A Multi-Agent Orchestration Framework for Venture Capital Due Diligence
On the map: LLM agents and tool use → Financial trading and forecasting agents
Abstract (arXiv)
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 (Gamma.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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 7 of its 12 references that are in the map. First posted on arXiv 13 May 2026.
Builds on
7 of 12 references.
Closest ancestors · 1
Same direction, newest first
Other references · 6
- 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
- 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,906
- 2023MetaGPT: Meta Programming for A Multi-Agent Collaborative Frameworkcited by 1,761
- 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,422
- 2023BloombergGPT: A Large Language Model for Financecited by 923
- 2023FinGPT: Open-Source Financial Large Language Modelscited by 244
Built on by
Citing papers per year: 2026: 1.
1 paper.
- 2026Agentic Trading: When LLM Agents Meet Financial Marketscited by 7
- 2026Agentic Trading: When LLM Agents Meet Financial Markets19 May 2026
Similar, not cited
Close in wording, no citation either way
- 2026DSA: Evidence-Aware LLM-Agent Orchestration for Multi-Market Stock Research
- 2026DIALECTIC: A Multi-Agent System for Startup Evaluation
- 2026OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents
- 2026Toward Expert Investment Teams:A Multi-Agent LLM System with Fine-Grained Trading Tasks
- 2025Structuring the Unstructured: A Multi-Agent System for Extracting and Querying Financial KPIs and Guidance
- 2024Enhancing the Efficiency and Accuracy of Underlying Asset Reviews in Structured Finance: The Application of Multi-agent Framework
- 2025FinDeepResearch: Evaluating Deep Research Agents in Rigorous Financial Analysis
- 2025The Gaining Paths to Investment Success: Information-Driven LLM Graph Reasoning for Venture Capital Prediction