AI Report Writing System

The Challenge

Penetration testing engagements generate large volumes of technical findings data. Translating this into polished, boardroom-ready documentation is time-consuming and requires a precise writing register that is difficult to maintain consistently across multiple concurrent engagements. Common failure modes include technical jargon in executive summaries, invented impacts not supported by source data, and inconsistent severity ordering. Any of these risk embarrassing the consultancy in front of FTSE 100 clients.

The Solution

We built an AI-assisted report writing system that generates two distinct document sections from raw findings data: an Assessment Summary for board-level readers and a Key Findings section for technical teams. The system applies strict quality controls throughout, and a final AI quality assurance pass checks every output against a comprehensive set of writing standards before it reaches the writer.

Our Approach

• Status-triggered workflow initiates automatically when project data is ready, no manual handoff required
• API retrieval pulls all findings, severity ratings, and status flags for the engagement
• Template generation structures findings by issue type and severity, with audience-appropriate guidance pre-populated
• Human review stage preserves expert judgement at the point where it adds the most value
• AI quality assurance pass enforces writing standards, British English compliance, and structural completeness before sign-off

{
  "technologies": [
    "Python",
    "OpenAI",
    "Anthropic Claude",
    "REST APIs",
    "Project Management Integration"
  ]
}