Batch Inference for Synthetic Data Generation
Generate millions of high-quality training examples at a fraction of the cost of other providers for your training and fine-tuning jobs.
Why Doubleword Batched for Synthetic Data Generation?
Massive Dataset Generation
Generate millions of training examples without breaking the bank.
Consistent Quality
Every example generated with the same parameters for uniform dataset quality.
OpenAI-Compatible API
Drop-in replacement for your existing workflows with full tool use and JSON mode support.
Common Use Cases
- Creating instruction-following datasets for fine-tuning
- Generating question-answer pairs for RAG training
- Building evaluation datasets for model benchmarking
- Augmenting existing training data with variations
Everything You Need for Synthetic Data Generation
Up to 75% Savings
Our batch-optimized infrastructure delivers dramatic cost savings on every inference call.
Guaranteed SLAs
Choose 1-hour or 24-hour delivery. If we miss it, you don't pay. Simple as that.
Streaming Results
Results flow back as they're processed. Start using data before the batch completes.
Ready to Optimize Your Synthetic Data Generation?
Join our private preview and start saving up to 75% on your batch inference workloads today.
Other Use Cases
Async Agents
Autonomous agents that do long running background multi-step reasoning tasks.
Data Processing Pipelines
Process large datasets with LLM-powered analysis at scale.
Image Processing
Analyze, caption, and extract insights from thousands of images efficiently.
Model Evals
Run comprehensive evaluation suites across candidate models cost-effectively.
Document Processing
Extract, summarize, and analyze documents at scale.
Classification
Categorize and tag content across millions of items.
Embeddings
Generate vector embeddings for search, RAG, and semantic analysis.