Batch Inference for Embeddings
Generate vector embeddings at scale for search, RAG, and semantic analysis with open source models.
Why Doubleword Batched for Embeddings?
Bulk Embedding Generation
Embed entire document collections, product catalogs, or knowledge bases.
Multiple Models
Choose from leading embedding models for your use case.
Low Cost at Scale
Embed millions of documents at a fraction of the cost of other providers.
Common Use Cases
- Building vector search indexes for semantic search
- Generating embeddings for RAG knowledge bases
- Vector database migrations and re-indexing
- Embedding user queries for intent classification
Everything You Need for Embeddings
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 Embeddings?
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.
Synthetic Data Generation
Generate high-quality training data for model training and fine-tuning.
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.