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Founded Year



Series B | Alive

Total Raised


About Clustar

Clustar develops private computing technology to enhance the cluster communication. It offers privacy computing solutions, secure data network and integration solutions. The company was founded in 2018 and is based in Shenzhen, China.

Headquarters Location

1803, Block C, Dachong Business Center, Nanshan District

Shenzhen, Guangdong,



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Clustar's Products & Differentiators

    Clustar Software Platform for PPC

    It is an enterprise-level full-stack privacy preserving computation platform that is designed for enterprise users. The platform provides one-stop HW/SW solution from access of massive trusted and secured data source, data encryption and computing acceleration hardware, multi-source data fusion in privacy computing, authority management to auditing and persistent storage of data communication. It enables enterprises to overcome the challenges to adopting privacy preserving technology such as learning, deployment, management, and application and creates a safe space for the data interactions and the fusion of applications among multiple enterprises and departments.

Expert Collections containing Clustar

Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.

Clustar is included in 1 Expert Collection, including Artificial Intelligence.


Artificial Intelligence

10,393 items

This collection includes startups selling AI SaaS, using AI algorithms to develop their core products, and those developing hardware to support AI workloads.

Clustar Patents

Clustar has filed 3 patents.

The 3 most popular patent topics include:

  • Data security
  • Block ciphers
  • Cryptography
patents chart

Application Date

Grant Date


Related Topics




Data security, Data management, Data mining, Machine learning, Computer security


Application Date


Grant Date



Related Topics

Data security, Data management, Data mining, Machine learning, Computer security



Latest Clustar News

Federated Learning Distributed Training for AI Excellence with Shared Model

Jul 26, 2022

Federated Learning Distributed Training for AI Excellence with Shared Model Ansprechpartner:in Frau Karen Kulinski +49 1511 2667736 Federated Learning Distributed Training for AI Excellence with Shared Model ADLINK’s Edge Server implements edge federated learning, disrupting the traditional centralized ML training model and solving privacy issues for personal information for application to privacy-critical financial, medical, retail and Internet vertical ) ‎ ADLINK Technology, Inc. , a global leader in edge computing, has implemented edge federated learning application with the MECS-7211 as an edge computing server to resolve the privacy of personal information and for accelerated applications in intensive computing, such as privacy computing, machine learning, gene sequencing, financial business, medical, video processing and network security.‎ ‎With the rapid development of IoT and popularization of 5G networks, a large number of terminal devices are connected to the network and generating massive amounts of data. Traditional data computing and analysis are based on cloud computing. With the rapid increase in data quantities, the transmission from application terminals to cloud computing centers can cause delay and data leakage. Timely and effective processing of data becomes a major challenge for cloud computing centers. ‎‎A new computing model - edge computing – processes data at the network edge; providing intelligence services closer to the person or object requiring that data, and allowing network services to respond more efficiently and better meet the business needs of applications in IoT, Internet of Vehicles (IoV), industrial control, intelligent manufacturing and video processing.‎ ‎The introduction of edge computing technology has eased the network burden of cloud centers, but also raised security issues. Localization of data can easily hinder data interaction. In addition, data security and application specifications have been tightened in recent years. Topics such as GDPR data privacy and data protection have been given high priority.‎ ‎The centralized computation of data used in traditional machine learning algorithms cannot meet current and future data processing requirements and limits the development of artificial intelligence.‎ ‎In this context, federated machine learning provides the solution to edge computing security problems.‎ Federated learning is a machine learning framework that uses encrypted private data for operations by participants, exchanging only the parameters, weights, and gradients of the encrypted model, without moving the raw data out of the local area or moving the encrypted raw data set. Multiple agencies can model data usage and implement machine learning while allowing multiple organizations to conduct data usage and machine learning modeling under the requirements of user privacy protection, data security and government regulations.‎ Federated learning, as a distributed machine learning paradigm, ensures that data are not leaked and allows enterprises to use more data training models, carry out joint modeling, realize AI collaboration, and provide strong support for the implementation of privacy protection computing solutions.‎ Recently, ADLINK and Clustar jointly launched an integrated machine for edge federated learning. ‎Using ADLINK's MECS-7211 as an edge computing server and Clustar's FPGA isomeric acceleration card, the system performs qualitative analysis and hardware optimization of commonly used complex operators in federated learning to facilitate user acceleration of distributed dense state machine learning tasks. ‎Efficient storage, computing and data transmission systems play a collaborative optimization role in the efficient operation of isomeric systems. Compared with traditional CPU architectures, performance is improved by 7 times, and improved by 2 times with power consumption reduced by 40% over CPU+GPU platforms. ‎This integrated machine for edge federated learning is suitable or financial, medical, and data center applications that require extensive data analysis and focus on privacy, and has already been deployed in many instances. Julian Ye, Director of Network Communications and Public Sector of ADLINK, said, “ADLINK’s MECS series is a 5G-based edge computing platform. As one of the initiators of the Open Telecom IT Infrastructure (OTII) specification, MECS series products conform to OTII industry specifications, using isomeric architecture to flexibly support FPGA, GPU, and 5G acceleration cards and other expansion cards. ‎Compact size design coupled with an operating environment that supports a wide range of temperatures makes the MECS series suitable for distributed architecture applications and deployment at the edge and on the application side of the network. ‎ADLINK and Clustar jointly launched an integrated machine for edge federated learning to optimize computing systems collaboratively and expand the application of MECS series products. In the future, ADLINK will continue to cooperate with Clustar in the AI field to enrich application scenarios of edge computing.” ‎ADLINK is committed to edge computing and the AI industry, has more than two decades of R&D experience in telecommunications network computing; focuses on network security, 5G, edge computing, IoT and other infrastructure products and services; provides leading, hardened and reliable hardware and software solutions; and has become the driving force for artificial intelligence to change Pressemitteilung teilen:

Clustar Frequently Asked Questions (FAQ)

  • When was Clustar founded?

    Clustar was founded in 2018.

  • Where is Clustar's headquarters?

    Clustar's headquarters is located at 1803, Block C, Dachong Business Center, Nanshan District, Shenzhen.

  • What is Clustar's latest funding round?

    Clustar's latest funding round is Series B.

  • How much did Clustar raise?

    Clustar raised a total of $11M.

  • Who are the investors of Clustar?

    Investors of Clustar include Fengtouxia, Huatai Chuangxin, CMB International Capital, Co-Stone Venture Capital, Hong Kong Science and Technology Parks Corporation and 5 more.

  • Who are Clustar's competitors?

    Competitors of Clustar include Hua Kong Tsingjiao and 7 more.

  • What products does Clustar offer?

    Clustar's products include Clustar Software Platform for PPC and 2 more.

Compare Clustar to Competitors

Hua Kong Tsingjiao

Hua Kong Tsingjiao focuses on the research, development, and operation of big data security fusion technology and standards and computing analysis platform that are based on cryptography, game theory, and artificial intelligence. The company was founded in 2018 and is based in Beijing, China.

Impulse Online

Impulse Online is a distributed privacy computing network based on Blockchain. The company provides safe, private, credible, and intelligent data computing capabilities.

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Ant Group

Ant Group (SGX: 5VJ) is a technology company that offers financial services, serving small and micro enterprises and consumers. It is dedicated to building an open ecosystem of technologies while working with other financial institutions to support the future financial needs of society. The company's products include Alipay, a payment and lifestyle platform, Ant Fortune, a comprehensive wealth management app, and Zhima Credit, an independent, private, alternative credit service. It was founded in 2011 and is based in Hangzhou, China.

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Owkin specializes in AI technologies applied to clinical research with the aim of developing better drugs and treatments for patients. The company's purpose is to empower researchers in hospitals, universities and the biopharma industry to i) understand why drug efficacy varies from patient to patient, ii) improve the drug development process and iii) to help identify key drugs and treatments for each individual patient to improve patient outcomes. The company's precision medicine platform aims to enable medical insights for drug discovery and development by connecting life sciences firms with academic researchers and hospitals. The Owkin platform aims to enable partners to uncover siloed datasets while maintaining patient privacy and securing proprietary data using Federated Learning and innovative collaborative AI technology. The company was founded in 2016 and is based in New York, New York.


YeeZTech is positioned as a privacy protection solution provider for data cooperation, focusing on building an infrastructure for government and enterprise data cooperation, and committed to becoming a liquidity aggregation bridge for data assets.

Primitive Hub

Primitive Hub focuses on building an enterprise-level open source privacy computing platform. The company was founded in 2021 and is based in Beijing, China.

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