Question Answering Over Documents With Citation Tracking

via “contextual question-answering with document grounding”

Jamba models API — hybrid SSM-Transformer, 256K context, summarization, enterprise fine-tuning.

Unique: Performs end-to-end QA with source attribution without requiring external vector databases or retrieval systems, leveraging the 256K context to embed entire documents and ground answers with span-level citations

vs others: Simpler deployment than traditional RAG (no vector DB needed) while maintaining citation accuracy comparable to specialized QA systems, though less flexible than modular RAG for multi-source queries