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Visual Chart & Graph Interrogation

Standard PDF readers fail at images. Coral AI deploys its Vision-Language Model directly onto the document's graphical elements.

Core Architecture

How It Works Under The Hood

The Visual Chart & Graph Interrogation module is built on a highly optimized C++ and Python bridge. By bypassing standard Windows UI restrictions, Coral AI directly interfaces with system memory, native Win32 APIs, and DOM structures to achieve near-zero latency execution.

Pixel Analysis

Understands X/Y axes and legends of complex bar charts and line graphs.

Architecture Diagram Reading

Extracts technical flows from system architecture image blocks inside the PDF.

Hand-Written OCR

Can transcribe hand-written notes or annotations scribbled on the document pages.

Table Formatting

Converts visual tables in PDFs into clean Markdown or CSV formats for easy export.

Diagnostics

Execution Trace

~ > coral execute --module visual-chart-graph-interrogation --verbose
0.00ms [INFO] Initializing C++ memory hooks... OK
2.14ms [INFO] Bypassing UI thread restrictions... OK
5.89ms [INFO] Allocating vector buffer for LLM context...
8.22ms [WARN] Elevating privileges to Admin ring...
14.01ms >>> Execution payload delivered successfully.

Technical Specs

  • Latency< 15ms
  • RuntimeC++ / Py 3.11
  • PrivilegeRing 3 / Admin
  • Offline ModeRequires Internet

Agentic Integration

This module does not operate in isolation. It is dynamically invoked by the Coral PlannerAgent via JSON-RPC, allowing it to be chained endlessly with vision and memory modules.