Artificial intelligence for
ending global corruption

“Three things cannot long stay hidden: the sun, the moon and the truth.”

— BUDDHA

At Deep Discovery, we are in the business of discovering secrets. The secrets that undermine the health of civilization. Secrets hiding in plain sight in the vast ocean of data across the open Internet. Even as we fiercely defend the privacy of personal data on ordinary people.

In the past five years, intrepid investigative journalists have uncovered the shadowy underbelly of the global financial system in the Panama Papers, identified a hit squad team of Russian assassins, and Vladimir Putin’s secret construction of a multi-billion dollar personal palace, all using public data from the open web.

Deep Discovery’s own investigations with open data have uncovered a nuclear trafficking network, held local government officials accountable for their roles in inciting the attacks on the US Capital and identified slave labor in the gold mines of West Africa.

The United Nations estimates that corruption, money laundering, and other forms of illicit finance account for 5% of the global economy, $3.6 trillion each year. This undercuts national and international efforts to solve the world’s most pressing challenges, poverty, inequality, climate change, public health, and undermines the democratic foundations of a healthy society.

Peter Thiel famously said, “We wanted flying cars, but we got 140 characters.” Artificial intelligence is a revolutionary technology, but it is too often being used for squeezing out incremental improvements to consumers and daily businesses tasks, “first world problems”. Now is the time to put the power of AI to use in support of a revolution in the fight against corruption and bolster the democratic freedoms and wellbeing of billions.

At Deep Discovery, our ambition is to build the first social-impact unicorn focused on ending corruption on Earth, thereby improving the lives of billions of citizens. We believe recent innovations in machine learning, deep neural networks, representation learning, graph technologies, deep link analysis, entity and identity resolution, natural language processing, search and the emergence of web scale data make such an audacious mission tractable.

Our first products in development are a network-based financial crime risk scoring and analysis system for Know-Your-Customer (KYC) due diligence in the financial services sector and a sister product for network analysis to support investigative journalism. We are generating crime and corruption risk assessment scores for every single company in the world, and every director and officer of those companies.

Billions of data points in corporate registry data, professional profiles, social network profiles, news articles, legal case filings, shipping data, government contracts, leaks data, and much much more comprise the vast ocean of data on the open web within which the secrets of crime and corruption lie. The tools now exist to systematically mine this data to reveal the truth and restore the balance of power towards healthy democratic societies.

We are on a mission to change the world by piercing the veil of secrecy, creating a better world built upon a foundation of transparency. If you share these values and align to this mission, come partner with us or join our team.

Deep Discovery Team

Jeffrey Stein

Jeffrey Stein is a serial technology entrepreneur. After earning an MBA from Stanford Business School, he founded Open Data Registry, which used graph DB technology to provide traceability across global supply chains for consumer goods companies. 

He co-founded Orbital Insight, which pioneered the use of deep learning and AI to automate satellite imagery analysis. Jeffrey was VP of Business Development while the company grew from zero to over one hundred employees, raising $80 million in venture capital from Sequoia Capital, Google, Lux Capital, Bloomberg, and In-Q-Tel.

Russell Jurney

Russell Jurney is a data science generalist with 18 years of experience building apps from data using visualization and AI. He joined Jeffrey as co-founder and CTO of Deep Discovery. 

Previously, he founded Relato, which built a business graph to understand markets. He was CTO of Archipelo—a venture backed code search company, an early Senior Data Scientist in Product Analytics at LinkedIn and was the first Hadoop Evangelist at Hortonworks. Russell is the author of four O’Reilly books.

Investors

Careers

At Deep Discovery we’re passionate about two things.

Most research at most companies never leaves the lab. We don’t have that problem. Technical skills in machine learning and visualization are prerequisites for working here but they are not sufficient. You must be passionate about getting the best tools in the users’ hands where they can make the most impact. You need to develop domain expertise.

Interested in joining our team?

Please send us a resume, and any links to your portfolio of work, demonstrating your track record in shipping data-driven products.

Deep Discovery is hiring Machine Learning (ML) Engineers with experience with Natural Language Processing (NLP), Natural Language Understanding (NLU), Graph Neural Networks (GNN) or with ML for knowledge graphs, information extraction, entity (ER) and identity (IR) resolution, geospatial processing, time series analysis or risk scoring to help us build a 1.5 billion node business graph to better understand the world’s legitimate and illegitimate business… 

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Deep Discovery is hiring a Data Scientist with domain experience in Anti Money Laundering (AML) or Know Your Customer (KYC) to help us build and understand a 1.5 billion node business graph of legitimate and illegitimate business…

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Deep Discovery is hiring a Data Engineer to build the middleware software for connecting the user interface for our network-centric risk scoring system to the backend components that provide access to the 1.5 billion node business graph driving the system…

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Contact

Please include a LinkedIn profile or resume, link to your Github portfolio and a note explaining why you want to work here.