AI platform Disadvantages: Essential disadvantages of Palantir for European companies and institutions

Palantir Technologies is an American software company that specializes in the development and marketing of platforms for integration, analysis and administration of large, heterogeneous amounts of data. The company was founded in 2003 and has its headquarters in Denver, Colorado, USA. The founders include Peter Thiel and Alex Karp, who also acts as CEO.

Palantir is particularly known for two main products:

• Palantir Gotham: This platform is mainly used by security authorities, intelligence services and the military to link, visualize and analyze large quantities of structured and unstructured data. It is used, for example, in combating terrorism and fraud.
• Palantir Foundry: This platform is aimed at companies and organizations from business and industry. It supports data -driven decision -making processes, enables digital transformation and is used, among other things, in the financial industry, healthcare and industrial production.

Technologically, Palantir is based on semantic data modeling, granular access control and a highly scalable analysis engine, which allows you to connect data from a wide variety of sources without physically replicating them.

Palantir works worldwide and works for state institutions and companies in various industries. In addition to classic analysis functions, Palantir increasingly integrates artificial intelligence and machine learning into its platforms to enable predictive analyzes and automated decision -making processes.

The company has been listed since 2020 and generated sales of around $ 2.86 billion in 2024. Palantir is also a member of GAIA-X, a European initiative for safe and networked data infrastructure.

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Palantir Gotham and Foundry: Data integration with AI

Palantir Gotham and Palantir Foundry are not pure AI platforms, but extensive data integration and analysis platforms, which, however, increasingly integrate artificial intelligence (AI) and machine learning (ML).

Palantir Gotham was originally developed for use in the security and defense area. The platform uses advanced AI and ML algorithms to analyze large and heterogeneous amounts of data, to recognize patterns and to make predictions. AI is therefore a central component of Gotham's analysis functions, for example in the predictive police work or the evaluation of intelligence information.

Palantir Foundry is aimed at companies and authorities from various industries. Foundry also offers extensive options for integrating AI, especially since the introduction of Artificial Intelligence Platform (AIP), the generative KI and Large Language Models (LLMS) integrated directly into the platform. This enables companies to carry out AI-based analyzes, automation and decision-making processes on their own data.

Both platforms are therefore not “AI platforms” in the narrower sense such as pure ML frameworks, but modular data platforms that use AI as an integral part of analysis, sample recognition and automation. The actual AI innovation and functionality at Palantir is increasingly provided by the additional Artificial Intelligence Platform (AIP), which expands Foundry and Gotham and seamlessly integrates AI functions into the existing data processes.

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Geopolitical dependencies through Palantir: a danger to European companies

The use of Palantir software by European companies and authorities is associated with considerable legal, technical and reputation-related risks. These challenges range from data protection concerns to geopolitical dependencies that undermine the digital sovereignty of Europe. The following sections analyze the central problem areas in detail.

Data protection incompatibility and constitutional conflicts

Palantir's software solutions are fundamental to European data protection standards, in particular the GDPR. The Federal Constitutional Court ruled in 2023 that the use of Palantir Gotham in Hesse and Hamburg was unconstitutional, since the thresholds for data access were insufficiently defined and massively uninvolved people were affected. Specifically, the judges criticized:

• The uncontrolled linking of data from different sources (e.g. residents' registration register, mobile phone data)
• Missing transparency in the identification of data accommodation
• Inadequate control mechanisms to prevent profiling.

Despite technical adjustments, the basic problem remains: Palantir's AI algorithms operate as a black box, which makes data processing practically impossible. For companies, this means a permanent risk of warnings or fines, especially when processing sensitive personal data.

Geopolitical dependency and sovereign concerns

As a US company, Palantir is subject to the Cloud Act, which enables US authorities access to data stored by American companies-also outside the USA. This legal situation is an incalculable risk for European users, since:

• Business secrets or customer data could be forwarded to US positions
• Compliance is not guaranteed with EU data transfer rules (e.g. Privacy Shield Successor Signs).

This dependency has caused countries like France and Germany to develop their own solutions. France is working on national police software, while the German Interior Ministry is driving the “Joint Data House P20” project to avoid US providers. For companies, this means the risk of Vendor-Lock-in effects, combined with rising migration costs in the event of a politically forced exit.

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Reputation risks through political interdependencies

Palantir's image as a “Trump-related surveillance company” is burdening acceptance in Europe. Co -founder Peter Thiel, the main financier of Donald Trump's campaign in 2024, stands for an agenda that actively rejects European values ​​such as data protection and state transparency. These associations lead to:

• Public relation crises when disclosing Palantir use
• Resistance from employees and customers against cooperation
• Boycott calls of civil society groups such as Netzpolitik.org or digital courage.

This is an example of the failure of Palantir's collaboration with Europol, which was discontinued in 2024 based on public protests. For companies in the private sector, there is a risk of falling through Palantir usage in "guilt through association"-a risk that is particularly weighing for ESG-certified companies.

Technical and economic inefficiencies

Despite high license costs (from € 1 million/year for enterprise licenses), Palantir often delivers disappointing results in Europe:

• False adjustments to local legal systems: The software in Germany had to be expensive for simple police research, since original functions (e.g. automatic suspicion generation) violate German process law.
• Over-complexity: User reports from Hesse and NRW complain that 80% of the functions remain unused, while IT departments for maintenance work are overloaded at the same time.
• A lack of interoperability: Integration with European cloud services such as GAIA-X is only possible via cost-intensive adapter solutions.

In addition, Palantir does not offer exit strategies for data migrations-a problem that the NHS is currently burdening in Great Britain when replacing the system. The NHS (National Health Service) is the state health system of the United Kingdom

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Structural lack of transparency and lack of accountability

Palantir practices a secret culture that is diametrically opposed by European compliance requirements:

• The AI ​​algorithms are not subject to external auditization
• Even official supervisory centers do not get an insight into the data processing logic
• The company regularly refuses to provide information on data flows between subsidiaries (e.g. between Zurich and Denver).

This lack of transparency makes Palantir risky for companies, which-for example as part of the EU AI regulation-must provide evidence of the reliability of their AI systems. The recent revelations for the use of Swift data in Palantir's banking modules show how difficult violations of compliance requirements are detectable.

A systemic risk for European digital strategies

The disadvantages of Palantir are not primarily in technical weaknesses, but in a fundamental conflict of interest between the US technology agency and European sovereign efforts. While the company offers short-term efficiency gains in niche areas (e.g. military logistics), its dominance in the long term undermines the ability of Europe to build independent AI ecosystems. The current developments-from the promotion of European alternatives to tightened liability rules for US cloud providers-indicate that Palantir's market position in Europe is not sustainable in the medium term. For companies, this means that investments in Palantir infrastructures are subject to a high risk of beached cost as soon as regulatory or political framework conditions tip over.

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