Source: H3C |Original Link

With the evolution of large models, AI agents have demonstrated practical utility in personal office and daily life scenarios; however, their implementation in government and enterprise sectors has progressed far below expectations. According to IDC data, as many as 90% of AI projects in these sectors remain at the Proof of Concept (PoC) stage. General-purpose AI agents frequently encounter adaptation gaps within government and enterprise business environments, while private domain deployment faces multiple barriers, including data sovereignty, regulatory compliance, and system integration. Consequently, despite having established computing centers, many government and enterprise clients continue to struggle with operationalizing business applications.

How can AI be effectively integrated into the core business processes of government and enterprises? H3C, a subsidiary of Unisplendor Corporation, highlighted itsEnd-to-End Private Domain AI Agent Solutionat this year's WAIC, empowering government and enterprise clients to convert token value into intelligent business upgrades within their private domains.

Deploying Private Domain AI Agents Is Not Merely Software Installation

During implementation, government and enterprise clients commonly face practical concerns characterized by reluctance, hesitation, and cost constraints:

  • Reluctance stems from the lack of clear methodologies and tools for scenario identification and data governance, leaving organizations uncertain about where to begin;
  • Hesitation arises from the absence of systematic security and compliance safeguards, creating fears of data breaches or regulatory risks;
  • Cost constraints result from difficulties in controlling expenses related to model adaptation and architecture design, rendering ROI unpredictable.

In response, H3C offers a modular, phased end-to-end implementation framework that delivers coordinated capabilities across computing power, platforms, and services, enabling clients to select appropriate AI application entry points based on their existing infrastructure:

  • Computing Power Layer: Centered on the UniPoD Super Node Cluster, this layer provides horizontally scalable AI infrastructure to ensure the economic efficiency and continuity of token generation.
  • Platform Layer: This layer offers tools for model governance, data preparation, and agent orchestration, enabling clients to transform private domain data into actionable agent capabilities while significantly lowering barriers to secondary development.
  • Service Layer: The delivery team engages directly with client operations to execute scenario selection, system integration, performance optimization, and operational support, thereby embedding technical capabilities into specific workflows.

Five Key Capabilities Addressing AI Implementation Challenges in Government and Enterprise Sectors

Through continuous co-creation with government and enterprise clients, H3C has addressed concerns regarding reluctance to engage, hesitation to adopt, and affordability constraints by establishing five key capabilities covering the entire lifecycle of private-domain intelligent agent deployment:

  • Scenario Identification: Based on client business requirements, scenarios with clear ROI and robust data foundations are selected for AI integration. This approach avoids overly broad implementations and ensures a defined return expectation for each investment.
  • Data Governance: Multi-source heterogeneous data is processed through knowledge extraction, regularization, and structuring, enabling stable and efficient consumption of private-domain data by models.
  • Model Adaptation: Foundation models are flexibly selected according to business needs, followed by vertical fine-tuning and alignment training to achieve an optimal balance between model performance and inference costs.
  • Architecture Design: Multi-agent collaboration and allocation mechanisms are optimized to enable automatic planning, decomposition, and execution of business requests within the private-domain environment, eliminating the need for manual intervention in complex processes.
  • Security Assurance: Isolation and control measures are implemented across model outputs, agent behaviors, and audit logs to fully satisfy government and enterprise compliance and security requirements.

Industry Practices: From Pilot to Application

Leveraging the aforementioned solution capabilities, H3C has achieved scalable operations across multiple government and enterprise sectors, transitioning from pilot projects to full deployment:

In the field of bidding supervision, H3C developed a full-chain supervision system for a provincial-level agency under a central ministry. Upon deployment, the team formulated 64 computable rules, established industry rule libraries comprising 26 and 38 entries respectively, integrated over ten data sources, and deployed 12 large models alongside 64 small models to realize automated multi-agent planning and execution. Over 17 months of operation, the system generated 198,000 alerts, verified 170,000 cases, assisted in recovering economic losses totaling RMB 1.409 billion, and facilitated the refinement of more than 550 bidding regulations. In one notable instance, AI-driven alerts identified anomalies in credit scoring, uncovering a case of disguised bid rigging; responsible parties were held accountable in accordance with the law, and the case was featured in a special report by CCTV.

In the power and energy sector, IoT SIM card management at a provincial grid company had long relied on manual processes, resulting in cumbersome workflows and delayed responses amid quarterly activations exceeding 50,000 cards and a backlog of 100,000 anomalous cards. H3C deployed a customized intelligent agent system for IoT SIM card management tailored to this operational context. The system automatically matches tariff plans, identifies dormant and anomalous cards, and generates standardized remediation recommendations, achieving end-to-end automated closed-loop management. After one year of operation, over 430 inactive cards were cleared, one full-time position was reallocated, and the organization successfully transitioned from reactive handling to proactive early warning.

For government and enterprise clients, the value of large models lies not in parameter scale, but in their ability to deliver quantifiable benefits within real-world business operations. The H3C Private Domain Intelligent Agent End-to-End Solution establishes a closed loop for token generation and application entirely within the client's private domain. Through the integrated coordination of computing power, platforms, and services, this solution enables AI capabilities to be seamlessly embedded into daily business workflows. Moving forward, H3C will continue to refine its engineering capabilities, transforming project experience into standardized toolsets, and collaborating with clients to advance the practical implementation of intelligent transformation across the government and enterprise sectors.