Edge AI inference array
AntHub
Built for edge AI. A high-density array architecture scales elastically and schedules AI compute on demand, with low-power hardware that delivers stable throughput and sharply lower inference latency.
Product photo
Core capabilities
Capability directions; supported models and performance ranges follow official specifications and project testing.
Elastic array compute
- Modular array design, deployed as a single node or freely combined, scaling with AI workload
- Multi-node scheduling pools compute resources and lifts overall utilization
- Distributed multi-site networking serves both small deployments and large centralized projects
Real-time inference acceleration
- Streamlined scheduling and task paths remove redundant work for millisecond-level response
- Tuned for dense, continuous inference that runs at high frequency over long periods
- Proximal compute completes analysis and feedback on site, with no cloud round trip
Domestically sourced, stable compute
- Domestic AI chips across a fully localized hardware stack, independent of external supply
- Tuned specifically for domestic chip architectures, supporting 24/7 edge inference
- Industrial-grade design — wide temperature, interference resistance, high fault tolerance
Product applications
The directions below come from product planning; supported models and performance ranges follow formal specifications and project test results.
On-site visual inference
For industrial image and video analytics, assess local inference against input scale and latency targets.
Model deployment & updates
Confirm the runtime environment and maintenance needs based on model type, precision and update frequency.
Edge node collaboration
Discuss single-node, cluster and cloud collaboration based on network, data retention and scale.
Product status
If you are already planning a selection, share your workload and deployment conditions and we will update you on the latest materials.
Prepare these details before contacting us
Source, count, resolution and retention requirements of image or video streams.
Model framework, precision, concurrency, latency and update frequency.
Network, power, site environment, administrative rights and fault handling requirements.
Product resources
The product line overview is available; the formal AntHub datasheet is not yet public.
Product matrix and solution overview, v0.1; downloadable once complete.
In preparationGet progress on materials and a project fit assessment.
Ask for product resources →Ask about AntHub
Share your business needs, deployment conditions and timeline so we can arrange the next technical step.