What should the public know about Palantir

Scary or beautiful? What does Palantir actually do?

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A startup that is actually no longer in the strict sense. A CEO supposedly in need of personal protection around the clock. Big investments that turn the company into billions. Palantir is remarkable without a doubt. What is behind the company and its technology?

A company shies away from the public

Discretion is part of the business of Palantir, which was founded in 2004 and borrows its name from the Tolkien saga "Lord of the Rings". One of the founding fathers is Peter Thiel, who took up an idea and technology from his previous company PayPal with the company. Computer scientists there had developed a methodology and software to detect fraudulent behavior in real time. Since no investor was really enthusiastic about the idea of ​​offering such services to other companies, Thiel quickly put his own money into Palantir. But the secrecy begins with the amount of this investment. Depending on the source, it should have traded between 30 and 40 million dollars. In-Q-Tel's investment of the rumored two million dollars looks rather modest. This insert is only interesting because it comes indirectly from the first (and for a long time the only) customer - the CIA.

How Palantir Helps Prevent Cyber ​​Attacks

Not only has a long time passed since these beginnings, but also plenty of money has flowed into Palantir. Most recently, a financing round of 880 million was completed in December 2015. So the donors have invested around $ 1 billion in the company.

Trust in the company should pay off for investors in the medium and long term. Last year, the company, which now has offices in New York, Washington and London, had total sales of just under $ 1 billion.

Exact knowledge and predictions as a business model

Palantir offers its solution in two areas:

  • Palantir Gotham: Huge amounts of data can be searched and analyzed in real time using various tools. It is this part of the company that made the CIA and NSA, the Department of Homeland Security, the Navy, and the Air Force customers of Palantir. In the prospectuses for investors, the company itself emphasizes its success in the fight against terrorism. Gotham consists of a whole range of visualization options and different tools. Progress displays, full-text searches and potential correlations can thus be determined. For this purpose, the software is fed with data pots from a wide variety of sources (structured data such as log files, Excel sheets, database content, unstructured data such as memos, e-mails, etc.). The information is usually available in separate systems. Gotham is now bringing these together. Last but not least, the product is now also positioned on the Palantir website as a big data solution for large companies.

The proximity to secret services and the rumors that Palantir was at least involved in the analyzes that led to the tracking of Osama bin Laden make Alex Karp, head of Palantir, a person who enjoys personal protection around the clock.

  • Palantir Metropolis: What are the trends in the stock markets? When is the optimal time for transactions? Can price manipulation be recognized? Metropolis, the second division, has dedicated itself to analyzing data from the financial sector. On this side, for example, Palantir counts JP Morgan among its customers. The financial services provider imports 500 gigabytes of data into Metropolis every day with the aim of discovering attempted fraud at an early stage.

Palantir Detecting Mortgage Fraud

Data analysis without a crowd of computer scientists

  • Palantir was founded in 2004 by Peter Thiel and Alex Karp.
  • The company specializes in analyzing large amounts of data in real time.
  • In contrast to other solutions, the queries and analyzes can be formulated in natural language, and results are available in real time.
  • Palantir counts security agencies and secret services among its customers and points to successes in the fight against terrorism.
  • Possible uses in e-commerce include fraud detection, goods control, trend analyzes, and predictions of customer behavior.
Solutions for business intelligence and data analysis are usually quite complex and often require in-depth knowledge of database languages ​​such as SQL or the development of complex commands. Without the help of trained computer scientists who take care of the merging of data and its analysis, not much can happen. Palantir (what Tolkien describes as "widely seeing") has found a way to carry out these analyzes using a surface that, at first glance, does not appear to be more complex than an office suite. Instead of SQL statements, queries can be formulated as the user knows from search engines. This analogy includes returning results. Instead of entering SQL commands into a BI solution and then waiting minutes or hours for the results, the Palantir user interacts with the data volumes in real time.

E-commerce needs data analysis

Conceptually and technologically, the user of Palantir can analyze and process data of any kind. And that is exactly what makes the company interesting for e-commerce.

  • The scams used by fraudsters are becoming more and more sophisticated and it is precisely the providers of marketplaces that have a vital interest in identifying possible frauds at an early stage.
  • Online shops and marketplaces are a popular target for cyber criminals and script kids who want to paralyze systems or copy user data. Palantir could detect such attacks in time.
  • What is often referred to as the "customer journey" is becoming more and more complicated to analyze when implementing omnichannel strategies. At this point, too, many e-commerce providers are likely to have high hopes for Palantir. Especially since the system can also be connected to other tools via APIs. Palantir could thus provide the logic that the large marketing clouds still lack to provide real-time predictions about purchasing behavior. The takeover of Fancythat in February 2015 proves that the company's considerations are definitely in this direction. The small company specialized in analyzing the buying behavior of customers with the aim of optimally managing stores.


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