A New Phase for AI Data Infrastructure: Scaling and Quality Enhancement
On July 20, the four-day 2026 World Artificial Intelligence Conference and High-Level Meeting on Global AI Governance (WAIC 2026) came to a successful close in Shanghai. Looking across the forum topics, expert insights, and new product launches at this year's conference, one industry consensus has become increasingly clear: as the foundational capabilities of general-purpose large models converge, the competitive focus of the AI industry is shifting decisively from the "first half"—competing on computing power and parameters—to the "second half," centered on scaling and improving the quality of AI data infrastructure.Compared to computing power, high-quality datasets have become the scarcest factor of production. The depth and breadth of AI data infrastructure will directly determine the depth and ceiling of enterprise value realization from AI.

At this globally watched AI event, KeenData, as a leader in AI data infrastructure, made a strong appearance under the theme "Defining the Underlying Logic of AI, Reshaping Data Supply."Through a full showcase of its core products, validation through cross-industry benchmark practices, and a strategic partnership signing with an overseas partner, the company delivered a concentrated demonstration of its technological strength and global expansion strategy—providing solid support for the scaling and quality enhancement of AI data infrastructure.
KeenData Builds a Solid AI Data Foundation with Systematic Capabilities
Currently, the difficulty of scaling AI projects often stems from data-related challenges. KeenData presented its KeenData Lakehouse data intelligence platform in full.The platform adopts an AI-in-Lakehouse intelligent architecture that natively integrates a lakehouse engine, multimodal computing engine, and training-inference acceleration engine. It not only fully adapts to mainstream domestic and international computing power and diverse algorithm ecosystems but also enables large organizations to transition from data-driven to intelligence-driven operations.


With a core code self-development rate of 97% and over 200 technology patents, KeenData Lakehouse holds the top market share in the advanced technology lakehouse data platform segment and has ranked among the top five in China's big data platform private deployment market for three consecutive years.
At the same time, KeenData showcased large-scale implementation practices across energy, healthcare, government, manufacturing, and other key sectors, visually demonstrating the core industrial value of AI data infrastructure in empowering the digital transformation of thousands of industries and providing replicable and adaptable implementation models for various sectors.
Global Expansion: Technology Going Global to Build a New AI Ecosystem
While strengthening its domestic AI data foundation, KeenData also took a critical step forward in its globalization strategy during the exhibition. On the morning of July 18, KeenData formally signed a strategic partnership agreement with Impact Business Solutions, a leading Malaysian digital service provider, officially initiating a deep expansion into the Malaysian and broader ASEAN markets. This move signals that KeenData is accelerating the paradigm shift in AI data infrastructure through its independent, controllable technological capabilities and a global vision.

Building the Foundation, Empowering AI Value Realization
Throughout the four-day exhibition, the KeenData booth received a steady stream of visitors, including government officials, enterprise clients, and overseas business representatives, engaging in discussions on new pathways for AI-powered data enablement.




Though WAIC 2026 has drawn to a close, a new wave of AI data infrastructure development is just beginning. For enterprises and the broader industrial ecosystem, data infrastructure is not only the foundation of AI but also the critical engine that enables AI to create tangible value. Moving forward, KeenData will continue to be driven by technological innovation, steadily deepening its presence in the AI data infrastructure space and strengthening the supporting capabilities for large-scale AI industrial deployment—helping enterprises overcome application challenges and comprehensively drive the leap and upgrade of industrial intelligence.
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