VelaIris-DM produces descriptive metadata at the depth archive and search systems actually need. Four modalities — computer vision, ASR, OCR and structured reasoning — converge on a single coherent descriptive record per asset, structured for ingestion into MAM, DAM or proprietary archives, on the customer’s own taxonomy.
Narrative metadata across the whole library — find any segment by describing it in plain language.
Records that drop into existing systems on the existing taxonomy — no re-platforming.
Turn an archive from cost center into discoverable, monetizable inventory.
VelaIris-DM transforms broadcast and streaming video into rich, structured and narrative metadata through a multi-modal content-understanding pipeline — fusing computer vision, ASR, OCR and neural-network narrative synthesis into coherent, flowing descriptions rather than disconnected keyword lists. The result is a fully searchable library: find any segment by describing it in plain language.
Visual understanding covers scene segmentation, location, activity, objects and on-screen graphics; audio adds speech recognition, speaker diarization and word-level transcript alignment; narrative synthesis writes segment-level descriptions and program summaries with cross-segment continuity. It runs entirely on-premises — content never leaves the facility — and output schemas map to the customer’s own taxonomy.
Visual, audio, on-screen text and narrative synthesis, fused into one searchable record per asset.
Scene segmentation and classification, location and activity recognition, object detection and graphics/logo identification.
High-accuracy speech recognition, speaker diarization and word-level transcript-to-video alignment, with language detection.
Segment-level descriptions and program summaries with cross-segment continuity and configurable verbosity — prose, not keyword lists.
Graphics, lower-thirds, chyrons, signage, tickers and crawls captured and indexed.
Natural-language search across narrative, tags and transcripts — archive exploration by topic, date, entity or program.
Rights-management support and accessibility-compliance metadata framed around CEA-608/708 caption support.
Output is one searchable narrative record per asset — continuous segment descriptions plus program summaries, hierarchical topic and entity tags, temporal markers, content classification, rights and compliance flags, exported as JSON, XML or a custom schema.
Visual, audio, on-screen text and structured reasoning fuse into a single descriptive record — segment narrative, summaries and structured metadata.
Live, file-based or streaming — SD and HD, common codecs, multi-language audio.
Named surfaces for description, search and integration.
Split-screen live video with synchronized descriptive-metadata cards.
Natural-language search across the whole library.
Segment descriptions synced to playback.
Structured tags, entities and classifications per asset.
Exploration by topic, date, entity or program.
Schema-mapped delivery into MAM / DAM.
A Vela-supplied GPU appliance — all processing in-facility, content never leaves.
Documented interfaces into existing archive systems.
VelaIris-DM turns raw assets into a searchable narrative archive — one coherent record at a time.
Vision, audio, on-screen text, reasoning.
Coherent prose plus structured metadata.
Find any segment in plain language.
Accuracy and speed across visual, audio and on-screen text — on production broadcast material, not synthetic clips.
Composite 91.5% (ASR 94% / OCR 89% / visual 92% / narrative 91%), 2–4× faster than real-time.
On a regional broadcast network’s ~87,000-hour archive: metadata fill 30%→85% within 90 days; clip research 25 minutes → 4 minutes.
Engagements start with a signal. Bring a representative slice of the archive and we run it through the description pipeline — you see exactly what VelaIris-DM produces, before any commercial conversation.
info@vela.com · (727) 507-5300