What We Believe
Palantir is a mission-focused company. Our team is dedicated to working for the common good and doing what's right, in addition to being deeply passionate about building great software and a successful company.
From protecting privacy and civil liberties to promoting open software to pursuing philanthropic engagements to a host of other initiatives, we put our values to work in the service of making the world a better place, every day.
Palantir Technologies is a mission-driven company, and a core component of that mission is protecting our fundamental rights to privacy and civil liberties. Since its inception, Palantir has invested its intellectual and financial capital in engineering technology that can be used to solve the world’s hardest problems while simultaneously protecting individual liberty. Robust privacy and civil liberties protections are essential to building public confidence in the management of data, and thus are an essential part of any information system that uses Palantir software.
Some argue that society must “balance” freedom and safety, and that in order to better protect ourselves from those who would do us harm, we have to give up some of our liberties. We believe that this is a false choice in many areas. Particularly in the world of data analysis, liberty does not have to be sacrificed to enhance security. Palantir is constantly looking for ways to protect privacy and individual liberty through its technology while enabling the powerful analysis necessary to generate the actionable intelligence that our law enforcement and intelligence agencies need to fulfill their missions.
We believe that privacy and civil liberties-protective capabilities should be “baked in” to technology from the start rather than grafted onto it later as an afterthought. By seamlessly integrating these features into our software, we reduce user friction that might otherwise create incentives to try to work around these protections. With the right engineering, the technologies that protect against data misuse and abuse can be the same technologies that enable powerful data analysis.
We also believe that privacy and civil liberties-protective technical capabilities must be combined with a rigorous set of policies to maximize their effectiveness. Audit logs are only effective when they are reviewed and access controls only protect information when they are used to limit data availability to those with particular needs and authorities. We work with our customers to advise them on how to use our technology to support effective privacy and civil liberties policies, and we educate advocates and policymakers as to our capabilities so that they can craft more informed law and policy.
Technological advances often raise novel privacy and civil liberties issues. Where the law is silent or undeveloped, Palantir consults with privacy and civil liberties advocates and some of the top legal experts in the world to figure out how to build our technology with safeguards that can be used as part of a responsible information handling regime. We obligate ourselves to do what is right, not just what is legal.
In October 2012, we created the Palantir Council of Advisors on Privacy and Civil Liberties (PCAP). The PCAP is an advisory body of independent experts in privacy law, policy, and ethics who help the PCL team understand and address some of the complex issues we encounter in the course of our work.
The Palantir PCL team meets with the PCAP regularly for discussion and exchange, including on such topics as:
Our obligations go beyond just our product and our customers. Palantir supports a number of privacy and civil liberties advocacy organizations around the world. We also are eager to lend our voice and technical expertise to academic and policy discussions that will shape the future of the fundamental freedoms that we hold dear.
We are proud of the work we are doing to ensure that data analysis is not just effective, but also reflects the values that are most important to us.
We are enormously grateful to the following internationally recognized privacy and civil liberties experts who currently serve on the PCAP:
Bryan Cunningham – Founder of Cunningham Levy LLP, Cunningham is a privacy, cybersecurity, and data protection lawyer and long-time senior counsel to Palantir, Bryan serves as the Executive Director of the PCAP.
Alex Deane – Managing Director at FTI consulting. Alex was a founder of Big Brother Watch, a prominent U.K. privacy and civil liberties advocacy organization. Alex previously served as Chief of Staff to David Cameron and Tim Collins during their respective terms as Shadow Secretaries of State for Education.
Susan Freiwald – A law professor at the University of San Francisco who frequently participates in electronic surveillance legislation and litigation efforts.
Robert Gellman – A privacy and information consultant who worked for nearly two decades on privacy issues in the U.S. Congress.
Chris Hoofnagle – Chris holds dual appointments as adjunct professor in the University of California Berkeley School of Law and the School of Information (where he is resident).
Nancy Libin – Partner at Jenner & Block, former Chief Privacy and Civil Liberties Officer of the U.S. Department of Justice, and former Counsel to then-Senator Joseph Biden on the Senate Judiciary Committee and at the Center for Democracy and Technology.
Sylvain Métille – Partner at the Swiss law firm HDC where he specializes in data protection, surveillance, and IT law. Sylvain also lectures on computer crime at Lusanne University.
Stephanie Pell – A private consultant specializing in privacy and civil liberties issues who formerly served in the Department of Justice as an Assistant US Attorney and later as Senior Counsel to the Deputy Attorney General.
Dan Solove – A law professor at George Washington University, author, and founder of TeachPrivacy, a company that designs privacy and security training programs.
Nico van Eijk – Professor of Media and Telecommunications Law and the Director of the Institute for Information Law at the University of Amsterdam. Nico is an expert in legal and technical topics related to privacy and civil liberties.
Daniel Weitzner – Founding Director, MIT Internet Policy Research Initiative, former White House Deputy Chief Technology Officer for Internet Policy and Co-founder of the Center for Democracy and Technology.
What does emancipation mean for your enterprise? Emancipation means freedom from constraints imposed by outdated ways of storing, managing, and analyzing data. Palantir liberates your data from these constraints, giving you the freedom to harness your data’s full potential, and to do it in days, not years.
Legacy systems cripple your enterprise, leaving you mired in an infrastructure designed for the past and unequipped for the future. Meanwhile, the future and its challenges are upon you. Your enterprise confronts adaptive adversaries and new challenges every day. You cannot solve these problems with incompatible data sets isolated in disparate places.
Cyber-security. Internal threats. Terrorism. Viral outbreaks. Health care distribution and quality. Insurance and mortgage pricing. Data monetization.
These challenges are core to your business and are unified by one theme:
Either your enterprise moves into the future, or the evolving landscape of adversaries will ensure it never does.
Palantir’s platform rapidly integrates your enterprise’s data—from any source and in any format, whether structured or unstructured. This gives you a secure point of access to all data, regardless of form or location. Palantir empowers analysis that is optimized for security, scalability, ease of use, and collaboration.
Palantir emancipates you from the past. And it does so very, very quickly. Within eight weeks, and in many cases within days, you will see operational results.
We take pride in designing, developing, and shipping great software. But our mission inspires us to be something more than just a product company. In a time of fiscal austerity and economic uncertainty, we deliver Silicon Valley culture to resource-constrained organizations in the form of powerful, open, extensible, and scalable platforms, on the backs of which people can solve their hardest problems and achieve world-changing outcomes. Adapting to the rapidly changing informational landscape when managing natural disaster recovery and relief operations. Finding foreclosure alternatives for troubled home lending assets. Improving operations while sending fewer soldiers downrange. Tracking down and rescuing missing and exploited children. These are just some of the extraordinary results that organizations have achieved with Palantir.
In 1965, Intel co-founder Gordon Moore made an observation that would come to be known as Moore’s Law. The amount of computing power that could be manufactured at a fixed cost had been doubling roughly every 18 months, and he predicted that this trend would continue for at least another 10 years. Moore’s Law has held true for half a century, and it has become shorthand for the entire Silicon Valley ethos—the belief that it is in the very nature of technology to deliver more for less, and that dedicated engineers can make improvements at an exponential rate without similar increases in cost. We reject the notion that constrained budgets necessarily entail a constrained ability to achieve positive outcomes. For organizations in crisis, we deliver the best software, the best engineering minds, and the conviction that even the hardest data problems yield to elegant solutions.
We are a platform company. That means we don’t create one-off solutions or solve the same problem from scratch over and over again. Instead, we ship open, extensible, scalable software platforms that can be deployed immediately against an entire class of problems facing a given industry. We also ship the world’s best engineering talent to optimize the software to meet a particular customer’s specific needs. By establishing a deep partnership with our customers, we can incorporate their requests and feedback directly into the future development of our software. This iterative process of continuous improvement produces productized solutions that can be implemented immediately at a fraction of the cost and with none of the risk of bespoke solutions.
Organizations today are facing problems of unprecedented scale and complexity. These are the problems that get us excited. These are the problems we seek out. Our greatest satisfaction comes from deploying our software at an enterprise, iterating on a solution quickly, and delivering substantive results in weeks, not months. By following this model, we have helped organizations achieve outcomes that have never before been possible. Born in Silicon Valley, battle-tested in the field and the commercial marketplace, our data fusion platforms are revolutionizing the way data is analyzed across an extraordinarily diverse range of enterprises.
Our culture of openness, collaboration, and continuous innovation is reflected in the software that we develop. In designing and developing our data platforms, we seek to combine the benefits of a commercially developed product—efficiency, reliability, and value—with the benefits of an open system—collaboration, flexibility, and customization. Simply put, we believe that open software is better software, and we have seen time and time again how openness enables organizations to achieve extraordinary outcomes with their data.
An open, extensible or plugin architecture promotes customization by enabling users to add and remove custom modules. Apple iOS is an example of software that features an open architecture. While iOS ships with a number of applications written by Apple developers, independent developers are also able to write applications that run on the iPhone. Open software platforms provide a base upon which developers can easily build new capabilities. Our platforms feature an open plugin architecture that allows organizations to add applications specially suited to their use cases.
An open architecture also promotes collaboration among systems. We know that software systems do not operate in a vacuum, and organizations need software that can integrate with their existing investments. An open architecture makes cross-platform interoperability possible. Our software has a proven record of interoperability with legacy systems and third-party software.
Organizations need to be able to access and understand their data despite whatever changes might be going on in their software environment. Systems get refactored, business processes change and analytical methodologies evolve. Data in closed, proprietary formats can be rendered inaccessible during these changes, risking the loss of crucial intelligence.
An open data platform maximizes data portability, making it easy for users to get their data both into and out of the system. A truly open data platform is one that can integrate data in closed, proprietary formats and export the same data in a variety of usable, non-proprietary, documented formats while maintaining data fidelity. Open data is like an escape hatch that protects users from vendor lock-in to any one software system. Our platforms combine comprehensive data integration capabilities, open standards data formats, robust integration APIs, and flexible export options to give organizations total control over their data.
It’s impossible to talk about openness in software without addressing the topic of open source. Open source software is software that is made available for use along with the source code that was written to create the software itself. This allows anyone to include, modify, and enhance someone else’s work as part of their own software.
Palantir’s ability to rapidly build and ship innovative software owes a great deal to the availability of high-quality open-source software that is freely available to integrate as components of larger works. A few high profile modules we use to power various pieces of our technology stack are Lucene (an open source search engine), Cassandra (an open source data warehousing server), and Hadoop (an open source implementation of Google’s MapReduce programming framework for super-scalable computation). In addition, Palantir’s software uses a long list of open source libraries to avoid re-inventing the wheel when high quality, tested, and trusted solutions to common programming challenges already exist.
As a group, Palantir’s engineers are bullish on the idea and reality of open source, so much so that we open source pieces of technology that we’ve built from scratch so that other organizations can benefit from the work that we’ve done—we’re paying it forward. Our first set of releases took place in late 2011. They live on the public open source repository GitHub; you can find them here. Going forward, time and resource permitting, we’ll be identifying other pieces of our software that make sense to release as open source components and making them available to the public.
Data mining is a phrase that is used to describe a variety of techniques for using statistical algorithms to extract patterns and insight from raw data. From detecting simple credit card fraud to recommending movies to suggesting a good place to eat in a new city, these inference models play an increasingly active role in our daily lives, and often for the better.
But data mining has its limitations. From a technical perspective, data mining techniques work best when three conditions are met:
If your data problem has these features, automated data mining techniques will often find most of the answers you seek. But if your problem doesn’t have these features, a different approach is likely to produce a better outcome.
Our software is designed to solve the hardest, messiest data problems in the world, which tend to have the following characteristics:
These problems also have a social aspect that’s often overlooked: no one wants machines to be the final arbiter when people’s lives and livelihoods are on the line.
In these contexts, the algorithmic approach fails. So we do something else. Our data platforms are designed to surface the totality of known data about a problem in a way that’s easily digestible by the best pattern matching and inference machinery ever devised: the human brain. Our software is designed to augment human intelligence through a symbiosis of mind and machine. You can think of our systems as an array of exponential levers to move data, levers operated by human mental might and insight. Any conclusions reached are done so by a person, not an algorithm. To the extent that we do use data mining techniques, they are used to narrow a very large universe of data to smaller sets of interesting data to be reviewed by human analysts.
Although our products are complex and fairly difficult to design and build, they serve a single, simple goal: surfacing data as information so that people can make sense of what’s going on.