workflows that actually work in production