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Enterprise AI Company Landscape Breakdown 2024

Artificial intelligence is revolutionizing every industry with various use cases. Demand for AI products grows as more companies shift their legacy systems with digital products to survive in the competitive business landscape.  However, the AI vendor landscape is crowded, and most executives or decision-makers have limited knowledge of the AI landscape. Therefore, we compiled a comprehensive categorization of AI companies based on their sizes, technology, industry, business function, geography, business model & services they offer. Yet, this list does not contain all AI vendors. If you want to see our comprehensive and up-to-date AI vendor lists, feel free to check out AIMultiple.com, where we list 8,000+ AI vendors based on their technology offerings.

Breakdown by size

Tech-giants

The global AI race is getting fierce, and companies such as Google, Facebook, Amazon, Microsoft, and Apple are developing new AI products& services and making new AI acquisitions. Apple is leading in the number of AI acquisitions, and Microsoft has the most AI-related patents (more than 18,000) in its portfolio.

Tech giants are making more acquisitions every year
Source: CBInsights

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Startups

Total funding ≥ $1 Billion

As of October 2020, 5 startups raised more than or equal to $1 Billion in funding:

  • SenseTime: AI company that focuses on computer vision and deep learning technologies.
    • Funding*: $2.6B
    • Headquarters: Hong Kong
    • # of employees**: 1001-5.000
  • MEGVII: The company builds AI Engines that power various AI applications.
    • Funding: $1.4B
    • Headquarters: China
    • # of employees: 1.001-5.000
  • UiPath: RPA company that focuses on automation via artificial intelligence.
    • Funding: $1.2B
    • Headquarters: United States
    • # of employees: 1.001-5.000
  • OpenAI: A non-profit AI research company that focuses on safe artificial general intelligence.
    • Funding: $1B
    • Headquarters: United States
    • # of employees:51-200
  • Nuro: A robotics company that develops autonomous delivery vehicles.
    • Funding: $1B
    • Headquarters: United States
    • # of employees: 501-1.000

$1 Billion > Total funding ≥ $500 Million

  • Zoox: AI robotics company that provides mobility-as-a-service and self-driving car services.
    • Funding: $955M
    • Headquarters: United States
    • # of employees:1.001-5.000
  • UBTech Robotics: Robotics company that specializes in humanoid robots.
    • Funding: $940M
    • Headquarters: China
    • # of employees: 501-1.000
  • ThoughtSpot: AI company that develops business-intelligence analytics search software.
    • Funding: $743.7M
    • Headquarters: United States
    • # of employees: 501-1.000

$500 Million > Total funding ≥ $100 Million

  • DataRobot: The most funded autoML company that enables customers to prepare their data, create and validate machine learning models.
    • Funding: $430.6M
    • Headquarters: United States
    • # of employees: 1.001-5.000
  • Mobvoi: AI company that focuses on speech recognition, natural language processing, and vertical mobile search. They also have a strategic partnership with Google.
    • Funding: $252.8M
    • Headquarters: United States
    • # of employees: 501-1.000
  • C3: AI software company for building enterprise-scale AI applications for digital transformation.
    • Funding: $228.5M
    • Headquarters: United States
    • # of employees: 201-500

 $100 Million > Total funding

  • Orion Labs: Developing voice-activated communication and automation solutions for deskless workers.
    • Funding: $63M
    • Headquarters: United States
    • # of employees:51-200
  • Hive: A full-stack AI company specializing in computer vision and deep learning.
    • Funding: $20.2M
    • Headquarters: United States
    • # of employees: 51-200
  • Hypatos: A process automation startup that applies language processing AI and computer vision tech to speed up financial document processing
    • Funding: $10M
    • Headquarters: Germany
    • # of employees: 11-50

Breakdown by technology

types of artificial intelligence
Source: Medium

Machine Learning

Enables companies to build and deploy ML models. These models could be in any AI domain such as NLP, machine vision, etc.

Machine learning vendors

  • H2O.io: An open-source machine learning platform that enables AI applications via services in cloud and on-premises.
    • Funding: $151.1M
    • Headquarters: United States
    • # of employees: 201-500
  • Prevision.io: Providing an automated machine learning platform to generate and deploy highly accurate predictive models on the cloud or on-premises.
    • Funding: €7.5M
    • Headquarters: France
    • # of employees: 11-50
  • Tazi.ai: TAZI’s AutoML platform enables businesses to easily create, update, deploy, and take actions with ML where models are understandable and learn continuously from data and humans.
    • Funding: €1M
    • Headquarters: United States
    • # of employees: 11-50

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Natural Language Processing (NLP)

Natural language processing is the core technology behind chatbots. NLP is a subcategory of AI that helps break down, understand, process, and determine the required action based on queries. NLP is the engine that performs tasks such as dialog control and task prediction. Since interest in chatbots is increasing and the market is expected to be $1+ billion by 2025, companies that provide NLP technology are in demand.

Natural Language Processing Vendors

  • SoundHound: The company provides voice-enabled AI and conversational intelligence technologies through a music discovery app and voice assistant.
    • Funding: $215M
    • Headquarters: United States
    • # of employees: 201-500
  • Grammarly: A digital writing assistant helps people write without errors.
    • Funding: $200M
    • Headquarters: United States
    • # of employees: 201-500
  • MindMeld: Their conversational AI platform enables companies to build intelligent conversational interfaces for any application or device.
    • Funding: $15.4M
    • Headquarters: United States
    • # of employees: 11-50

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Machine Vision

Machine vision is at the core of technology behind industrial automation. The decrease in cost of cameras and advancement in image recognition technology resulted in more accurate and cheaper machine vision systems. Therefore, industrial companies aim to achieve increased automation and efficiency through machine vision systems.

Machine Vision Vendors

  • Prophesee: Providing computer vision solutions for autonomous navigation and connected objects where sensors and algorithms mimic how the human eye and brain work to improve efficiency.
    • Funding: $65M
    • Headquarters: France
    • # of employees: 51-200
  • RADAR: An RFID and computer vision platform that automates inventory management, analytics, and checkout in physical stores.
    • Funding: $16M
    • Headquarters: United States
    • # of employees: 11-50
  • IVISYS: Developing advanced machine vision inspection systems that provide solutions for quality inspection, verification, and machine guidance.
    • Funding: Info not available
    • Headquarters: Sweden
    • # of employees: 11-50

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Autonomous Things

Autonomous things include robotics, vehicles,  drones, autonomous smart home devices, and autonomous software. Self-driving cars are getting the most attention among these technologies. However, there is still time before we see them on most roads due to technical and regulatory challenges.

Autonomous things vendors

  • Peloton: Connected and autonomous truck company that supports drivers’ health and safety while minimizing the heavy dependence of logistics companies on drivers
    • Funding: $78.4M
    • Headquarter: United States
    • # of employees: 51-200
  • DJI Innovations: Developing innovative drone and camera technology for commercial and recreational use.
    • Funding: $105M
    • Headquarter: China
    • # of employees: 10.001+
  • Sunflower Labs: Combining outdoor sensors with autonomous aerial drones for a complete view of home security
    • Funding: Info not available
    • Headquarter: Sweden
    • # of employees: 11-50

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Analytics

AI helps analytics get automated, more accessible, and more accurate. Thanks to AI and ML algorithms, organizations’ analytics methods are better in prediction, pattern recognition, and classification.

Analytics Vendors

  • RapidMiner: A software platform for data science teams that unites data prep, machine learning, and predictive model deployment.
    • Funding: $36M
    • Headquarters: United States
    • # of employees: 51-200
  • Alteryx: Data science and self-service analytics platform can prep, blend, enrich, and analyze data, manage, and deploy predictive analytics solutions.
    • Funding: $163M
    • Headquarters: United States
    • # of employees: 1.001-5.000
  • Saama: AI-powered clinical analytics cloud platform company that delivers actionable business insights for life sciences.
    • Funding: $75.8M
    • Headquarters: United States
    • # of employees: 1.001-5.000

For more on AI-powered analytics:

Task Mining

Task mining technologies enable businesses to collect and monitor user interaction data to understand how they perform the tasks. Most task mining solutions are integrated with process mining technologies. These enable organizations to understand processes and find ways to enhance the whole process rather than just improve how employees perform specific tasks.

Task Mining Vendors

  • FortressIQ: They claim that their platform can automatically discover, map, and document all the digital processes executed by an organization’s workforce thanks to AI.
    • Funding: $46M
    • Headquarters: United States
    • # of employees: 11-50

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Automation

AI-powered systems can automate various business processes with the help of RPA technology. Some automation examples are

  • accounts payable (AP) automation,
  • invoice automation,
  • document automation,
  • sales & marketing automation

AI-powered automation vendors

  • Automation Anywhere: An AI-powered digital workforce platform that democratizes automation and liberates people from mundane and repetitive tasks.
    • Funding: $840M
    • Headquarters: United States
    • # of employees: 1.001-5.000
  • Workfusion: Automating enterprise business processes by combining robotics, AI-powered cognitive automation, and workforce orchestration.
    • Funding: $121.3M
    • Headquarters: United States
    • # of employees: 201-500

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Breakdown by industry

Healthcare

The AI healthcare market is expected to be $6.6 billion by 2021. The most prominent applications of AI companies in the healthcare industry are early diagnosis, drug discovery, and better treatment along with data-driven administration by analyzing and interpreting the available patient and company data more precisely.

Healthcare AI vendors

  • Atomwise: A startup using AI to accelerate drug discovery.
    • Funding: $176.6M
    • Headquarters: United States
    • # of employees: 51-200
  • Owkin: Deploying AI and federated learning for medical research.
    • Funding: $74.1M
    • Headquarters: United States
    • # of employees: 51-200
  • Zebra Medical Vision: Imaging Analytics Platform allows healthcare institutions to analyze clinical imaging data in real-time and detect medical indications.
    • Funding: $74.1M
    • Headquarters: United States
    • # of employees: 51-200

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Insurance

The insurance industry heavily relies on documents and repetitive processes. AI and Insurtech companies deliver automation in back-office tasks while improving customer service (via chatbots) and enabling fraud detection (via predictive analytics).

Insurance AI vendors

  •  Lemonade: A licensed insurance carrier that offers renters, homeowners, and pet health insurance in the United States and contents and liability insurance in Germany and the Netherlands.
    • Funding: $480M
    • Headquarters: United States
    • # of employees: 201-500
  • Tractable: The insurtech startup that develops artificial intelligence for accident and disaster recovery.
    • Funding: $59.9M
    • Headquarters: United States
    • # of employees: 201-500
  • Zesty.ai: An AI-powered property analytics and risk platform for insurance.
    • Funding: $13M
    • Headquarters: United Kingdom
    • # of employees: 51-200

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Retail

AI products & services can provide retailers various capabilities such as

  • Customer Intelligence is where businesses leverage customer data to deliver better and more personalized products & services.
  • Autonomous stores to serve customers faster.
  • Autonomous warehouses to improve the efficiency of supply chain processes.

AI Retail Vendors

  • AiFi: Specialized in developing store automation systems with a combination of AI, edge computing, and scalable sensor fusion technology.
    • Funding: $29.5M
    • Headquarters: United States
    • # of employees: 51-200
  • Heuritech: Specialized in developing store automation systems with a combination of AI, edge computing, and scalable sensor fusion technology.
    • Funding: €5.2M
    • Headquarters: France
    • # of employees: 51-200
  • Osara: Osara is an artificial intelligence company that provides warehouse automation technology through machine learning solutions.
    • Funding: $29.3M
    • Headquarters: United States
    • # of employees: 51-200

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Manufacturing

Most popular AI use cases in manufacturing focus on improving maintenance and quality. Manufacturing includes the orchestration of processes and full of analytical data that suits AI/ ML algorithms; therefore, manufacturers can generate value through AI adoption.

AI Manufacturing Vendors

  • Data Prophet: Its AI solution suite improves quality and yield in manufacturing
    • Funding: $6M
    • Headquarters: South Africa
    • # of employees: 51-200
  • NavVis: The company helps manufacturers drive efficiencies in global factory planning and operations with a digital twin solution that enables fast and accurate 3D mapping and 3D visualization of the shop floors,
    • Funding: $68.2M
    • Headquarters: Germany
    • # of employees: 51-200
  • Noodle.AI: Noodle AI provides AI-powered analytics to minimize waste in manufacturing and supply chain operations.
    • Funding: $72M
    • Headquarters: United States
    • # of employees: 51-200

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Logistics

Capabilities AI technology offers to logistics companies are:

  • Supply & Demand Planning
  • Backoffice & Warehouse Automation
  • Autonomous transportation
  • Logistics optimization through analytics

AI Logistics Vendors

  • Scale AI: An investment company that funds AI initiatives for supply chain companies.
    • Funding: CA$23.4M
    • Headquarters: Canada
    • # of employees: 11-50
  • Aquify: Company focuses on scalable 3D computer vision solutions based on commodity hardware for accelerating and improving the accuracy of the manual processes gating logistics and manufacturing throughput.
    • Funding: $36.8M
    • Headquarters: United States
    • # of employees: 11-50
  • LogiNext: An SaaS company for field service and logistics optimization. LogiNext uses data analytics and machine learning algorithms to optimize movements across the globe.
    • Funding: $49.6M
    • Headquarters: United States
    • # of employees: 51-200

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Telecom

In the telecommunication industry, AI projects focus on the following technologies:

  • Network optimization
  • Virtual Assistants
  • Robotic process automation (RPA)

AI Telecom Vendors

  • Metawave: A wireless technology company that builds intelligent and high-performance automotive radars by leveraging metamaterials and AI.
    • Funding: $49.6M
    • Headquarters: United States
    • # of employees: 11-50
  • DeepSig:  Using ML and AI to learn optimized models directly from data so that communication systems become faster, more cost efficient, more secure, and able to excel in complex environments.
    • Funding: $7.7M
    • Headquarters: United States
    • # of employees: 11-50

Banking

AI helps banks and other financial institutions reduce costs and errors with improved banking processes while ensuring data security and compliance. McKinsey estimated that AI can generate more than $250 billion in value for financial institutions.

AI Banking Vendors

  • Avant: An online lending platform that offers alternatives to its clients by relying upon big data and machine-learning algorithms.
    • Funding: $1.6B
    • Headquarters: United States
    • # of employees: 501-1.000
  • OakNorth: A credit science platform that leverages machine learning to model a view of a borrower’s financial situation.
    • Funding: $1B
    • Headquarters: United Kingdom
    • # of employees: 501-1.000
  • ComplyAdvantage: Providing AI-driven financial crime risk data and detection technology for financial institutions.
    • Funding: $88.2M
    • Headquarters: United Kingdom
    • # of employees: 201-500

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Breakdown by business function/department they serve

Sales

Most important challenge of sales reps is spending a significant time on unqualified leads due to a lack of lead prioritization and manual processes in lead generation. AI technologies can target these obstacles with its analytics and automation capabilities.

AI Sales Vendors

  • SalesDirector.ai: Providing AI based sales coaching and forecasting for enterprise sales teams
    • Funding: Not available
    • Headquarters: United States
    • # of employees: 11-50
  • Zilliant: The company offers price optimization and management software for manufacturing, distribution, high-tech, and industrial service companies.
    • Funding: $92.4M
    • Headquarters: United States
    • # of employees: 51-200
  • People.ai: Using AI to transforms business activity data into recommendations that increase the impact of Sales, Marketing, and Operations.
    • Funding: $100M
    • Headquarters: United States
    • # of employees: 51-200

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Marketing

There are numerous AI products you can purchase to enhance different marketing strategies such as SEO, content marketing, and account based marketing (ABM). Products like recommendation engines or website personalization solutions help businesses improve conversations while AI-powered analytics is enabling better customer targeting.

AI Marketing Vendors

  • MarketMuse: Using AI to accelerate content planning, creation, and optimization. Some examples are identifying content quality issues on the site and building blueprints that show how to write to cover a topic comprehensively.
    • Funding: $6.7M
    • Headquarters: United States
    • # of employees: 11-50
  • Writer: An AI writing assistant
    • Funding: $5M
    • Headquarters: United States
    • # of employees: 11-50
  • Seamless.AI: A sales automation software that organizes contacts and makes them universally accessible and useful.
    • Funding: $300K
    • Headquarters: United States
    • # of employees: 51-200

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Customer Service

AI can help customer service team enable communication with customers through chatbots while performing analytics on customer responses to enhance call experience.

AI Customer Service Vendors

  • Gong.io: A Revenue Intelligence Platform that captures and understands every customer interaction then delivers insights to empower revenue teams for data driven decisions.
    • Funding: $333M
    • Headquarters: United States
    • # of employees: 201-500
  • Observe.AI: A software company that leverages AI, machine learning, and analytics to develop contact center software. The company helps businesses analyze all calls and streamline quality assurance workflows.
    • Funding: $88.1M
    • Headquarters: United States
    • # of employees: 51-200
  • Directly: The company offers AI-powered solutions to help resolve customer issues with a mix of automation and human support.
    • Funding: $66.8M
    • Headquarters: United States
    • # of employees: 51-200

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Human Resources (HR)

AI can facilitate recruiting and saves time for recruiters by automating processes such as candidate identification & outreach, resume screening & interview analysis.

AI vendors for HR department

  • XOR.ai: Developing technologies for human resource and talent acquisition workflow automation.
    • Funding: $8.4M
    • Headquarters: United States
    • # of employees: 51-200
  • Ideal: The company uses AI to centralize rich candidate data and screen candidates so that recruiting teams make more accurate, fair, and efficient talent decisions.
    • Funding: $3M
    • Headquarters: Canada
    • # of employees: 11-50

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Security

Artificial intelligence’s influence on security systems depends on where you look.

  • AI helps enhance security systems.
  • AI creates new vulnerable points that businesses need to secure.
  • Cyberattackers may use AI for malicious actions.

Regardless of perspective, businesses should rely on AI to secure themselves from cyberattacks since average cost of a data breach is expected to surpass $150 million in 2020.

AI Security Vendors

  • Palo Alto Networks: Addressing the security challenges with continuous innovation that seizes the latest breakthroughs in artificial intelligence, analytics, automation, and orchestration.
    • Funding: $65M
    • Headquarters: United States
    • # of employees: 5.001-10.000
  • LogRhythm: Delivering security analytics; user and entity behavior analytics (UEBA); network detection and response (NDR); and security orchestration, automation, and response (SOAR) within a single, integrated platform for rapid detection, response, and neutralization of threats.
    • Funding: $126.3M
    • Headquarters: United States
    • # of employees: 501-1.000
  • Absolute Software: Creating endpoint resiliency solutions that enable organizations to secure their devices, data, and users.
    • Funding: Publicly traded company on Toronto Stock exchange
    • Headquarters: United States
    • # of employees: 201-500

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Breakdown by geography

According to a study from 2018, the top 5 countries by number of AI startups are

  1. United States: 1394 startups
  2. China: 383 startups
  3. Israel: 362 startups
  4. United Kingdom: 245 startups
  5. Canada: 131 startups

And San Francisco is the leading region that has the highest number of  AI startups with 596 startups. Yet, the interesting fact is around one-third of startups have Chinese founders/co-founders.

Breakdown by business model

Like tech companies, AI companies can also be classified by the size of the businesses they target:

  • Consumers (B2C)
  • B2B
    • SMEs
    • Mid-market (Companies with hundreds of millions in revenue)
    • Enterprise (Forbes 2000 or at least $1 billion in revenue)

Though most AI startups, specifically in industries such as insurance, retail, healthcare, and banking, focus on enhancing customer experience through the guidance of data and analytics, they promote their products for businesses rather than consumers. In other words, most AI companies are B2B-focused. According to Asgard’s research, which is a venture fund for AI companies, 64% of AI companies are B2B. However, their calculation methodology doesn’t look 100% accurate since there are numerous B2B companies such as OJO Labs (in real estate) and Personetics Technologies (in Fintech) where the research below included them in the B2C environment. Therefore, we assume the ratio of B2B AI startups is higher than 64% of the AI ecosystem.

Number of B2B AI companies vs B2C AI companies
Source: Asgard

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Breakdown by service

Product offerings

Hardware

AI chips are specially designed accelerators for artificial neural network(ANN) based applications. ANN is considered a subfield of artificial intelligence and most commercial ANN applications are deep learning applications.

AI Chip Vendors

  • Graphcore: A semiconductor company that develops accelerators for AI and machine learning.
    • Funding: $460M
    • Headquarters: United States
    • # of employees: 51-200
  • Wave Computing: A company that is revolutionizing AI with its dataflow-based chips, systems and software that deliver orders of magnitude performance improvements over legacy architectures.
    • Funding: $203.3M
    • Headquarters: United States
    • # of employees: 51-200

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Software

Most AI products you encounter in the business world are SaaS products where vendors share APIs or deliver a product via an app or web portal.

Service offerings

Some vendors offer specific services based on your business needs. AI services businesses may purchase include

  • AI-as-a-Service (AIaaS)
  • Custom AI Development
  • Services for enabling AI transformation
    • Consulting
  • Services to support your internal data science teams

If your business needs are niche, you need to build custom AI solutions. For this reason, you may want to check our custom AI development whitepaper where we explained every aspect of vendors that you may encounter within the AI landscape.

Download our Whitepaper on Custom AI Solutions

Recommended readings:

You can also check out our list of AI tools and services:

If you still have questions on AI vendors, don’t hesitate to contact us:

Find the Right Vendors

Sources:

*Data related to businesses’ funding is taken from Crunchbase

**Data related to businesses’ number of employees is taken from Linkedin

Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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