One question across four media types
A single query can return document passages, image semantics, audio transcripts, and video segments without relying on filenames.
Back to products[ FULL-MEDIA KNOWLEDGE PRODUCT ]
Lumora KB: full-media knowledge retrieval workbench
A knowledge base should understand more than PDFs. This workbench puts text, images, audio, and video into one observable chain so results cross media and still return to their source.
The point is unified understanding and traceability, not format count
Every result returns to its source
Each hit preserves a section, tag, timestamp, or character range instead of becoming an untraceable summary.
Deployment boundaries stay selectable
Sensitive material can use local models and private storage while public data can use cloud capabilities based on cost, latency, and compliance.
Four media types, four processing paths, one knowledge layer
Text structure parsing
Preserve headings, paragraphs, tables, and section anchors.
Image understanding
Generate descriptions, tags, OCR, and vector representations.
Audio/video processing
Align transcripts, keyframes, subtitles, and timelines.
Unified recall and navigation
Rerank cross-media hits and retain source locations.
[ CURRENT BOUNDARY ]
A deterministic interactive demo with explicit integration boundaries
The public version uses pre-loaded materials and deterministic simulated retrieval for reliable demonstrations. RAGFlow, Qwen-VL, Whisper, vLLM, enterprise identity, and object storage are not connected yet; production integration requires permission, model, and storage boundaries based on data sensitivity.