RavenPack

ravenpack.com ↗ ·Marbella ·Series B

RavenPack is a financial data analytics company that uses NLP and AI to turn unstructured content — news, filings, transcripts and over 40,000 web and social sources — into structured, machine-readable analytics and sentiment signals for hedge funds, banks and asset managers. Founded in 2003 in Marbella, Spain, it is a mature, venture-backed scaleup (~200 employees, offices in Marbella and New York) that raised a $20M Series B led by GP Bullhound in July 2024 to launch Bigdata.com, its AI research assistant for finance. It was named one of VivaTech's Top 100 Scaleups in Europe.

Founded
2003
Founders
1
Total funds raised
$35M+
Rounds
4
Investors
5
Last round
Dec 2025
SectorsAI & Data, Fintech, Enterprise Software, Financial Data & Analytics, NLP Start-up MapAI & Data › AI monitoring & insights

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Founders

Armando Gonzalez
Co-Founder & CEO

Global models 5

AlphaSense
United States · www.alpha-sense.com ↗
Sells AI and NLP search and analytics over filings, transcripts, news and expert content on subscription to investment firms and corporates.
$1.4BComparable
Dataminr
United States · www.dataminr.com ↗
Turns unstructured public web, social and news data into real-time AI-generated event signals, sold on subscription, with financial institutions as an original core market.
$1.05BComparable
Hebbia
United States · www.hebbia.com ↗
Sells an AI research assistant that reads filings and documents for asset managers, banks and hedge funds, much like RavenPack's Bigdata.com.
$160MComparable
Kensho
United States · www.kensho.com ↗
Built NLP and machine-learning analytics that turn unstructured financial text and events into structured data for banks and investors, before S&P Global acquired it.
$67MComparable
Accern
United States · www.accern.com ↗
Sells NLP-derived news and sentiment signals and no-code AI analytics built from unstructured sources to asset managers and banks.
$40MComparable

In the same niche 18 others

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Notes: Most funded first

Investors 5

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Funding rounds 4

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