From August 27 to 30, the 2026 China International Big Data Industry Expo was held in Guiyang. Under the theme "Token — A New Path to Unlocking the Value of Data Elements," this year's Expo brought together cutting-edge technologies and innovative achievements from across the industry. During the Expo, KeenData was invited to participate in the AI + Trusted Data Space Development Exchange, engaging in discussions with representatives from local data groups and big data trading centers on the path to trusted data space implementation. The company's case was recognized as a 2026 AI + Trusted Data Space Development Practice Achievement, showcasing the innovative practices of AI data infrastructure in supporting trusted data space construction and unlocking the value of data elements.
Building Trusted Data Spaces Requires New AI Data Infrastructure
As trusted data space development enters a critical phase of large-scale implementation across the country, AI technologies have opened new pathways while also exposing numerous bottlenecks. How to build AI-powered trusted data spaces and unlock the full chain of data element value creation has become a shared challenge for the industry. On the afternoon of August 29, during the roundtable session of the AI + Trusted Data Space Development Exchange, Zhu Jianyong, Vice President of KeenData, participated as a representative of technology service providers, engaging in in-depth discussions with industry peers on the theme of AI-driven trusted data space implementation.
In his view, four key technological barriers must be addressed to effectively deploy AI-driven trusted data spaces:
First, as AI and trusted data spaces penetrate industries, data inevitably becomes more diverse, complex, and multimodal. Only by achieving unified management of multimodal data can data be truly transformed into trusted circulation assets.
Second, the circulation of data elements must be deeply integrated with domestic models, domestic chips, and domestic data systems to build a solid, self-controllable AI data foundation.
Third, the diversity of data elements must be fully leveraged to unlock and release the multidimensional value of data circulation.
Fourth, the integration of AI data infrastructure and trusted data spaces should extend to a broader range of industrial scenarios and even the general public, fostering a model of broad-based participation to drive the market-oriented supply and efficient circulation of data elements.
During the dialogue, Zhu Jianyong shared KeenData's technological innovations and practical experience in building AI-powered trusted data spaces. Through a new AI data infrastructure, KeenData has supported the development of trusted data spaces in cities including Hangzhou, Suzhou, and Changsha, facilitating the trusted circulation and value realization of data elements.
KeenData Case Recognized as an AI + Trusted Data Space Development Practice Achievement
At the AI + Trusted Data Space Development Exchange, the organizers officially announced the annual practice case selection results. The case submitted by KeenData, titled "City-Level Trusted Data Space: Building a Foundation for Urban Data Element Circulation," was successfully recognized as an AI + Trusted Data Space Development Practice Achievement.
In this case, KeenData, as a recognized pilot unit in the first batch of trusted data space pilots by the National Data Administration, was deeply involved in the development of a city-level trusted data space. Leveraging its self-developed AI data integration platform, KeenData built a trusted, controllable infrastructure covering the entire data circulation and utilization lifecycle, effectively ensuring the secure and compliant supply of public data while establishing a mechanism for open access to high-quality datasets. The project has explored a viable path for the market-oriented allocation of data elements, providing a replicable and scalable demonstration model for the development of city-level trusted data spaces.
Technical Sessions Deep-Dive into Keen Agentic OS Core Capabilities
To help industry guests and partners gain a deeper understanding of the core capabilities of the Keen Agentic OS intelligent agent development operating system, KeenData hosted two consecutive technical sessions at its booth on August 28 and 29. Technical experts provided detailed walkthroughs of key capabilities including Data+Agent deep integration, Agent Runtime, Ontological Semantic Knowledge Base, Multi-Agent Collaboration, State-of-the-Art Training and Inference Performance (SOTA), and enterprise-grade governance and security. The experts also elaborated on the innovative upgrades to the KeenData Lakehouse multimodal lakehouse platform, covering its multimodal processing engine, multimodal data processing, and intelligent data pipelines. The two products work in deep synergy with interoperable capabilities, together forming the KeenData Agentic Lakehouse Platform intelligent foundation.
The technical sessions attracted a large audience of industry guests, partners, media professionals, and expo attendees, offering them an up-close look at KeenData's technological innovation capabilities as a leader in AI data infrastructure. Following the sessions, attendees engaged in in-depth discussions with KeenData's technical experts on core architecture, application scenarios, and implementation cases, gaining a tangible understanding of the product's technical value and deployment effectiveness through direct face-to-face exchanges.
From trusted data space development to unlocking the value of data elements, from agent applications to large-scale AI deployment, AI data infrastructure remains the solid foundation. Looking ahead, KeenData will continue to strengthen its technological innovation, deepen its full-stack AI data infrastructure capabilities, and build more replicable and scalable trusted data space implementation models. The company aims to help more enterprises achieve digital and intelligent transformation, making AI a true engine for business growth.
