GeoTMT

GeoTMT

Operates as an advertising data technology company.

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DateInvestorsAmountRound
investor investor

€0.0

round
investor

€0.0

round

N/A

Series C
Total Funding000k
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Founded in August 2012, Beijing GeoTMT Co., Ltd. operates as a third-party data integrator and scenario-based application platform. The company is headquartered in Beijing, with Cui Xianzhen serving as the legal representative and major shareholder. GeoTMT focuses on leveraging big data to provide clients with intelligent risk control, anti-fraud services, credit assessment, and strategic analysis.

The firm's core offerings are centered around its Artificial Intelligence Modeling Platform, which utilizes active machine learning to combine expert risk control experience with AI computing power. This platform delivers solutions that include natural language processing, voice recognition, intelligent voice services, decision engines, and risk alerts. These tools are designed to help businesses, particularly in the financial, automotive, real estate, and tourism sectors, to enhance operational efficiency and reduce costs. The business model appears to be providing end-to-end solutions and services for enterprise clients, helping them manage credit cycles from analysis and monitoring to post-loan management.

GeoTMT has established itself as a high-tech enterprise within China's technology and services industry. The company has secured C-round financing and holds numerous patents, software copyrights, and other intellectual property. It primarily serves businesses by creating value through the deep mining of big data, offering solutions that cater to specific industry needs and operational scenarios. Keywords: big data, data integration, risk control, anti-fraud, credit assessment, artificial intelligence, machine learning, natural language processing, decision engine, financial technology, enterprise solutions, data analytics, scenario application, strategic analysis, business intelligence, predictive platform, voice recognition, knowledge graph, operational efficiency, AI modeling

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