Palantir Deep Dive: Why It Still Impresses

大家好，这里是Money or Life美股频道. This article will delve deeper into Palantir, building on a previous analysis, to explain why the company continues to impress. We will explore the reasons why it might be a worthwhile long-term investment, especially when considering potential future dips in the market. Perhaps this analysis can help you decide to add it to your portfolio.

Video Overview

This video is structured into four key parts:

1. Review of Previous Analysis: A recap of the main points from a previous video analyzing Palantir's business.
2. Financial Data Analysis: Presentation of a self-created chart highlighting crucial Palantir financial data and the underlying insights.
3. Competitive Advantage: Addressing the perception that Palantir simply "stacks blocks" of data and arguing that it possesses a strong moat.
4. Product Demonstrations: Showcasing three real-world applications of Palantir's products to demonstrate their value and capabilities.

Palantir's Fundamentals: A Quick Review

Let's quickly revisit the core concepts discussed in the prior video. Palantir's products are built upon the Foundry platform, which is based on ontology. In 2023, Palantir launched the vital AIP (Artificial Intelligence Platform). The prior video highlighted that Palantir's products provide AI Agent capabilities, visualization, and low-code/no-code functionality. This saves clients time, manpower, and resources.

• Foundry: The base platform for data integration and analysis.
• Ontology: The underlying theory for understanding relationships within data.
• AIP: AI platform acting as an interactive plug-in to Foundry.

The overall conclusion of the first Palantir video was that while the company has a strong moat, its valuation was high. However, this high valuation was justified by its immense potential.

Key Concepts: Foundry and AIP

Two critical concepts to understand Palantir are Foundry and AIP. Foundry serves as an operating system specifically designed for enterprise workflows. It features its own marketplace, fostering an ecosystem with third-party developers, much like Google's marketplace.

AIP isn't a standalone product but functions as an interactive plugin for Foundry. It leverages large language models (LLMs) like GPT-4 to enable seamless interaction between users and Palantir's tools. This dramatically reduces the learning curve for non-technical users, providing powerful visualization and low-code/no-code capabilities.

Ontology, paired with data, forms a knowledge graph. While not unique to Palantir, its effective application is key to their success. Many companies like Google already utilizes this technology.

Palantir's Financial Performance: Decoding the Data

Here's a breakdown of the crucial financial data points to understand Palantir's recent performance:

• Revenue (White Bars): Demonstrates quarterly revenue from Q3 2020 to Q4 2024.
• Adjusted Operating Margin (Pink Line): Shows the adjusted operating profit margin, which initially declined but rebounded strongly to 45% in Q4 2024.
• Year-on-Year Revenue Growth (Green Line): Tracks the revenue growth rate compared to the same quarter of the previous year, mirroring the V-shaped recovery of the operating margin.

The chart reveals two key insights. First, the quarterly revenue growth accelerated significantly from 2023 to 2024. Second, both the adjusted operating margin and year-on-year revenue growth exhibited a V-shaped recovery between late 2022 and early 2023.

These two percentages added together relate to the "Rule of 40." A company with a combined adjusted operating margin and year-on-year revenue growth exceeding 40% indicates strong performance. Palantir's results were 81% in Q3 2024 (45% + 36%), compared to a much lower figure just two years prior.

This impressive turnaround isn't coincidental. In early 2023, two significant events occurred: the release of GPT-4 and the introduction of Palantir's AIP. AIP, leveraging LLMs, significantly boosted both Palantir's operating margin and revenue growth, leading to consistently strong quarterly results.

While Palantir has been around for over two decades, its rapid growth is a more recent phenomenon. It's important to differentiate between Palantir's foundation and its current trajectory. The advent of mature LLMs and the launch of AIP have been transformative. Casetext, a legal tech startup utilizing LLMs, experienced similar rapid growth and was acquired, proving the transformative power of language models.

Palantir's Competitive Advantage: Beyond Data Stacking

Let's address the concern that Palantir is just "stacking blocks" of data and consider its competitive advantages. While the earlier analysis touched on the subject, further learning has revealed more insights.

• Customization is Key: Palantir offers a customized data application service, not a generic SaaS system. This is often criticized but is actually a core strength. Data application cannot be truly generic. Different companies, even within the same industry, have unique data types, storage methods, and supply chains. A general SaaS approach cannot effectively address these nuances. Deep customization is essential for data application now and in the future.
• Building a Data Ecosystem: Palantir builds enterprise data ecosystems, not just utilizing data. This involves the entire process, from preparation to utilization to system construction. Palantir integrates all data needs end-to-end. Once a client adopts Palantir, they become deeply integrated within its data ecosystem, making them less likely to switch providers.
• Dual Government and Commercial Business: Palantir uniquely serves both government and commercial clients, which gives it a competitive edge unmatched by any of its competitors.
• Strong Corporate Culture: Palantir's employees, driven by a strong sense of mission, particularly within the government sector, create a powerful and efficient team. The company promotes an aggressive, results-oriented culture.

Real-World Applications: AIPCON 6 Highlights

To illustrate Palantir's capabilities, let's examine three examples from the recent AIPCON 6 conference.

1. Heineken: Supply Chain Optimization: Showcases Palantir's traditional strength in supply chain management. It uses AI Agents to automatically optimize Heineken's complex beer supply chain. The company emphasizes the rapid implementation timeline (3 months from concept to reality).
2. European Cricket Network: Enterprise Operating System: Highlights Palantir's ability to provide a complete enterprise operating system beyond basic software tools. Palantir enables data integration and process optimization by managing human resources, budgeting, reporting, and logistics.
3. Parexel: Clinical Trial Data Analysis: Demonstrates Palantir's application in the medical field. It utilizes AI Agents to assist in the analysis of clinical trial data, reducing the timeline for submission readiness from 10-12 weeks to 3-6 weeks.

Heineken Example: AI Agents in Action

Heineken uses the following AI Agents to improve supply chain orchestration:

• Abu (Accelerate Order Before Out of Stock): Prioritizes orders for customers facing potential stockouts, optimizing the supply chain to prevent shortages.
• Dr. Skip Container into Inventory: Prioritizes containers at risk of incurring demurrage fees at ports, accelerating their entry into inventory to reduce costs.
• Neptune Execute Container Swaps: Allows for last-minute container swaps based on real-time demand, rerouting shipments to areas facing shortages even while in transit.

These AI Agents operate autonomously, eliminating the need for manual intervention, contrasting with traditional SaaS software that requires more human involvement.

European Cricket Network Example: Beyond Spreadsheets

The European Cricket Network highlights how Palantir replaced legacy spreadsheets and ERP systems. It provides a comprehensive operating system centered around AI and data application, supporting event scheduling, budgeting, human resources planning, and reporting.

Parexel Example: Transforming Clinical Trials

Parexel, a company focused on clinical trial data, was challenged by slow data processing and the need for highly skilled professionals. Palantir's AIP platform reduced the time for "submission readiness" by more than half through the following:

• Abstracting inputs, where all clinical trial data is prepared to be used in an organized and effective manner.
• Building a data model, where the correct inputs are entered as a data model.
• Building outputs, where the final file formats are produced.

The system can automatically fill data into prescribed tables, provide annotations, and identify and suggest fixes for errors.

Conclusion

This analysis aims to provide a deeper understanding of Palantir's business, its strengths, and its potential. I've been dollar-cost averaging in Palantir. Consider reviewing the first Palantir video for a more comprehensive overview. If you enjoyed this analysis, please subscribe to Money or Life 美股频道 for more. Thank you!