What is actually visible in extracted frames — objects, layout, on-screen text and scene composition grounded in image evidence.
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Grounding & evidence
How VisionaryAI Suite separates visual observation, interpretation and uncertain assumptions — with hallucination control, grounding scores and evidence sources in diagnostics.
Evidence layers in multimodal analysis
Contextual readings fused from Vision LLM output, speech, OCR, BLIP/CLIP signals and metadata — aligned to timeline events.
Low-confidence or ungrounded claims kept separate — with hallucination control, grounding scores and evidence sources surfaced in diagnostics.
Hallucination control
Evidence-based fusion separates grounded observations from interpretation. When the model lacks visual support, claims are down-ranked, flagged or omitted from automatic metadata writes — so search and review surfaces stay trustworthy.
Grounding scores and evidence sources are inspectable per timeline event. This is essential for archivists, researchers and compliance workflows where provenance matters.