AI-powered contract review skill with CUAD risk detection, market benchmarks, and lawyer-ready redlines. Works with Claude Code, Codex, Cursor, and 26+ tools.

A mapping between SDCs M&A database and the gvkey's in Compustat

Legal flags a risk. Finance flags another. We connect and cite. Open-source forensic M&A due diligence: 13 AI agents read your data room across 9 domains (Legal, Finance, Commercial, Tech, Cyber, HR, Tax, Regulatory, ESG), cross-reference findings no single reviewer connects, and trace every one to an exact page & quote.

SAMAR is an AI-driven tool designed to automate research and analysis processes for mergers and acquisitions (M&A), facilitating the generation of comprehensive reports. By leveraging advanced artificial intelligence techniques, SAMAR streamlines tasks such as data collection, financial modeling, and risk assessment.

Predicting merger decision outcomes of the European Commission: A Natural Language Processing and Machine Learning approach

A curated list of awesome acquisitions happened. Free feel to add more.

Script to set AutoResponder inbox rule on an Exchange mailbox. This can be used to inform relations and partners sending messages to support mergers, acquisitions or rebranding.

Events study: Kalman filter and neural network applications with a case study on M&A price run-ups

🏛️ A curated collection of the best resources, tools, books, podcasts, data providers, courses, and communities for Private Equity professionals.

M&A Multiples Index — open dataset of median EV/EBITDA & EV/Revenue valuation multiples for SMB & lower-middle-market deals, by sub-vertical and EV bracket. From 25,000+ real disclosed transactions. CC-BY-4.0. By ExitValue.ai.

Cultural Due Diligence 2.0 - Winner Qloo LLM Hackathon 🏆

Legora — collaborative legal AI workspace (formerly Leya)

Your AI ECM / IB analyst squad for M&A and IPOs

M&A Leadership Simulator puts players in the seat of a leader navigating the human side of a merger — integration decisions, cultural friction, communication timing, and the moments where the deal that looked good on paper starts to unravel in the hallway.

Hypothetical Monopoly Test

Interpretable ML for M&A: XGBoost + SHAP predicting post-merger operating performance across five outcome measures on 4,229 public-firm deals. MSc thesis, University of Twente (2026).

Public lite version of a personal multi-disciplinary ontology spanning forensic accounting, integrated data science, and valuation. Licensed under CC BY-NC-SA 4.0

Claude Code skill that builds branded M&A / fundraising investor shortlists — local DBs + Outlook + Firecrawl + Dropcontact → Excel with 31-column transaction pipeline.

A full-scale corporate finance and valuation framework of the Chevron-Hess Mega-Deal. Built entirely in Python, showcasing data driven DCF, LBO, and synergy analysis for strategic M&A evaluation.