按類型、技術、應用、最終用戶產業和部署模式分類的海事分析市場 - 2025-2030 年全球預測

預計 2024 年海事分析市場價值將達到 16.2 億美元，2025 年將成長至 17.8 億美元，到 2030 年將達到 28.2 億美元，複合年成長率為 9.60%。

主要市場統計數據
基準年2024年	16.2億美元
預計2025年	17.8億美元
預測年份 2030	28.2億美元
複合年成長率（%）	9.60%

海事分析已成為全球航運業營運效率、風險規避和策略決策的關鍵驅動力。隨著船舶產生海量性能和感測器數據，相關人員如今能夠利用先進的分析框架來獲取即時洞察。本報告探討了數據主導方法如何從根本上重塑傳統的航行、船隊管理和貨物運作模式。透過檢驗即時監控系統和預測模型等最新技術整合，本報告揭示了分析解決方案如何帶來實際競爭優勢的關鍵途徑。

隨著海上作業日益複雜，決策者越來越重視透明度和敏捷性。本入門分析旨在為理解核心市場趨勢奠定基礎，識別影響技術應用的關鍵因素，並為深入探索變革性轉變、監管動態和策略細分奠定基礎。隨著從傳統的手動報告向整合分析平台的轉變，該行業有望加速創新。這些發展凸顯了利用數據最佳化資源利用率、增強安全性和支援永續成長的重要性。

透過技術突破再形成海事分析的顛覆性變革；模式轉移

近年來，一系列變革性變化正在重新定義海事分析與營運現實之間的介面。基於機器學習的新型數位雙胞胎如今能夠提供預測性洞察，在設備故障發生之前進行預測。同時，物聯網感測器在船隊和港口基礎設施中的普及，正在推動前所未有的數據粒度，並實現即時決策循環。

評估2025年美國關稅調整對海事分析生態系統和全球貿易動態的深遠影響

美國2025年最新關稅的實施，對海事分析生態系統產生了多方面的影響。進口硬體組件和感測器技術的關稅上調，增加了部署高階分析解決方案的資本支出需求。因此，船隊營運商和港口當局開始重新評估籌資策略，通常會轉向區域供應商或探索租賃模式，以降低前期成本的增加。

解讀多面向的細分動態，揭示海事分析市場的核心服務技術應用與最終用戶促進因素

細緻的細分框架揭示了海事分析實現價值的多種途徑。按服務類型分類，公司既利用諮詢服務來指導策略實施，又利用數據分析服務將原始感測器輸出轉化為可操作的洞察。互補的維護和支援服務確保系統可靠性，而系統整合服務則將傳統架構與下一代平台連接起來。在軟體方面，資產績效管理應用程式專注於最佳化設備運作，資料視覺化工具將複雜的資料集轉換為直覺的儀表板，船隊管理軟體協調船舶部署，導航和航線軟體計算最佳航線，預測分析工具則預測維護需求和營運異常。

分析美洲、歐洲、中東和非洲以及亞太地區在海事分析採用方面的區域差異和協同作用

區域動態持續影響海事分析技術的應用軌跡。在美洲，大型航運公司的早期投資以及有利的法規環境推動了高級分析技術融入船隊管理和港口營運。公共和私營部門組織之間的聯合舉措正在推動以脫碳分析和彈性供應鏈建模為重點的試驗計畫。

與領先的行業創新者會面，他們正在使用先進的海事分析平台來塑造市場競爭並推動策略合作

領先的技術供應商和系統整合商正在透過持續創新和策略夥伴關係不斷提升海事分析能力。專注於自動化數位化的領先公司正在擴展產品系列，涵蓋雲端原生分析平台、預測性維護解決方案以及針對海事環境量身定做的整合物聯網框架。一些知名軟體供應商正在透過先進的視覺化模組和人工智慧決策引擎增強其船隊管理套件。

為產業領導者制定可行的策略議程和營運框架，以利用海事分析的進步

為了充分利用海事分析領域的發展勢頭，產業領導者應優先整合能夠提供大規模可操作洞察的人工智慧主導平台。與技術專家、學術機構和監管機構建立跨夥伴關係，可以加速解決方案的發展並確保符合新興標準。此外，將網路安全措施納入分析架構對於保護敏感營運資料免受不斷演變的數位威脅至關重要。

概述確保分析嚴謹性的穩健調查方法；海事分析研究中的全面數據整合和洞察有效性

本研究採用了混合調查方法，結合了原始訪談、二手資料分析和嚴格的檢驗通訊協定，以確保獲得全面且準確的洞察。首先，我們與高階主管、技術架構師和最終用戶代表進行了一系列深入討論，從定性觀點探討了市場促進因素、應用障礙和藍圖。這些定性研究結果也得到了二手資料（包括行業期刊、監管文件和供應商白皮書）的補充，從而捕捉新興趨勢和技術進步。

綜合關鍵分析的結論性見解：海事分析領域的策略意義與未來發展方向

本文的分析凸顯了數據主導方法對海上營運的變革性影響。透過整合先進的感測器網路、人工智慧和即時分析平台，相關人員可以前所未有地洞察船隊績效、港口效率和供應鏈韌性。法律規範和基礎設施投資的地區差異正在催生不同的技術創新中心，而不斷變化的關稅則凸顯了製定適應性採購和技術策略的必要性。

目錄

第1章：前言

第2章調查方法

第3章執行摘要

第4章 市場概述

第5章市場動態

• 航運業對數據驅動的洞察以最佳化營運的需求日益成長。
• 擴大人工智慧和機器學習的應用，以提高海上作業效率和安全性
• 增強的數據視覺化工具可以改善港口營運和貨物處理的決策
• 對配備先進分析系統的自主和遠端操作船舶的需求激增
• 加強海事分析公司與監管機構之間的合作，以確保合規性和數據標準化
• 先進的衛星和遙感探測技術提高了海上情境察覺和風險管理。
• 開發基於區塊鏈的平台，提高海上物流的透明度和安全性
• 利用巨量資料分析最佳化運輸路線和燃料消耗以降低成本
• 增加對預測性維護技術的投資，以減少海上作業的停機時間和成本
• 擴展物聯網整合，實現即時船舶追蹤和狀態監測

第6章 市場洞察

• 波特五力分析
• PESTEL分析

第7章 2025年美國關稅的累積影響

第 8 章：按類型分類的海事分析市場

• 服務
  • 諮詢服務
  • 維護和支援服務
  • 系統整合
• 軟體
  • 資產績效管理
  • 車隊管理軟體
  • 導航和路線規劃軟體
  • 預測分析工具

9. 海事分析市場（按技術）

• 人工智慧（AI）
• 區塊鏈
• 物聯網 (IoT)
• 機器學習（ML）

第 10 章：海事分析市場（按應用）

• 車隊管理
  • 燃料最佳化
  • 維護計劃
  • 路線最佳化
  • 船舶追蹤和監控
• 港口營運
  • 最佳化貨物物流
  • 連接埠擁塞監控
  • 連接埠效能分析
• 供應鍊和物流
  • 貨物追蹤
  • 庫存管理
  • 供應鏈可視性

第 11 章：按最終用戶產業分類的海事分析市場

• 國防和海軍
• 漁業和水產養殖
• 石油和天然氣
• 航運和物流
• 觀光和郵輪業

第 12 章：按部署模式分類的海事分析市場

• 雲端基礎
• 本地

13.美洲海事分析市場

• 美國
• 加拿大
• 墨西哥
• 巴西
• 阿根廷

14. 歐洲、中東和非洲海事分析市場

• 英國
• 德國
• 法國
• 俄羅斯
• 義大利
• 西班牙
• 阿拉伯聯合大公國
• 沙烏地阿拉伯
• 南非
• 丹麥
• 荷蘭
• 卡達
• 芬蘭
• 瑞典
• 奈及利亞
• 埃及
• 土耳其
• 以色列
• 挪威
• 波蘭
• 瑞士

第 15 章：亞太海事分析市場

• 中國
• 印度
• 日本
• 澳洲
• 韓國
• 印尼
• 泰國
• 菲律賓
• 馬來西亞
• 新加坡
• 越南
• 台灣

第16章競爭格局

• 2024年市場佔有率分析
• 2024年FPNV定位矩陣
• 競爭分析
  • Windward Ltd. by FTV Management Company, LP
  • OrbitMI, Inc.
  • ABB Ltd.
  • Avathon, Inc.
  • BigOceanData
  • Datalastic
  • Dataloy Systems AS
  • DNV AS by Stiftelsen Det Norske Veritas
  • Inmarsat Global Limited by Viasat, Inc.
  • Kongsberg Gruppen ASA
  • Kpler Holding SA
  • Leonardo SpA
  • Maritime Holdings Group Inc.
  • RightShip Pty Limited
  • Ship Data Center Co., Ltd. by Nippon Kaiji Kyokai
  • Shipnet AS by Volaris Group Inc.
  • ShipsDNA
  • Signal Group
  • Spire Global, Inc.
  • SRT Marine Systems plc
  • Veson Nautical LLC
  • Zeronorth A/S

第17章 研究人工智慧

第18章 研究統計

第19章 研究聯絡人

第20章 研究報導

第21章 附錄

The Maritime Analytics Market was valued at USD 1.62 billion in 2024 and is projected to grow to USD 1.78 billion in 2025, with a CAGR of 9.60%, reaching USD 2.82 billion by 2030.

KEY MARKET STATISTICS
Base Year [2024]	USD 1.62 billion
Estimated Year [2025]	USD 1.78 billion
Forecast Year [2030]	USD 2.82 billion
CAGR (%)	9.60%

Maritime analytics has emerged as a pivotal driver of operational efficiency, risk mitigation, and strategic decision-making across the global marine industry. With vessels generating massive volumes of performance and sensor data, stakeholders can now leverage advanced analytical frameworks to gain real-time insights. Throughout this report, we explore how data-driven approaches are fundamentally reshaping traditional paradigms of navigation, fleet management, and cargo operations. By examining recent technological integrations, including real-time monitoring systems and predictive modeling, we uncover the critical pathways through which analytics solutions deliver tangible competitive advantages.

As the complexity of maritime operations intensifies, decision-makers are prioritizing transparency and agility. This introductory analysis establishes the foundational context for understanding core market trends, identifies the key factors influencing technology adoption, and sets the stage for deeper exploration of transformative shifts, regulatory dynamics, and strategic segmentation. Transitioning from legacy manual reporting to integrated analytics platforms, the industry is poised for accelerated innovation. These developments underscore the importance of harnessing data to optimize resource utilization, enhance safety, and support sustainable growth

Unveiling Disruptive Transformations Reshaping Maritime Analytics through Technological Breakthroughs Regulations and Operational Paradigm Shifts

Recent years have witnessed a series of transformative shifts that are redefining how maritime analytics interfaces with operational realities. Emerging digital twins, powered by machine learning, now offer predictive insights that anticipate equipment failures before they occur. At the same time, the proliferation of Internet of Things sensors across fleets and port infrastructures has facilitated unprecedented levels of data granularity, enabling real-time decision loops.

As blockchain networks gain traction for secure cargo tracking and transaction transparency, stakeholders are collaborating across traditional boundaries to establish shared data ecosystems. Regulatory frameworks aimed at reducing carbon emissions have further accelerated the adoption of analytics-driven optimization models for fuel consumption and route planning. In parallel, edge computing architectures ensure that data processing occurs closer to the vessel or port, minimizing latency and enhancing resilience in connectivity-challenged environments. Together, these breakthroughs and operational paradigm shifts are ushering in a new era of efficiency and strategic foresight for maritime operators and service providers alike

Assessing the Far-Reaching Consequences of United States Tariff Adjustments on Maritime Analytics Ecosystem and Global Trade Dynamics in 2025

The introduction of updated United States tariffs in 2025 has exerted a multifaceted influence on the maritime analytics ecosystem. Heightened duties on imported hardware components and sensor technologies have escalated capital expenditure requirements for deploying advanced analytics solutions. As a result, fleet operators and port authorities have begun reevaluating procurement strategies, often turning to regional vendors or exploring leasing models to mitigate elevated upfront costs.

These tariff adjustments have also reverberated through global supply chains, compelling service providers to optimize logistics networks and revisit sourcing arrangements. Data-driven simulation tools are now being employed to identify alternative trade routes and consolidation points that minimize exposure to tariff-induced expenses. Simultaneously, the heightened cost environment has spurred innovation in software-centric solutions that reduce hardware dependencies, driving increased interest in cloud-based analytics platforms and predictive applications. Ultimately, the cumulative impact of these tariff measures underscores the importance of adaptable strategies and resilient technology architectures in maintaining operational continuity and competitive positioning

Deciphering Multifaceted Segmentation Dynamics to Illuminate Core Service Technology Application and End User Drivers in Maritime Analytics Market

A nuanced segmentation framework reveals the diverse pathways through which maritime analytics delivers value. By service type, organizations leverage both consulting services that guide strategic implementations and data analytics services that transform raw sensor outputs into actionable insights. Complementary maintenance and support services ensure system reliability, while system integration offerings bridge legacy architectures with next-generation platforms. On the software side, asset performance management applications focus on optimizing equipment uptime, data visualization tools translate complex datasets into intuitive dashboards, fleet management software coordinates vessel deployments, navigation and routing software calculates optimal courses, and predictive analytics tools forecast maintenance needs and operational anomalies.

Technology segmentation highlights the central role of artificial intelligence algorithms in automating data interpretation, blockchain networks in ensuring transactional integrity, Internet of Things frameworks in aggregating real-time telemetry, and machine learning models in identifying hidden performance patterns. Application-focused analysis emphasizes fleet management enhancements such as fuel optimization, maintenance scheduling, route optimization, and vessel tracking & monitoring; port operations benefits including cargo logistics optimization, port congestion monitoring, and port performance analytics; and supply chain & logistics improvements through cargo tracking, inventory management, and enhanced visibility across distribution networks. End-user industry adoption spans defense & naval operations seeking secure analytics, fisheries & aquaculture stakeholders optimizing yields, oil & gas enterprises enhancing offshore asset utilization, shipping and logistics companies streamlining cargo flows, and tourism & cruise line operators improving guest experiences. Deployment choices range from scalable cloud-based models offering rapid provisioning to traditional on-premise architectures that address data sovereignty and control requirements

Analyzing Regional Divergences and Synergies in Maritime Analytics Adoption across Americas Europe Middle East Africa and Asia Pacific Landscapes

Regional dynamics continue to shape the trajectory of maritime analytics adoption. In the Americas, early investments by major shipping lines and supportive regulatory environments have driven the integration of advanced analytics into fleet management and port operations. Collaborative initiatives among public agencies and private enterprises are fostering pilot programs focused on decarbonization analytics and resilient supply chain modeling.

Across Europe, Middle East & Africa, robust environmental regulations and significant port modernization projects in the Middle East have fueled demand for real-time congestion monitoring and predictive maintenance frameworks. European maritime hubs are leveraging analytics to comply with stringent emissions mandates while enhancing cargo throughput and berth utilization rates. In the Asia-Pacific region, rapid digital transformation led by leading ports in Singapore, China, and Australia is propelling extensive deployment of IoT-connected sensors and AI-driven optimization engines. This convergence of investments and strategic partnerships underscores the competitive landscape and highlights regional centers of excellence in maritime analytics innovation

Highlighting Leading Industry Innovators Leveraging Advanced Maritime Analytics Platforms to Shape Market Competition and Drive Strategic Collaborations

Industry-leading technology providers and system integrators are advancing the capabilities of maritime analytics through continuous innovation and strategic partnerships. Major enterprises specializing in automation and digitalization have expanded their product portfolios to include cloud-native analytics platforms, predictive maintenance solutions, and integrated IoT frameworks tailored to maritime environments. Several established software vendors have enhanced their fleet management suites with advanced visualization modules and AI-powered decision engines.

Collaborations between traditional marine engineering firms and technology firms are accelerating the development of digital twins and autonomous vessel prototypes. New entrants focusing on niche predictive analytics applications are also gaining traction by addressing specific operational challenges such as fuel efficiency and route optimization. This competitive landscape underscores the importance of open APIs, modular architectures, and co-development initiatives as companies strive to deliver end-to-end solutions that meet the evolving needs of diverse maritime stakeholders

Formulating Actionable Strategic Imperatives and Operational Frameworks for Industry Leaders to Capitalize on Maritime Analytics Evolution

To capitalize on the momentum in maritime analytics, industry leaders should prioritize the integration of AI-driven platforms that deliver actionable insights at scale. Establishing cross-sector partnerships with technology specialists, academic institutions, and regulatory bodies can accelerate solution development and ensure compliance with emerging standards. Moreover, embedding cybersecurity measures within analytics architectures is essential to safeguard sensitive operational data against evolving digital threats.

Leaders are advised to adopt flexible deployment frameworks that support hybrid cloud and on-premise configurations, enabling rapid scalability while addressing data governance requirements. Investing in workforce training programs will equip personnel with the skills needed to interpret complex analytical outputs and implement data-driven decision processes. Sustainable innovation should be reinforced through pilot projects that test alternative fuel optimization models and carbon tracking analytics. By championing interoperable solutions and fostering a culture of continuous improvement, organizations can harness the full potential of maritime analytics to secure long-term competitive advantage

Outlining Robust Research Methodology Ensuring Analytical Rigor Comprehensive Data Synthesis and Insight Validity in Maritime Analytics Study

This study applies a hybrid research methodology combining primary interviews, secondary data analysis, and rigorous validation protocols to ensure comprehensive and accurate insights. Initially, a series of in-depth discussions with senior executives, technology architects, and end-user representatives provided qualitative perspectives on market drivers, adoption barriers, and solution roadmaps. These qualitative findings were augmented by secondary research involving industry publications, regulatory filings, and vendor white papers to capture emerging trends and technological advancements.

Data synthesis was conducted through triangulation techniques, cross-referencing multiple sources to enhance reliability and mitigate bias. An expert advisory panel reviewed preliminary conclusions to validate assumptions and refine analytical frameworks. Quantitative insights were derived from anonymized operational datasets provided by leading maritime operators, ensuring empirical grounding for key observations. The resulting methodology delivers a balanced blend of strategic context and data-driven analysis, equipping decision-makers with robust evidence to inform technology investment and implementation roadmaps

Concluding Insights Synthesizing Key Analyses Strategic Implications and Future Trajectories in the Maritime Analytics Domain

The analysis presented herein underscores the transformative impact of data-driven approaches on maritime operations. By integrating advanced sensor networks, artificial intelligence, and real-time analytics platforms, stakeholders can achieve unprecedented visibility into fleet performance, port efficiency, and supply chain resilience. Regional variances in regulatory frameworks and infrastructure investments have created distinct centers of innovation, while tariff shifts have highlighted the need for adaptable procurement and technology strategies.

As market dynamics continue to evolve, organizations that embrace segmentation insights and operational best practices will be well positioned to lead the next wave of maritime innovation. This executive summary provides a strategic foundation for understanding critical developments, navigational challenges, and growth opportunities within the maritime analytics domain, offering a clear roadmap for stakeholders to harness data as a decisive competitive asset

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Segmentation & Coverage
• 1.3. Years Considered for the Study
• 1.4. Currency & Pricing
• 1.5. Language
• 1.6. Stakeholders

2. Research Methodology

• 2.1. Define: Research Objective
• 2.2. Determine: Research Design
• 2.3. Prepare: Research Instrument
• 2.4. Collect: Data Source
• 2.5. Analyze: Data Interpretation
• 2.6. Formulate: Data Verification
• 2.7. Publish: Research Report
• 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

• 4.1. Introduction
• 4.2. Market Sizing & Forecasting

5. Market Dynamics

• 5.1. Growing need for data-driven insights in the maritime industry to optimize operations
• 5.2. Increasing adoption of AI and machine learning for maritime operational efficiency and safety enhancements
• 5.3. Enhanced data visualization tools enabling better decision-making in port operations and cargo handling
• 5.4. Surge in demand for autonomous and remotely operated vessels supported by sophisticated analytics systems
• 5.5. Increased collaboration between maritime analytics firms and regulatory bodies to ensure compliance and data standardization
• 5.6. Advanced satellite and remote sensing technologies improving maritime situational awareness and risk management
• 5.7. Development of blockchain-based platforms for enhanced transparency and security in maritime logistics
• 5.8. Leveraging big data analytics to optimize shipping routes and fuel consumption for cost savings
• 5.9. Rising investment in predictive maintenance technologies to reduce downtime and costs in maritime operations
• 5.10. Expansion of IoT integration for real-time vessel tracking and condition monitoring

6. Market Insights

• 6.1. Porter's Five Forces Analysis
• 6.2. PESTLE Analysis

7. Cumulative Impact of United States Tariffs 2025

8. Maritime Analytics Market, by Type

• 8.1. Introduction
• 8.2. Services
  • 8.2.1. Consulting Services
  • 8.2.2. Maintenance & Support Services
  • 8.2.3. System Integration
• 8.3. Software
  • 8.3.1. Asset Performance Management
  • 8.3.2. Fleet Management Software
  • 8.3.3. Navigation & Routing Software
  • 8.3.4. Predictive Analytics Tools

9. Maritime Analytics Market, by Technology

• 9.1. Introduction
• 9.2. Artificial Intelligence (AI)
• 9.3. Blockchain
• 9.4. Internet of Things (IoT)
• 9.5. Machine Learning (ML)

10. Maritime Analytics Market, by Application

• 10.1. Introduction
• 10.2. Fleet Management
  • 10.2.1. Fuel Optimization
  • 10.2.2. Maintenance Scheduling
  • 10.2.3. Route Optimization
  • 10.2.4. Vessel Tracking & Monitoring
• 10.3. Port Operations
  • 10.3.1. Cargo Logistics Optimization
  • 10.3.2. Port Congestion Monitoring
  • 10.3.3. Port Performance Analytics
• 10.4. Supply Chain & Logistics
  • 10.4.1. Cargo Tracking
  • 10.4.2. Inventory Management
  • 10.4.3. Supply Chain Visibility

11. Maritime Analytics Market, by End-User Industry

• 11.1. Introduction
• 11.2. Defense & Naval
• 11.3. Fisheries & Aquaculture
• 11.4. Oil & Gas
• 11.5. Shipping & Logistics
• 11.6. Tourism & Cruise Line Industry

12. Maritime Analytics Market, by Deployment Mode

• 12.1. Introduction
• 12.2. Cloud-Based
• 12.3. On-Premise

13. Americas Maritime Analytics Market

• 13.1. Introduction
• 13.2. United States
• 13.3. Canada
• 13.4. Mexico
• 13.5. Brazil
• 13.6. Argentina

14. Europe, Middle East & Africa Maritime Analytics Market

• 14.1. Introduction
• 14.2. United Kingdom
• 14.3. Germany
• 14.4. France
• 14.5. Russia
• 14.6. Italy
• 14.7. Spain
• 14.8. United Arab Emirates
• 14.9. Saudi Arabia
• 14.10. South Africa
• 14.11. Denmark
• 14.12. Netherlands
• 14.13. Qatar
• 14.14. Finland
• 14.15. Sweden
• 14.16. Nigeria
• 14.17. Egypt
• 14.18. Turkey
• 14.19. Israel
• 14.20. Norway
• 14.21. Poland
• 14.22. Switzerland

15. Asia-Pacific Maritime Analytics Market

• 15.1. Introduction
• 15.2. China
• 15.3. India
• 15.4. Japan
• 15.5. Australia
• 15.6. South Korea
• 15.7. Indonesia
• 15.8. Thailand
• 15.9. Philippines
• 15.10. Malaysia
• 15.11. Singapore
• 15.12. Vietnam
• 15.13. Taiwan

16. Competitive Landscape

• 16.1. Market Share Analysis, 2024
• 16.2. FPNV Positioning Matrix, 2024
• 16.3. Competitive Analysis
  • 16.3.1. Windward Ltd. by FTV Management Company, L.P.
  • 16.3.2. OrbitMI, Inc.
  • 16.3.3. ABB Ltd.
  • 16.3.4. Avathon, Inc.
  • 16.3.5. BigOceanData
  • 16.3.6. Datalastic
  • 16.3.7. Dataloy Systems AS
  • 16.3.8. DNV AS by Stiftelsen Det Norske Veritas
  • 16.3.9. Inmarsat Global Limited by Viasat, Inc.
  • 16.3.10. Kongsberg Gruppen ASA
  • 16.3.11. Kpler Holding SA
  • 16.3.12. Leonardo S.p.A.
  • 16.3.13. Maritime Holdings Group Inc.
  • 16.3.14. RightShip Pty Limited
  • 16.3.15. Ship Data Center Co., Ltd. by Nippon Kaiji Kyokai
  • 16.3.16. Shipnet AS by Volaris Group Inc.
  • 16.3.17. ShipsDNA
  • 16.3.18. Signal Group
  • 16.3.19. Spire Global, Inc.
  • 16.3.20. SRT Marine Systems plc
  • 16.3.21. Veson Nautical LLC
  • 16.3.22. Zeronorth A/S

17. ResearchAI

18. ResearchStatistics

19. ResearchContacts

20. ResearchArticles

21. Appendix