AI Document Analysis

Overview#

The AI Document Analysis module provides automated analysis of uploaded documents through the platform's edge AI infrastructure. Documents are converted to structured markdown using a document-to-markdown service, then analysed by a language model to produce a summary, key insights, and extracted entities. The module handles the complete pipeline from file upload through conversion, analysis, and structured response delivery, with full usage tracking for cost management.

Key Features#

• File Upload and Conversion - Accept document uploads via multipart form data and convert them to clean markdown using a document processing service. The conversion preserves document structure including headings, lists, tables, and emphasis while stripping formatting that would consume unnecessary tokens during analysis.

• AI-Powered Analysis - The converted markdown is analysed by a language model to produce three structured outputs: a concise summary of the document's content, a list of key insights and findings, and a list of extracted entities (people, organisations, locations, dates, and other significant identifiers) found in the document.

• Token Usage Tracking - Every analysis request tracks token consumption across both the document conversion and analysis stages. The response includes raw token counts, billable units (with the standard 1.5x multiplier), and request latency, enabling organisations to monitor document analysis costs alongside other AI usage.

• Structured Response Format - Analysis results are returned in a consistent JSON structure with summary, insights array, and entities array fields, making it straightforward for consuming applications to display results without parsing unstructured text.

• Multi-Application Availability - The document analysis endpoint is available across both the main web application and the investigations application, enabling document analysis from any context where an analyst encounters a document that needs rapid assessment.

Use Cases#

• Evidence Triage - Upload documents received during investigations for rapid AI-powered summarisation and entity extraction, reducing the time needed to assess document relevance and identify key information.
• Intelligence Report Processing - Analyse incoming intelligence reports to extract mentioned entities, identify key findings, and generate summaries for inclusion in operational briefings.
• Document-Heavy Investigations - Process large volumes of documents (financial records, communications, reports) to identify patterns and extract entities that can be cross-referenced against the knowledge graph.
• Quick Assessment - Analysts upload an unfamiliar document and receive a summary and entity list within seconds, enabling rapid triage decisions about whether the document warrants detailed manual review.

Integration#

The AI Document Analysis module connects to the Cloudflare Workers AI infrastructure for document conversion and language model inference, the token usage management system for cost tracking, and the investigation and evidence management workflows for contextual document analysis. Analysis results can feed extracted entities into the entity resolution and knowledge graph systems.

Last Reviewed: 2026-04-02