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QiEvidence Domain (QiEn)

Purpose

QiEvidence (internal engine name: QiEn) is a local-first evidence intelligence module that transforms raw multimedia and documents (videos, photos, PDFs, audio, screenshots, etc.) into a structured, cross-referenced, searchable evidence archive.

Core capabilities: - Timestamped transcription and visual event extraction - Neutral, cold, objective narration (no emotion, no speculation, no mind-reading) - Entity normalization and tracking (people, vehicles, locations, accounts, etc.) - Automated contradiction / inconsistency detection - Master timeline assembly across all artifacts - Human review queue for uncertain or conflicting items

It is a disciplined evidence-processing engine with two brains: - Extractor: Factual, structured output only. - Analyst: Cross-referencing, flagging, and neutral narration.

Folder Structure

The local execution environment uses a standardized folder hierarchy:

/QiEvidence/
├── input/
│   ├── videos/
│   ├── photos/
│   ├── documents/
│   └── other/
├── working/
│   ├── audio/
│   ├── frames/
│   └── transcripts/
├── output/
│   ├── events/
│   ├── entities/
│   ├── timelines/
│   ├── reports/
│   └── reviews/
└── archive/ (hashed originals + metadata)

Schema: qievidence

The domain uses the following tables, linked to qione.tenants and qicase.cases.

Table Description
evidence_records Master artifact registry (one row per file)
evidence_segments Chunked slices of long media/documents
evidence_entities Canonical people, vehicles, locations, accounts, etc.
evidence_entity_mentions Join table (where each entity appears)
evidence_events Observed or extracted events
evidence_claims Statements/assertions extracted from content
evidence_observations Machine-grounded visual/textual facts (non-claims)
evidence_links Cross-references between any two objects
evidence_conflicts Detected inconsistencies (the “money” table)
evidence_timelines Named timeline containers
evidence_timeline_items Ordered items in timelines
evidence_reviews Human review queue

Processing Pipeline

  1. Ingest: Hash file, read metadata, assign evidence ID, store in evidence_records.
  2. Extract:
  3. Audio → faster-whisper → transcript.
  4. Video → ffmpeg keyframes → Qwen2.5-VL observations.
  5. Photos/Docs → OCR + Qwen2.5-VL description.
  6. Structure: Populate segments, entities, events, claims, observations.
  7. Link & Compare: Build links and run contradiction scanner.
  8. Timeline Assembly: Populate timelines and items.
  9. Narrate: Final cold, logical report using strict prompt rules.
  10. Review: Push uncertain/conflicting items to evidence_reviews.

Narration Rules

  • No emotion words.
  • No speculation or intent inference.
  • Separate Observed / Stated / Uncertain.
  • Preserve timestamps and source IDs.
  • Mark unclear audio/visuals explicitly.