Lower the cost of storing text.
TextFold helps companies store less data in RAG pipelines, knowledge bases, and archives. It’s designed to compress text quickly and restore it on demand.
See how it works for RAG-
Source documentsText from your knowledge base or data exports
- Compress before storing
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Compressed textFewer bytes to store and transfer
- Decompress when needed
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Text for your applicationRead it, search it, or pass it to a model
Save on storage. Keep text accessible.
Smaller files
Reduce the volume of text your company pays to store in archives, backups, and recurring exports.
Fast compression
Designed to keep up with routine ingestion and batch jobs as your text collection grows.
Fast decompression
Designed to make stored text available quickly when an application needs to read it.
For retrieval-augmented generation
RAG pipelines can store a large collection of source text even though each request uses only a few passages. Store text chunks in compressed form, then decompress only the passages retrieved for the model.
Keep your retrieval index
Use your existing vector index to find relevant chunks. TextFold targets the source text and chunk storage, separate from the embeddings that power retrieval.
Measure savings on your own data.
Compare storage cost, time to compress, and time to decompress on a representative text collection. For RAG, include decompression time in your end-to-end retrieval latency.