We present a fully automated multi-agent framework for corporate due diligence and market analysis in venture capital. The system runs on an event-driven orchestration architecture, combining Large Language Models (LLMs) with real-time web retrieval to synthesize unstructured data into structured investment intelligence. A central technical contribution is a programmatic extraction pipeline that reverse-engineers the frontend-to-backend communication of the Greek Business Registry ($Γ$.E.MH.), querying dynamic endpoints to retrieve official financial filings that are then parsed using a layout-aware OCR extractor. A structural fallback mechanism explicitly flags data absence rather than generating unverified figures, directly targeting hallucination in financial contexts. All workflow artifacts are publicly available to support replication.

翻译：我们提出了一种全自动的多智能体框架，用于风险投资领域的公司尽职调查与市场分析。该系统基于事件驱动的协同架构运行，结合大语言模型与实时网络检索功能，将非结构化数据合成为结构化的投资情报。核心技术贡献在于一个程序化提取管线：该管线逆向解析希腊商业登记系统的前后端通信机制，通过查询动态端点获取官方财务申报文件，并利用布局感知型OCR提取器进行解析。针对金融场景中的幻觉问题，系统设计了结构性容错机制，在数据缺失时明确标记其不存在，而非生成未经验证的数值。所有工作流构件均已公开，以支持结果复现。