财报前瞻 | Palantir(PLTR.US)Q3财报公布在即 AI热潮持续涌动之际营收增长有望再提速

Core Viewpoint - Palantir Technologies is expected to report a significant revenue growth of 50.7% year-over-year for Q3 2025, reaching $1.09 billion, with an adjusted EPS of $0.17 [1] Group 1: Recent Performance - In Q2 2023, Palantir reported a revenue increase of 48% year-over-year, surpassing market expectations of 38%, marking the eighth consecutive quarter of accelerating revenue growth [4] - The company's U.S. business revenue surged by 68% year-over-year, with government business growing by 53%, largely due to a $10 billion, 10-year contract with the U.S. Department of Defense [4] - U.S. commercial revenue skyrocketed by 93% year-over-year, becoming the main driver of overall business growth, while international market growth remains slower [4] Group 2: Recent Contracts and Collaborations - Palantir has secured significant contracts recently, including a memorandum of understanding with the Polish Ministry of Defense, focusing on cybersecurity and AI collaboration [5] - In mid-October, Palantir announced a partnership with Snowflake to integrate their AI data cloud with Palantir's AI platform [5] Group 3: Stock Performance and Market Position - Palantir's stock has increased over 165% this year, driven by its expanding influence in the AI application sector and rising demand for its unique AI ecosystem and applications [5] - The company primarily serves the U.S. government and global defense and intelligence agencies, while also generating substantial revenue from large corporations [5] Group 4: AI Platform Launch - In 2023, Palantir launched its AI platform (AIP), which has gained widespread attention and is being used by over 100 organizations across various sectors, including healthcare and automotive [6] - The AIP platform features an AI assistant similar to ChatGPT, enabling businesses to analyze and make decisions based on big data with low technical barriers [6] - The platform integrates with Palantir's existing data analysis ecosystem, allowing users to efficiently apply generative AI to data analysis, enhancing insights and operational efficiency [6]