AIDC Computing Power & Hardware-Software Adaptation

Adapt GPU servers, intelligent computing clusters, container platforms and model runtime environments, supporting deployment of mainstream open-source models, inference frameworks and AI applications.

Hardware delivered with ready-to-run AI capability to cut integration costs and trial cycles.

Token Performance Optimization

Optimize inference throughput, VRAM utilization, context management, concurrent scheduling and cost control to boost Token output on existing computing resources.

Maximize value from given compute and keep model invocation costs controllable.

High-quality Industry Dataset Development

Leverage business documents, process records, knowledge bases and historical data to deliver data cleaning, labeling, structuring and train/evaluation dataset construction.

Convert enterprise archives into trainable, retrievable and reusable AI data assets.

Vertical Model Adaptation & Tuning

Based on general LLMs and open-source ecosystem, we conduct model selection, fine-tuning, RAG enhancement and effect evaluation for customer service, government, manufacturing, finance, education and research scenarios.

Enable models to understand industries and workflows better, improving business responses and task execution.

Joint Development of AI Agents

Build enterprise-specific agents on Agent frameworks, integrating tool calling, workflow orchestration, automatic skill generation and sandbox testing to close the loop from task understanding to execution feedback.

Beyond model capabilities, we help integrate AI into real business workflows.

Sandbox Validation & Continuous Iteration

Quickly validate agent capabilities in isolated test environments. Continuously assess performance, refine prompts, expand tool sets and iterate datasets and business workflows.

Validate before launch with iterative updates to lower enterprise pilot risks.