About us
About Us
About us
About Us
About us
About Us
开启具身智能数据分析
的新纪元
开启具身智能数据分析
的新纪元
刻⾏时空成⽴于 2022 年 5 ⽉，是⼀家专注于⼈⼯智能数据全流程平台的企业。公司由苹果、⾕歌、亚⻢逊等知名科技公司的核⼼成员组成，并已获得数百万美元的天使投资。其主要领域包括机器⼈和⾃动驾驶，重点关注⾼效运维和可靠功能测试，以提⾼⼯作效率和用户满意度。
创始⼈在机器⼈数据平台领域有丰富经验，公司已与多家机器⼈和⾃动驾驶领域的公司签约并运营。
刻行时空数据平台的测试和仿真功能对于满⾜这些领域的需求⾄关重要，为创新和技术发展提供了⽀持。
Our team is highly experienced.
We are a team focused on automated systems, with members from top industry-leading companies.
Our team has extensive experience in developing machine platforms.
Yangming Huang
CEO
Yangming, a leader in the technology industry, has rich experience in serving as the head of automatic systems in multiple top robot technology companies, and currently holds the position of CEO of Kexing.
Yujing Zheng
CTO
Yujing, an outstanding talent in the field of technology research and development with a strong technical background, has previously served as a research and development director at multiple leading robotics companies and is currently the CTO of coScene.
Yangming Huang
CEO
Yangming, a leader in the technology industry, has extensive experience serving as the head of automated systems at several top robotics technology companies and is currently the CEO of coScene.
Yujing Zheng
CTO
Yujing, an outstanding talent in the field of technology research and development with a strong technical background, has previously served as a research and development director at multiple leading robotics companies and is currently the CTO of coScene.
Our team is highly experienced.
We are a team focused on automated systems, with members from top industry-leading companies.
Our team has extensive experience in developing machine platforms.
Yangming Huang
CEO
Yangming, a leader in the technology industry, has rich experience in serving as the head of automatic systems in multiple top robot technology companies, and currently holds the position of CEO of Kexing.
Yujing Zheng
CTO
Yujing, an outstanding talent in the field of technology research and development with a strong technical background, has previously served as a research and development director at multiple leading robotics companies and is currently the CTO of coScene.
Yangming Huang
CEO
Yangming, a leader in the technology industry, has extensive experience serving as the head of automated systems at several top robotics technology companies and is currently the CEO of coScene.
Yujing Zheng
CTO
Yujing, an outstanding talent in the field of technology research and development with a strong technical background, has previously served as a research and development director at multiple leading robotics companies and is currently the CTO of coScene.
Frequently Asked Questions
What aspects does the data closed loop include?
coScene proposes the concept of spatiotemporal data containerization and has independently developed three major engines: the Data Container Engine, Workflow Engine, and Semantic Search Engine. These engines greatly enhance the capabilities of accessing, querying, governing, and scheduling data computation for unstructured data, becoming the cornerstone of various data applications. Currently, the company has implemented four major functional modules: the Control Console, Data Platform, Visualization Player, and Testing Platform, providing users with a service loop for the research and development process.
How can coScene empower enterprises?
With the rapid development of artificial intelligence, the demand for training data is constantly increasing. The AI industry is transitioning from single structured data to multi-modal and spatiotemporal data. Additionally, the robotics industry is also experiencing rapid growth. However, the rapid development of robots can easily lead to high-cost traps. coScene will realize enterprise data-driven operations, bringing a 700% increase in productivity, and ultimately become the core competitive advantage of robotics companies.
What are the application scenarios of coScene?
The application scenarios for coScene are extremely diverse, including but not limited to: smart home, industrial assembly, cafe management, and warehouse logistics.
How can I use the coScene platform?
Currently, coScene supports multiple interaction methods, including web platforms and various integrated features, allowing you to easily deploy and use it.
What is the development history of coScene?
2022: In May, coScene was established and received tens of millions of angel round financing in August. In October, we developed a multimodal data engine, provided diagnostic and collaborative capabilities, and successfully delivered the MVP, signing a seed customer agreement. 2023: In February, we joined AliCloud Computing Nest and signed cooperation agreements with Shanghai Software Center and others. In August, we successfully delivered a complete testing platform, and the cluster management experience completed the first-stage closed loop. We gained recognition from more than three top-tier paid robot head enterprises, including GAUSSIAN, KEENON and EVOLUTION. In November, we visited Figure.ai and began technical requirement docking. In December, we signed with Supor, officially entering the field of smart home appliances. 2024: In January, we integrated annotation platforms, simulation platforms, and other ecosystems, and signed with AGIBOT. In June, we vigorously promoted the research and development closed loop of physical robots, and cooperated with SHANGHAI ROBOT INDUSTRIAL TECHNOLOGY RESEARCH CENTER, Shanghai's top three universities, and launched data standardization services. We also began to expand into overseas markets. In September, we developed annotation integration and semantic search engines, completed PMF, and carried out extensive cooperation and integration. We also provided a marketplace and established an ecosystem.
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Unlock the potential of data, feel the power of cloud computing
Ready to use out of the box
Get started now
Unlock the potential of data, feel the power of cloud computing
Ready to use out of the box
Start Now
Unlock the potential of data and feel the power of cloud computing
Ready to use out of the box
Start Now
Unlock the potential of data and feel the power of cloud computing
Ready to use out of the box
Frequently Asked Questions
What aspects does the data closed loop include?
coScene proposes the concept of spatiotemporal data containerization and has independently developed three major engines: the Data Container Engine, Workflow Engine, and Semantic Search Engine. These engines greatly enhance the capabilities of accessing, querying, governing, and scheduling data computation for unstructured data, becoming the cornerstone of various data applications. Currently, the company has implemented four major functional modules: the Control Console, Data Platform, Visualization Player, and Testing Platform, providing users with a service loop for the research and development process.
What aspects does the data closed loop include?
coScene proposes the concept of spatiotemporal data containerization and has independently developed three major engines: the Data Container Engine, Workflow Engine, and Semantic Search Engine. These engines greatly enhance the capabilities of accessing, querying, governing, and scheduling data computation for unstructured data, becoming the cornerstone of various data applications. Currently, the company has implemented four major functional modules: the Control Console, Data Platform, Visualization Player, and Testing Platform, providing users with a service loop for the research and development process.
How can coScene empower enterprises?
With the rapid development of artificial intelligence, the demand for training data is constantly increasing. The AI industry is transitioning from single structured data to multi-modal and spatiotemporal data. Additionally, the robotics industry is also experiencing rapid growth. However, the rapid development of robots can easily lead to high-cost traps. coScene will realize enterprise data-driven operations, bringing a 700% increase in productivity, and ultimately become the core competitive advantage of robotics companies.
How can coScene empower enterprises?
With the rapid development of artificial intelligence, the demand for training data is constantly increasing. The AI industry is transitioning from single structured data to multi-modal and spatiotemporal data. Additionally, the robotics industry is also experiencing rapid growth. However, the rapid development of robots can easily lead to high-cost traps. coScene will realize enterprise data-driven operations, bringing a 700% increase in productivity, and ultimately become the core competitive advantage of robotics companies.
What are the application scenarios of coScene?
The application scenarios for coScene are extremely diverse, including but not limited to: smart home, industrial assembly, cafe management, and warehouse logistics.
What are the application scenarios of coScene?
The application scenarios for coScene are extremely diverse, including but not limited to: smart home, industrial assembly, cafe management, and warehouse logistics.
How can I use the coScene platform?
Currently, coScene supports multiple interaction methods, including web platforms and various integrated features, allowing you to easily deploy and use it.
How can I use the coScene platform?
Currently, coScene supports multiple interaction methods, including web platforms and various integrated features, allowing you to easily deploy and use it.
What is the development history of coScene?
2022: In May, coScene was established and received tens of millions of angel round financing in August. In October, we developed a multimodal data engine, provided diagnostic and collaborative capabilities, and successfully delivered the MVP, signing a seed customer agreement. 2023: In February, we joined AliCloud Computing Nest and signed cooperation agreements with Shanghai Software Center and others. In August, we successfully delivered a complete testing platform, and the cluster management experience completed the first-stage closed loop. We gained recognition from more than three top-tier paid robot head enterprises, including GAUSSIAN, KEENON and EVOLUTION. In November, we visited Figure.ai and began technical requirement docking. In December, we signed with Supor, officially entering the field of smart home appliances. 2024: In January, we integrated annotation platforms, simulation platforms, and other ecosystems, and signed with AGIBOT. In June, we vigorously promoted the research and development closed loop of physical robots, and cooperated with SHANGHAI ROBOT INDUSTRIAL TECHNOLOGY RESEARCH CENTER, Shanghai's top three universities, and launched data standardization services. We also began to expand into overseas markets. In September, we developed annotation integration and semantic search engines, completed PMF, and carried out extensive cooperation and integration. We also provided a marketplace and established an ecosystem.
What is the development history of coScene?
2022: In May, coScene was established and received tens of millions of angel round financing in August. In October, we developed a multimodal data engine, provided diagnostic and collaborative capabilities, and successfully delivered the MVP, signing a seed customer agreement. 2023: In February, we joined AliCloud Computing Nest and signed cooperation agreements with Shanghai Software Center and others. In August, we successfully delivered a complete testing platform, and the cluster management experience completed the first-stage closed loop. We gained recognition from more than three top-tier paid robot head enterprises, including GAUSSIAN, KEENON and EVOLUTION. In November, we visited Figure.ai and began technical requirement docking. In December, we signed with Supor, officially entering the field of smart home appliances. 2024: In January, we integrated annotation platforms, simulation platforms, and other ecosystems, and signed with AGIBOT. In June, we vigorously promoted the research and development closed loop of physical robots, and cooperated with SHANGHAI ROBOT INDUSTRIAL TECHNOLOGY RESEARCH CENTER, Shanghai's top three universities, and launched data standardization services. We also began to expand into overseas markets. In September, we developed annotation integration and semantic search engines, completed PMF, and carried out extensive cooperation and integration. We also provided a marketplace and established an ecosystem.
Frequently Asked Questions
What aspects does the data closed loop include?
coScene has proposed the concept of spatiotemporal data containerization and independently developed three major engines: the Data Container Engine, Workflow Engine, and Semantic Search Engine. These three engines greatly enhance the capabilities of accessing, querying, governing, and scheduling data computation for unstructured data, becoming the cornerstone of various data applications. Currently, the company has implemented four major functional modules: the Control Console, Data Platform, Visualization Player, and Testing Platform, providing users with a service loop for the research and development process.
What aspects does the data closed loop include?
coScene has proposed the concept of spatiotemporal data containerization and independently developed three major engines: the Data Container Engine, Workflow Engine, and Semantic Search Engine. These three engines greatly enhance the capabilities of accessing, querying, governing, and scheduling data computation for unstructured data, becoming the cornerstone of various data applications. Currently, the company has implemented four major functional modules: the Control Console, Data Platform, Visualization Player, and Testing Platform, providing users with a service loop for the research and development process.
How can coScene empower enterprises?
With the rapid advancement of artificial intelligence, the demand for training data is continuously increasing. The AI industry is transitioning from single structured data towards multi-modal and spatiotemporal data. Additionally, the robotics industry is experiencing rapid growth. However, the rapid development of robots can easily lead to high-cost traps. coScene will realize enterprise data-driven operations, bringing a 700% increase in workforce efficiency, and ultimately become the core competitive advantage of robotics companies.
How can coScene empower enterprises?
With the rapid advancement of artificial intelligence, the demand for training data is continuously increasing. The AI industry is transitioning from single structured data towards multi-modal and spatiotemporal data. Additionally, the robotics industry is experiencing rapid growth. However, the rapid development of robots can easily lead to high-cost traps. coScene will realize enterprise data-driven operations, bringing a 700% increase in workforce efficiency, and ultimately become the core competitive advantage of robotics companies.
What are the application scenarios of coScene?
The application scenarios for coScene are extremely diverse, including but not limited to: smart home, industrial assembly, cafe management, and warehouse logistics.
What are the application scenarios of coScene?
The application scenarios for coScene are extremely diverse, including but not limited to: smart home, industrial assembly, cafe management, and warehouse logistics.
How can I use the coScene platform?
Currently, coScene supports multiple interaction methods, including web platforms and various integrated features, allowing you to easily deploy and use it.
How can I use the coScene platform?
Currently, coScene supports multiple interaction methods, including web platforms and various integrated features, allowing you to easily deploy and use it.
What is the development history of coScene?
2022: In May, coScene was established and received tens of millions of angel round financing in August. In October, we developed a multimodal data engine, provided diagnostic and collaborative capabilities, and successfully delivered the MVP, signing a seed customer agreement. 2023: In February, we joined AliCloud Computing Nest and signed cooperation agreements with Shanghai Software Center and others. In August, we successfully delivered a complete testing platform, and the cluster management experience completed the first-stage closed loop. We gained recognition from more than three top-tier paid robot head enterprises, including GAUSSIAN, KEENON and EVOLUTION. In November, we visited Figure.ai and began technical requirement docking. In December, we signed with Supor, officially entering the field of smart home appliances. 2024: In January, we integrated annotation platforms, simulation platforms, and other ecosystems, and signed with AGIBOT. In June, we vigorously promoted the research and development closed loop of physical robots, and cooperated with SHANGHAI ROBOT INDUSTRIAL TECHNOLOGY RESEARCH CENTER, Shanghai's top three universities, and launched data standardization services. We also began to expand into overseas markets. In September, we developed annotation integration and semantic search engines, completed PMF, and carried out extensive cooperation and integration. We also provided a marketplace and established an ecosystem.
What is the development history of coScene?
2022: In May, coScene was established and received tens of millions of angel round financing in August. In October, we developed a multimodal data engine, provided diagnostic and collaborative capabilities, and successfully delivered the MVP, signing a seed customer agreement. 2023: In February, we joined AliCloud Computing Nest and signed cooperation agreements with Shanghai Software Center and others. In August, we successfully delivered a complete testing platform, and the cluster management experience completed the first-stage closed loop. We gained recognition from more than three top-tier paid robot head enterprises, including GAUSSIAN, KEENON and EVOLUTION. In November, we visited Figure.ai and began technical requirement docking. In December, we signed with Supor, officially entering the field of smart home appliances. 2024: In January, we integrated annotation platforms, simulation platforms, and other ecosystems, and signed with AGIBOT. In June, we vigorously promoted the research and development closed loop of physical robots, and cooperated with SHANGHAI ROBOT INDUSTRIAL TECHNOLOGY RESEARCH CENTER, Shanghai's top three universities, and launched data standardization services. We also began to expand into overseas markets. In September, we developed annotation integration and semantic search engines, completed PMF, and carried out extensive cooperation and integration. We also provided a marketplace and established an ecosystem.
