人工智慧检测工具市场报告：趋势、预测和竞争分析（至 2031 年）

全球人工智慧检测工具市场前景光明，在网路安全、内容审核和学术诚信市场中都存在着机会。预计 2025 年至 2031 年期间，全球人工智慧检测工具市场将以 24.0% 的复合年增长率成长。该市场的主要驱动力是越来越多地采用人工智慧进行即时威胁检测和回应，越来越关注用于资料保护和隐私合规的人工智慧工具，以及对确保法规合规性的人工智慧解决方案的需求不断增长。

• Lucintel 预测，按类型划分，语音辨识将在预测期内实现高速成长。
• 从应用角度来看，网路安全预计将实现最高成长。
• 根据地区来看，预计亚太地区将在预测期内实现最高成长。

AI检测工具市场的策略性成长机会

人工智慧检测工具市场在各种应用领域呈现多种策略成长机会。识别并利用这些机会可以推动创新并创造竞争优势。这里我们介绍了人工智慧检测工具市场的五个关键成长机会，每个机会都提供了巨大的开发和部署潜力。

• 网路安全与威胁侦测：网路安全领域为人工智慧侦测工具提供了巨大的成长机会。网路威胁和先进攻击方法的增加推动了对能够改善威胁侦测和回应的先进人工智慧解决方案的需求。透过使用人工智慧分析网路流量并识别漏洞，企业可以改善其安全态势并降低风险。
• 预防金融诈骗：金融机构正在转向人工智慧侦测工具来打击诈欺并确保遵守法规。人工智慧模型可以分析交易模式并即时侦测异常，从而减少诈欺的发生。这一成长机会是由金融领域对更准确、更有效率的诈欺侦测机制的需求所驱动的。
• 医疗诊断与安全：在医疗保健领域，人工智慧检测工具被用于提高诊断准确性并保护患者资料。能够分析医学影像和电子健康记录是否存在异常的工具可以带来很大的好处。此外，保护敏感的医疗资讯免遭洩露和未授权存取至关重要，这为专门针对该领域构建的人工智慧解决方案创造了机会。
• 工业自动化和安全：人工智慧检测工具越来越多地应用于工业自动化，以提高安全性和业务效率。透过监控设备和流程，人工智慧模型可以预测故障并在安全隐患造成问题之前检测到它们。这一机会是由工业环境中对更有效的预测性维护和安全管理的需求所驱动的。
• 监管合规和风险管理：随着监管要求变得越来越严格，对人工智慧检测工具的需求日益增长，以确保合规和管理风险。可以监控和分析资料以符合 GDPR 和 CCPA 等法规的工具为面临越来越严格的监管审查的组织提供了有价值的解决方案。

这些策略性成长机会凸显了人工智慧检测工具透过改善网路安全、诈欺预防、诊断、工业安全和法规遵循来改变各个领域的潜力。透过专注于这些应用，公司可以推动创新并在不断发展的人工智慧检测工具市场中获得显着的竞争优势。

人工智慧检测工具市场驱动因素与挑战

AI检测工具市场受到影响其成长和发展的各种驱动因素​​和挑战的影响。这些因素包括技术进步、经济考量和监管压力。了解这些驱动因素和挑战对于驾驭市场和有效利用机会至关重要。

推动AI检测工具市场发展的因素如下：

• 技术进步：人工智慧和机器学习技术的进步是人工智慧检测工具市场的主要驱动力。深度学习和先进演算法等技术创新将增强检测工具的能力，提高其准确性和效率。这些技术改进使得能够更好地检测威胁和异常，从而推动市场成长。
• 网路安全威胁日益增加：日益严重的网路安全威胁和资料外洩正在推动对人工智慧侦测工具的需求。企业正在投资先进的解决方案来防御复杂的网路攻击并确保资料安全。这项动力将推动开发更强大、更有效的检测工具，以应对不断演变的安全挑战。
• 监管要求：围绕资料保护和隐私的严格监管要求正在推动人工智慧检测工具的采用。要遵守 GDPR 和 CCPA 等法规，需要先进的检测系统来监控和保护敏感资料。这种监管压力是市场成长的主要驱动力。
• 数位转型的成长：各行各业都在进行数位转型，这推动了对人工智慧侦测工具的需求。随着组织采用更多的数位技术和平台，他们需要先进的解决方案来管理和保护他们的数位资产。这一趋势正在推动AI检测工具市场的扩张。
• 投资和资金筹措：对人工智慧研究和开发的大量投资和资金筹措将推动检测工具的进步。创业投资、政府津贴和企业投资将有助于开发创新的人工智慧解决方案，加速市场成长和技术进步。

AI检测工具市场面临的挑战如下：

• 隐私和道德问题：与人工智慧检测工具相关的隐私和道德问题对市场构成了挑战。资料滥用、演算法偏见和透明度等问题正在受到审查，并影响检测工具的开发和部署。解决这些问题对于建立信任和确保负责任地使用人工智慧至关重要。
• 高成本和资源要求：开发和部署先进的人工智慧检测工具的高成本对市场采用构成了挑战。对大量运算资源和专业知识的需求可能会限制对这些工具的使用，特别是对于较小的组织和开发中地区。
• 整合和相容性问题：与现有系统和技术的整合和相容性问题可能会阻碍人工智慧检测工具的部署。确保与旧有系统和多样化 IT 环境的无缝整合是影响这些工具的有效性和采用的挑战。

影响人工智慧检测工具市场的驱动因素和挑战凸显了影响其成长的复杂动态。技术进步、日益增加的威胁和监管要求正在推动市场扩张，而隐私问题、高成本和整合问题则带来了重大挑战。利用这些因素对于成功利用人工智慧检测工具市场机会和满足不断变化的需求至关重要。

目录

第一章执行摘要

第二章 全球人工智慧侦测工具市场：市场动态

• 简介、背景和分类
• 供应链
• 产业驱动力与挑战

第三章市场趋势与预测分析（2019-2031）

• 宏观经济趋势（2019-2024）及预测（2025-2031）
• 全球人工智慧检测工具市场趋势（2019-2024）及预测（2025-2031）
• 全球人工智慧检测工具市场（按类型）
  • 语音辨识
  • 自然语言处理识别
  • 其他的
• 全球人工智慧检测工具市场（按应用）
  • 网路安全
  • 内容审核
  • 学术完整性
  • 其他的

第四章区域市场趋势与预测分析（2019-2031）

• 全球人工智慧检测工具市场（按地区）
• 北美人工智慧检测工具市场
• 欧洲人工智慧检测工具市场
• 亚太地区人工智慧检测工具市场
• 世界其他地区的人工智慧检测工具市场

第五章 竞争分析

• 产品系列分析
• 营运整合
• 波特五力分析

第六章 成长机会与策略分析

• 成长机会分析
  • 全球人工智慧检测工具市场成长机会（按类型）
  • 全球人工智慧检测工具市场成长机会（按应用）
  • 全球人工智慧检测工具市场各区域成长机会
• 全球人工智慧检测工具市场的新趋势
• 战略分析
  • 新产品开发
  • 全球人工智慧检测工具市场产能扩张
  • 全球人工智慧检测工具市场的企业合併
  • 认证和许可

第七章主要企业简介

• AI Detector Pro
• Passed.AI
• Kazan SEO
• Crossplag
• Hugging Face
• Originality.ai
• Copyleaks
• Content at Scale
• ZeroGPT
• OpenAI Text Classifier

The future of the global AI detection tool market looks promising with opportunities in the cybersecurity, content moderation, and academic integrity markets. The global AI detection tool market is expected to grow with a CAGR of 24.0% from 2025 to 2031. The major drivers for this market are the rising adoption of AI for real-time threat detection & response, the growing focus on AI tools for data protection and privacy compliance, and the increasing need for AI solutions to ensure regulatory adherence.

• Lucintel forecasts that, within the type category, speech recognition is expected to witness higher growth over the forecast period.
• Within the application category, cybersecurity is expected to witness the highest growth.
• In terms of regions, APAC is expected to witness the highest growth over the forecast period.

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Emerging Trends in the AI Detection Tool Market

The AI detection tool market is influenced by several emerging trends that reflect advancements in technology, changing security needs, and evolving regulatory landscapes. These trends shape how detection tools are developed and deployed, driving innovation and impacting various industries.

• Enhanced Threat Intelligence: AI detection tools increasingly incorporate enhanced threat intelligence capabilities to better identify and respond to cyber threats. By analyzing vast amounts of data and learning from emerging threats, these tools detect sophisticated attacks more effectively. This trend improves proactive threat management and response, enhancing overall cybersecurity.
• Integration of Machine Learning and Automation: The integration of machine learning and automation transforms AI detection tools by enabling automated threat detection and response. This allows for real-time analysis and action without human intervention, increasing efficiency and reducing the time to address potential threats. This trend is critical for managing large-scale data and complex attack vectors.
• Focus on Privacy and Compliance: With growing concerns about data privacy and regulatory compliance, AI detection tools are being designed with built-in privacy features and adherence to regulations like GDPR and CCPA. This trend ensures that detection systems not only protect against threats but also comply with legal standards, fostering trust and reducing regulatory risks.
• Development of Adaptive and Self-Learning Systems: AI detection tools are becoming more adaptive and self-learning, allowing them to improve their accuracy and effectiveness over time. These systems use feedback loops and continuous learning to refine their detection algorithms, making them more resilient to evolving threats and changing attack patterns.
• Expansion into New Industry Verticals: AI detection tools are expanding into new industry verticals beyond traditional cybersecurity applications, such as finance, healthcare, and industrial automation. This trend is driven by the need for specialized solutions that address industry-specific challenges, leading to the development of tailored detection tools that enhance security and operational efficiency.

These emerging trends reshape the AI detection tool market by enhancing capabilities, improving efficiency, and addressing regulatory and privacy concerns. As AI technology continues to evolve, these trends will drive innovation and influence how detection tools are utilized across various sectors, creating new opportunities and challenges for market participants.

Recent Developments in the AI Detection Tool Market

Recent developments in the AI detection tool market shape the future of security and fraud prevention. These developments reflect advancements in technology, changes in regulatory environments, and evolving market demands. Understanding these key developments provides insight into how the market is evolving and the implications for various stakeholders.

• Advancements in Real-Time Threat Detection: Recent advancements in real-time threat detection have significantly improved the effectiveness of AI detection tools. Techniques such as deep learning and advanced analytics enable tools to identify and respond to threats with minimal latency. This development enhances the ability to counteract cyberattacks and fraud in real-time, improving overall security posture.
• Emergence of AI-Powered Fraud Detection Solutions: AI-powered fraud detection solutions gain traction as they offer sophisticated algorithms to detect fraudulent activities across various sectors. These solutions leverage machine learning to analyze transaction patterns and identify anomalies, reducing false positives and improving accuracy. This development is crucial for sectors like finance and e-commerce where fraud prevention is critical.
• Integration with Cloud-Based Platforms: The integration of AI detection tools with cloud-based platforms expands their reach and scalability. Cloud integration enables organizations to deploy detection tools more flexibly and cost-effectively, providing access to advanced capabilities without heavy upfront investment. This development drives adoption among businesses of all sizes and across different industries.
• Focus on Ethical AI and Transparency: There is a growing emphasis on developing AI detection tools that are transparent and adhere to ethical standards. This includes ensuring that detection algorithms are explainable and that data usage complies with privacy regulations. This development aims to build trust with users and address concerns about AI ethics and accountability.
• Enhanced Collaboration and Information Sharing: Enhanced collaboration and information sharing among organizations and between public and private sectors are becoming more common. This development facilitates the exchange of threat intelligence and best practices, improving the effectiveness of AI detection tools and fostering a more coordinated approach to addressing security challenges.

These key developments significantly impact the AI detection tool market by improving real-time detection capabilities, expanding fraud prevention solutions, and enhancing scalability through cloud integration. As the market evolves, these developments will continue to shape the landscape of AI detection, driving innovation and addressing emerging challenges.

Strategic Growth Opportunities for AI Detection Tool Market

The AI detection tool market presents several strategic growth opportunities across various applications. Identifying and capitalizing on these opportunities can drive innovation and create competitive advantages. Here are five key growth opportunities in the AI detection tool market, each offering significant potential for development and deployment.

• Cybersecurity and Threat Detection: The cybersecurity sector presents a major growth opportunity for AI detection tools. With increasing cyber threats and sophisticated attack methods, there is a growing demand for advanced AI solutions that can enhance threat detection and response. By leveraging AI to analyze network traffic and identify vulnerabilities, organizations can improve their security posture and mitigate risks.
• Financial Fraud Prevention: Financial institutions seek AI detection tools to combat fraud and ensure regulatory compliance. AI models can analyze transaction patterns and detect anomalies in real time, reducing the incidence of fraudulent activities. This growth opportunity is driven by the need for more accurate and efficient fraud detection mechanisms in the finance sector.
• Healthcare Diagnostics and Security: In healthcare, AI detection tools are being used to improve diagnostic accuracy and protect patient data. Tools that can analyze medical imaging and electronic health records for anomalies offer significant benefits. Additionally, securing sensitive health information against breaches and unauthorized access is crucial, creating opportunities for specialized AI solutions in this sector.
• Industrial Automation and Safety: AI detection tools are increasingly applied in industrial automation to enhance safety and operational efficiency. By monitoring equipment and processes, AI models can predict failures and detect safety hazards before they cause issues. This opportunity is driven by the need for more effective predictive maintenance and safety management in industrial environments.
• Regulatory Compliance and Risk Management: As regulatory requirements become more stringent, there is a growing need for AI detection tools that ensure compliance and manage risk. Tools that can monitor and analyze data for compliance with regulations, such as GDPR and CCPA, offer valuable solutions for organizations facing increasing regulatory scrutiny.

These strategic growth opportunities highlight the potential of AI detection tools to transform various sectors by improving cybersecurity, fraud prevention, diagnostics, industrial safety, and regulatory compliance. By focusing on these applications, organizations can drive innovation and achieve significant competitive advantages in the evolving AI detection tool market.

AI Detection Tool Market Driver and Challenges

The AI detection tool market is influenced by a range of drivers and challenges that impact its growth and development. These factors include technological advancements, economic considerations, and regulatory pressures. Understanding these drivers and challenges is essential for navigating the market and leveraging opportunities effectively.

The factors responsible for driving the AI detection tool market include:

• Technological Advancements: Advances in AI and machine learning technologies are major drivers for the AI detection tool market. Innovations such as deep learning and advanced algorithms enhance the capabilities of detection tools, improving their accuracy and efficiency. These technological improvements enable better detection of threats and anomalies, driving market growth.
• Increasing Cybersecurity Threats: The rise in cybersecurity threats and data breaches fuels demand for AI detection tools. Organizations invest in advanced solutions to protect against sophisticated cyberattacks and ensure data security. This driver pushes the development of more robust and effective detection tools to address evolving security challenges.
• Regulatory Requirements: Stringent regulatory requirements related to data protection and privacy drive the adoption of AI detection tools. Compliance with regulations such as GDPR and CCPA necessitates the use of advanced detection systems to monitor and protect sensitive data. This regulatory pressure is a key driver for market growth.
• Growth in Digital Transformation: The ongoing digital transformation across industries increases the need for AI detection tools. As organizations adopt more digital technologies and platforms, they require advanced solutions to manage and secure their digital assets. This trend drives the expansion of the AI detection tool market.
• Investment and Funding: Significant investment and funding in AI research and development drive advancements in detection tools. Venture capital, government grants, and corporate investments support the development of innovative AI solutions, accelerating market growth and technological progress.

Challenges in the AI detection tool market include:

• Privacy and Ethical Concerns: Privacy and ethical concerns related to AI detection tools pose challenges for the market. Issues such as data misuse, algorithmic bias, and transparency are under scrutiny, impacting the development and deployment of detection tools. Addressing these concerns is crucial for building trust and ensuring responsible AI use.
• High Costs and Resource Requirements: The high costs associated with developing and deploying advanced AI detection tools are challenges for market adoption. The need for substantial computational resources and expertise can limit access to these tools, particularly for smaller organizations and developing regions.
• Integration and Compatibility Issues: Integration and compatibility issues with existing systems and technologies can hinder the deployment of AI detection tools. Ensuring seamless integration with legacy systems and diverse IT environments is a challenge that impacts the effectiveness and adoption of these tools.

The drivers and challenges impacting the AI detection tool market highlight the complex dynamics shaping its growth. Technological advancements, increasing threats, and regulatory requirements drive market expansion, while privacy concerns, high costs, and integration issues present significant challenges. Navigating these factors is essential for successfully leveraging opportunities and addressing the evolving needs of the AI detection tool market.

List of AI Detection Tool Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies AI detection tool companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the AI detection tool companies profiled in this report include-

• AI Detector Pro
• Passed.AI
• Kazan SEO
• Crossplag
• Hugging Face
• Originality.ai
• Copyleaks
• Content at Scale
• ZeroGPT
• OpenAI Text Classifier

AI Detection Tool by Segment

The study includes a forecast for the global AI detection tool market by type, application, and region.

AI Detection Tool Market by Type [Analysis by Value from 2019 to 2031]:

• Speech Recognition
• Natural Language Processing Recognition
• Others

AI Detection Tool Market by Application [Analysis by Value from 2019 to 2031]:

• Cybersecurity
• Content Moderation
• Academic Integrity
• Others

AI Detection Tool Market by Region [Analysis by Value from 2019 to 2031]:

• North America
• Europe
• Asia Pacific
• The Rest of the World

Country Wise Outlook for the AI Detection Tool Market

The AI detection tool market is rapidly evolving as advancements in artificial intelligence drive innovations in security, fraud prevention, and data analytics. Key developments in the U.S., China, Germany, India, and Japan reflect differing national priorities and technological capabilities. As AI technologies mature, countries deploy detection tools to address various challenges, from cybersecurity threats to financial fraud, each adapting solutions to their specific needs and regulatory environments. This overview highlights recent advancements and shifts in these major markets.

• United States: The U.S. is at the forefront of developing advanced AI detection tools, driven by significant investments in cybersecurity and fraud prevention. Companies like Microsoft and IBM lead with sophisticated AI solutions for threat detection and response. The focus is on enhancing real-time capabilities and integrating AI with traditional security systems to combat evolving threats. Additionally, there is a strong emphasis on ethical AI practices and compliance with data protection regulations like CCPA and GDPR, shaping the development and deployment of these tools.
• China: China has made significant strides in AI detection tools, particularly in surveillance and cybersecurity. The government's "AI 2.0" policy aims to boost domestic AI capabilities, including advanced detection systems for monitoring and cybersecurity. Companies like Huawei and Tencent develop state-of-the-art AI tools for detecting and mitigating cyber threats. However, the integration of AI in surveillance has raised concerns about privacy and ethical implications, influencing the regulatory landscape and international perceptions of China's AI capabilities.
• Germany: Germany focuses on developing AI detection tools that emphasize data protection and compliance with stringent European regulations. German companies, such as Siemens and SAP, integrate AI into security systems to enhance fraud detection and operational efficiency. The market is characterized by a strong emphasis on ethical AI and adherence to GDPR. Innovations include tools for detecting anomalies in financial transactions and securing industrial systems, reflecting Germany's commitment to combining technological advancement with rigorous data protection standards.
• India: India experiences growth in AI detection tools driven by increased digitalization and the need for cybersecurity. Indian startups and tech giants develop tools tailored to the unique challenges of the Indian market, such as financial fraud and cybersecurity threats. Initiatives like the National AI Strategy promote the development and deployment of AI-based detection systems. Despite rapid progress, challenges include limited infrastructure and resource constraints, which impact the scalability and effectiveness of these tools.
• Japan: Japan leverages its strengths in robotics and advanced technology to develop AI detection tools for various applications, including cybersecurity and fraud prevention. Companies like NEC and Hitachi are at the forefront of integrating AI into detection systems, focusing on improving accuracy and response times. The Japanese market is characterized by a blend of cutting-edge technology and traditional industry practices, aiming to enhance both security and operational efficiency while navigating regulatory frameworks and ethical considerations.

Features of the Global AI Detection Tool Market

Market Size Estimates: AI detection tool market size estimation in terms of value ($B).

Trend and Forecast Analysis: Market trends (2019 to 2024) and forecast (2025 to 2031) by various segments and regions.

Segmentation Analysis: AI detection tool market size by type, application, and region in terms of value ($B).

Regional Analysis: AI detection tool market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the AI detection tool market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the AI detection tool market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

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This report answers following 11 key questions:

• Q.1. What are some of the most promising, high-growth opportunities for the AI detection tool market by type (speech recognition, natural language processing recognition, and others), application (cybersecurity, content moderation, academic integrity, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
• Q.2. Which segments will grow at a faster pace and why?
• Q.3. Which region will grow at a faster pace and why?
• Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
• Q.5. What are the business risks and competitive threats in this market?
• Q.6. What are the emerging trends in this market and the reasons behind them?
• Q.7. What are some of the changing demands of customers in the market?
• Q.8. What are the new developments in the market? Which companies are leading these developments?
• Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
• Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
• Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Global AI Detection Tool Market : Market Dynamics

• 2.1: Introduction, Background, and Classifications
• 2.2: Supply Chain
• 2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2019 to 2031

• 3.1. Macroeconomic Trends (2019-2024) and Forecast (2025-2031)
• 3.2. Global AI Detection Tool Market Trends (2019-2024) and Forecast (2025-2031)
• 3.3: Global AI Detection Tool Market by Type
  • 3.3.1: Speech Recognition
  • 3.3.2: Natural Language Processing Recognition
  • 3.3.3: Others
• 3.4: Global AI Detection Tool Market by Application
  • 3.4.1: Cybersecurity
  • 3.4.2: Content Moderation
  • 3.4.3: Academic Integrity
  • 3.4.4: Others

4. Market Trends and Forecast Analysis by Region from 2019 to 2031

• 4.1: Global AI Detection Tool Market by Region
• 4.2: North American AI Detection Tool Market
  • 4.2.1: North American Market by Type: Speech Recognition, Natural Language Processing Recognition, and Others
  • 4.2.2: North American Market by Application: Cybersecurity, Content Moderation, Academic Integrity, and Others
• 4.3: European AI Detection Tool Market
  • 4.3.1: European Market by Type: Speech Recognition, Natural Language Processing Recognition, and Others
  • 4.3.2: European Market by Application: Cybersecurity, Content Moderation, Academic Integrity, and Others
• 4.4: APAC AI Detection Tool Market
  • 4.4.1: APAC Market by Type: Speech Recognition, Natural Language Processing Recognition, and Others
  • 4.4.2: APAC Market by Application: Cybersecurity, Content Moderation, Academic Integrity, and Others
• 4.5: ROW AI Detection Tool Market
  • 4.5.1: ROW Market by Type: Speech Recognition, Natural Language Processing Recognition, and Others
  • 4.5.2: ROW Market by Application: Cybersecurity, Content Moderation, Academic Integrity, and Others

5. Competitor Analysis

• 5.1: Product Portfolio Analysis
• 5.2: Operational Integration
• 5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

• 6.1: Growth Opportunity Analysis
  • 6.1.1: Growth Opportunities for the Global AI Detection Tool Market by Type
  • 6.1.2: Growth Opportunities for the Global AI Detection Tool Market by Application
  • 6.1.3: Growth Opportunities for the Global AI Detection Tool Market by Region
• 6.2: Emerging Trends in the Global AI Detection Tool Market
• 6.3: Strategic Analysis
  • 6.3.1: New Product Development
  • 6.3.2: Capacity Expansion of the Global AI Detection Tool Market
  • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global AI Detection Tool Market
  • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

• 7.1: AI Detector Pro
• 7.2: Passed.AI
• 7.3: Kazan SEO
• 7.4: Crossplag
• 7.5: Hugging Face
• 7.6: Originality.ai
• 7.7: Copyleaks
• 7.8: Content at Scale
• 7.9: ZeroGPT
• 7.10: OpenAI Text Classifier