DeepSeek-V4.1-Flash Now Available · 1M context, web search, and tool calling fully supportedAI Job Platform for Industry Scenarios
End-to-end AI development toolchain for autonomous driving, embodied intelligence, scientific computing, and more—from data labeling to model deployment in one integrated workflow.
Core Capabilities
Professional AI Tool Platform Built for Industry Scenarios
Industry-Preconfigured Tools
Pre-built toolkits and algorithm frameworks for autonomous driving, embodied intelligence, scientific computing, and more—ready to use out of the box with no need to build from scratch.
End-to-End Pipeline
Unified orchestration across the entire workflow—from data labeling and model training to simulation validation and deployment—streamlining the path from R&D to production.
Heterogeneous Compute Scheduling
Automatically matches CPU/GPU cluster resources, supporting large-scale distributed training and high-concurrency simulation with elastic scaling up to thousands of GPUs.
Scenario-Based Workflows
Visual drag-and-drop AI pipeline orchestration with support for custom pipelines and parameter templates, reducing engineering complexity and lowering the barrier to entry.
Industry Toolchains
End-to-end platform support for three core scenarios
Autonomous Driving
Autonomous Driving
- Multi-sensor fusion data labeling and scene library management, supporting LiDAR, camera, millimeter-wave radar, and other multi-source data
- Perception, prediction, and planning model training, supporting both end-to-end and modular architectures
- Closed-loop simulation validation pipeline supporting million-scale scenario parallel testing and regression analysis
- Pre-configured mainstream framework compatibility for seamless integration with existing R&D pipelines
Embodied Intelligence
Embodied Intelligence
- High-fidelity physics simulation environment integration with pre-configured mainstream engines and scene templates
- Reinforcement learning training for manipulation and navigation policies, supporting multi-task parallelism and policy distillation
- Sim-to-Real transfer toolchain with domain randomization and policy fine-tuning pipelines
- Real-world deployment SDK with cross-platform model export and real-time inference
Scientific Computing AI4S
AI for Science
- Accelerated molecular dynamics simulations with large-scale parallel sampling and free energy calculations
- Protein structure prediction and drug molecule screening pipelines with pre-configured models like AlphaFold
- Weather and climate foundation model training supporting global high-resolution forecasting and extreme event early warning
- Materials genome and quantum chemistry calculations integrated with mainstream DFT and high-throughput screening frameworks
Onboarding Process
Five steps from scenario selection to model deployment
Use Cases
Comprehensive coverage across the industry AI R&D lifecycle
Autonomous Driving R&D
End-to-end development for L2-L4 perception, planning, and end-to-end models. Supports large-scale scene library management and distributed closed-loop simulation to accelerate model iteration cycles.
Robotics Development
Policy training for manipulation and navigation capabilities across industrial robots, service robots, and humanoid robots. Supports Sim-to-Real transfer and adaptation to diverse hardware morphologies.
Frontier Research
AI4S applications including protein structure prediction, new material discovery, weather forecasting, and drug discovery. Provides HPC-grade compute with support for mainstream scientific computing frameworks.
Frequently Asked Questions
General compute services provide raw GPU computing resources, requiring you to build your own environment and tools. The Job Platform builds on this with pre-configured industry-specific toolkits, algorithm frameworks, and workflow templates, allowing you to directly launch training or simulation tasks with significantly reduced engineering overhead.
Fully supported. You can add custom algorithms, frameworks, and scripts on top of pre-configured toolchains, and save them as private templates for team reuse. The visual workflow editor supports drag-and-drop orchestration for flexible composition of all pipeline stages.
Simulation tools and scene templates themselves are not charged—you only pay for actual GPU compute resources consumed. Pre-configured simulation environments already include commonly used engines and scenes, ready for immediate use.
Data is stored with tenant-level isolation, and the entire pipeline—upload, training, and model export—is encrypted end-to-end. Private deployment options are available to meet data compliance requirements for autonomous driving and research scenarios.
Multiple mainstream simulation engines are pre-configured, covering autonomous driving and robotics scenarios. For scientific computing, we pre-configure AlphaFold, OpenMM, PySCF, and other popular frameworks. For specific tools not listed, contact technical support for rapid adaptation.