About
Dealflow is an AI-powered M&A Deal Intelligence Agent that automatically monitors public sources, extracts structured deal data, and surfaces it in a searchable dashboard — so deal professionals spend less time on manual research and more time on judgment calls.
Investment Bankers
Track live deal flow, comps, and stage progression across mandates.
PE Professionals
Monitor acquisition targets, portfolio sector activity, and valuation multiples.
Corporate Development
Stay ahead of strategic deal activity in your sector before it closes.
Dealflow crawls 51 curated sources daily — SEC EDGAR filings, global press wires, law firm tombstone pages, PE firm portals, and AI-powered news search. Each document is passed through GPT-4o, which extracts structured deal records: parties, value, sector, stage, XBRL financials, and EV multiples. Deals are confidence-scored and deduplicated before reaching the dashboard.
8-K, S-4, 10-K, 10-Q, DEF 14A, DEFM14A, SC TO-T, SC 13D, SC 13G, Form 4
PR Newswire (US + UK), BusinessWire, GlobeNewswire (US + Europe), Canadian Newswire
CNBC, Nasdaq, Seeking Alpha, MarketWatch, The Street, Reuters, AFR, HKEX
Kirkland & Ellis, Skadden, Latham & Watkins, Weil Gotshal, Paul Weiss
Blackstone, KKR, Apollo, Carlyle, TPG, Warburg Pincus, Advent International
Evercore, Lazard, Moelis, Houlihan Lokey, PJT Partners
Tavily, Serper, NewsAPI — private deal coverage and deal valuation
Deal records are AI-extracted from public sources and assigned a data quality score (high / medium / low) based on source type, filing type, and whether both parties are identified. All data is sourced from publicly available filings and news — nothing on Dealflow constitutes financial advice. Always verify deal terms through primary sources before acting on them.
Dealflow is built and maintained by Nathan Lara as a personal project. It grew from a RAG-based research prototype into a full-stack deal intelligence platform with live data ingestion, LLM extraction, financial modelling, and a production dashboard.
Questions, feedback, or data issues — email nathanlara1357@gmail.com