Phase 6: AI Integration

Phase 6: AI Integration

Feed extracted data into local models for classification, summarization, and pattern detection. Ties directly into the Ollama + local AI stack.

Document Summarization

# Extract text then summarize with local model
pdftotext -layout report.pdf - | \
  ollama run mistral "Summarize this document in 3 bullet points:"

# Batch summarize all PDFs
find /data/docs -name '*.pdf' -exec sh -c '
  text=$(pdftotext -layout "$1" - 2>/dev/null)
  if [ -n "$text" ]; then
    summary=$(echo "$text" | head -500 | ollama run mistral "Summarize in 2 sentences:")
    echo "$1: $summary"
  fi
' _ {} \; > summaries.txt

Image Classification

# Classify image content with vision model
ollama run llava "What is in this image?" < photo.jpg

# Batch classify and tag
find ~/Photos -name '*.jpg' -exec sh -c '
  desc=$(ollama run llava "Describe this image briefly:" < "$1")
  echo "$1|$desc"
' _ {} \; > classifications.csv

Log Analysis

# Feed anomalous log entries to model for explanation
journalctl --since "1 hour ago" -p err | \
  ollama run codellama "Explain these Linux system errors and suggest fixes:"

# Correlate timeline anomalies
awk -F',' '$3 ~ /\.exe/ && $1 ~ /2026-03-1[0-2]/' timeline.csv | \
  ollama run mistral "Analyze these filesystem events for signs of compromise:"

Pattern Detection

  • Train local embeddings on known-good vs known-bad file metadata

  • Cluster photos by visual similarity for dedup beyond perceptual hashing

  • Classify documents by topic for automated filing

  • Anomaly detection on filesystem timelines