CIIP Platform・Industrial Internet

Powered by the CIIP platform and ecosystem partners, deliver next-generation industrial network transformation solutions. Built on 5G + TSN (Time-Sensitive Networking) + industrial PON converged networking, establish full-scenario industrial communication covering enterprise intranets, campus private networks, and cross-factory collaborative networks. End-to-end services from network planning, equipment selection, and construction to operations and maintenance. End-to-end network slicing ensures highly reliable, low-latency industrial data transmission—addressing data silos, protocol barriers, and security vulnerabilities in legacy industrial networks while achieving deep IT/OT integration. Business model: solution delivery + O&M services + platform operations.

The CIIP platform provides low-code industrial APP integration services, lowering the barrier to digital application development for industrial enterprises. Pre-built component libraries for BRICS industrial scenarios—production monitoring, quality traceability, equipment management—enable drag-and-drop configuration for rapid custom app deployment. Multi-language and multi-standard support resolves cross-country protocol differences, enabling cross-border, cross-industry APP reuse. Integrated platform capabilities—identification resolution, data acquisition, model invocation—connect APPs to industrial data pipelines. Business model: platform licensing + custom development + value-added services.

Build dedicated national industrial model pools with a "large-model foundation, small-model specialization" strategy, delivering core model capabilities for BRICS industrial digital intelligence. Integrate general-purpose industrial LLMs covering production scheduling, quality control, supply chain optimization, and other foundational scenarios, plus industry-specific small models for raw materials, high-end equipment, and other key sectors—adapted to each country's industrial standards and process specifications. Provide full lifecycle services including model registration, version management, online inference, and model evaluation, with cross-border deployment and collaborative optimization. Address poor industry model adaptability and insufficient cross-model coordination. Business model: model licensing + inference services + custom optimization.

The CIIP platform integrates computing resources from AI data centers, edge nodes, and cloud providers into a unified scheduling platform. For BRICS industrial AI workloads, deliver elastic compute supply, model training acceleration, and inference deployment optimization—addressing high compute costs, insufficient supply, and inefficient scheduling. Multiple billing models including pay-as-you-go, reserved instances, and spot compute lower enterprise compute barriers. Business model: compute leasing + scheduling services + integrated solutions.

Build a BRICS industrial data product library aggregating data from manufacturing, energy, supply chain, and other key domains—layered into general-purpose, industry-common, and dedicated datasets. Leverage identification resolution for data element ownership and traceability, with standardized tiered data product licensing and full-process processing—cleansing, labeling, synthesis, and evaluation. Open platform APIs enable multi-party dataset co-construction, forming a commercial loop of scenario discovery, data collaboration, and model empowerment.

Built on identification resolution, establish a three-tier service architecture: data integration, data interoperability, and data circulation. Data integration—connect internal IT/OT systems, equipment, and management layers to eliminate silos. Data interoperability—cross-enterprise, cross-industry, cross-border standardized data recognition and sharing to break protocol barriers. Data circulation—secure, compliant cross-border data trading and sharing through identification resolution and data ownership, unlocking data element value.

The CIIP platform's precision matching engine connects industrial data elements with AI applications—solving the industry pain points of data without scenarios, scenarios without models, and models without data. Intelligent recommendation algorithms enable precise three-way matching of data products, industrial scenarios, and AI models, delivering integrated "data + scenario + model" solutions. Multi-dimensional search and matching by industry, scenario, and data type lower AI adoption barriers and accelerate industrial intelligence deployment.

Security as foundation, intelligent computing as enabler—leveraging Xintong Guardian for classified data security management throughout the full dataset construction lifecycle. Dual assessment systems for data quality and security risk address cross-border industrial data security challenges and inconsistent data quality. Business model: security services + three-platform operations + integrated solutions.

Build a cross-border industrial AI model ecosystem—guiding partners to model and standardize industrial mechanisms and process knowledge while upgrading core capabilities in model inference and cross-modal processing. Integrate general industrial LLMs for raw materials, high-end equipment, and other key industries, plus dedicated small models for quality inspection, process optimization, and other scenarios. Open model interconnection APIs to optimize cross-border large-small model collaboration, delivering a "large-model foundation + small-model specialization" system tailored to BRICS industrial needs.

Accelerate aggregation of design plans, BOMs, and related resources—enabling auto-generation of design drawings, 3D models, and control code to reduce R&D cycles and costs. Build AI-powered virtual production lines with autonomous decision-making for equipment state prediction, process optimization, equipment parameter tuning, and material balancing. Partner with ecosystem players to create intelligent service products—equipment O&M models, equipment knowledge graphs—and deliver unmanned smart inspection, real-time fault self-healing, intelligent command and dispatch, and smart warehousing.

Catalog typical IIoT-AI fusion scenarios, technology product lists, supplier directories, and standard indexes across steel, aviation, shipbuilding, construction machinery, agricultural equipment, electronics manufacturing, power, petrochemicals, non-ferrous metals, textiles, pharmaceuticals, light industry, and other key sectors. Accelerate scenario cultivation and openness, build a solution resource pool, and deliver precise supply-demand matching services.

The three-platform system cultivates industry-level intelligent solution providers with system integration capabilities and specialized service providers in industrial data and models. Full-chain incubation—technology enablement, resource matching, market promotion—nurtures local BRICS intelligent solution ecosystems in a virtuous cycle of platform empowerment, partner incubation, and ecosystem co-building.

The three-platform system integrates smart innovation centers, smart laboratories, and other institutions to build public service platforms for BRICS industry datasets and industrial model evaluation. Standardized dataset evaluation, model benchmarking, and algorithm validation provide authoritative third-party assessment for BRICS industrial AI development—driving quality improvement and standard harmonization.

The three-platform system promotes open-source projects and communities—sharing software code, hardware designs, and development tools. Build a BRICS IIoT open-source collaboration network for technology sharing and co-innovation, lowering industrial intelligence barriers and accelerating digital transformation. Community operations aggregate global developer talent into a sustainable innovation ecosystem.