We build three core product systems to support enterprises and R&D departments from training to inference.
A complete training infrastructure for enterprise AI R&D, integrating distributed frameworks, data pipelines, and compute scheduling.
Helps customers build high-quality datasets rapidly.
A systematic toolchain to reduce model costs, accelerate inference, and improve deployment efficiency.
Reduces inference cost by 50%–90%.
Graph optimization, operator fusion & vectorization.
Deep integration of Cloud Task Triggers + Distributed Lightweight Compute Nodes.
Auto GPU/TPU scheduling, massive model inference, high concurrency queues.
Millisecond feedback, works in weak networks, local privacy processing.
Smartly decides: Which tasks are faster locally? Which fit the cloud?
Result: Faster speed, lower cost, scalable deployment.
Proprietary Quantization Framework
Graph Optimization Kernel
High-Precision Distillation
Memory Reordering Acceleration
Professional large-scale training from data to execution.
Reduce inference costs and improve efficiency.
Underlying architecture co-construction for enterprises.
Building cloud triggers and edge inference environments.
We work with your technical team to build training systems, data flows, and optimization toolchains to shorten R&D cycles.
Ready to see how our true full-stack solution can help drive meaningful growth for you?