Building a File Semantic Analyzer: Guarding Outbound Data at Scale with AI

What this post added

This post details the engineering journey of building the File Semantic Analyzer (FSA). It elaborates on the problem of traditional DLP systems' limitations, the solution leveraging Generative AI for semantic understanding, and the engineering steps involved: data labeling, pre-processing (content extraction, OCR, intelligent chunking), the Generative AI interpretation engine (summarization, entity extraction, intent inference, explanation generation), and the classification/policy enforcement layer. It also outlines the architecture, including File Connector, File Processing, Prompt Building, Decision engine, and Manual Review. Key risks addressed include LLM hallucinations, context loss due to token limits, and the importance of human-in-the-loop validation. The post quantifies the impact in terms of accelerated incident response times and person-year savings.