Building a RAG pipeline requires more than document extraction. Documents must be converted into structured chunks that preserve context while remaining small enough for embedding models. Many developers build custom ingestion scripts that become difficult to maintain as datasets grow.
Titan-Ingest converts document collections into structured JSON chunks suitable for vector databases and AI retrieval systems. It handles the heavy lifting of partitioning large corpora, ensuring that semantic meaning remains intact during the chunking process.
$ titan-ingest -in ./docs -out ./rag.json