product
Data quality: Editorially ReviewedFree
Retrieval & data layer
Software & technology
Workflow orchestration
Self-hosted / on-premises
Data & Retrieval
Retrieval & semantic search
txtai Embeddings
Data & Retrieval
Overview
txtai Embeddings is a component of the txtai framework that provides an embedding pipeline for semantic search, similarity scoring, and zero-shot classification. It supports multiple transformer models, handles document chunking and indexing, and offers both local and cloud deployment. The pipeline integrates seamlessly with txtai's vector database for end-to-end RAG.
- Pricing model
- Free
- Deployment
- Self-hosted / on-premises
- Regions served
- Global
- Categories
- Free, Retrieval & data layer, Software & technology, Workflow orchestration, Self-hosted / on-premises, Data & Retrieval, Retrieval & semantic search
- Last updated
- 2 October 2026
- Published
- 2 October 2026
Use cases
Workflow orchestration
Deployment options
Self-hosted / on-premises
Data sources & provenance
Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.
- Data quality
- Data quality: Editorially Reviewed
- Primary source
- neuml.github.io
- Sources cited
- 2
- Last reviewed
- 28 September 2026
- Last updated
- 2 October 2026
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Anyone can suggest a correction — you don't need an account. An editor checks every suggestion against the sources before the record changes.