SKYHUB AI provides integrated MLOps for the deployment, operation, and management of AI models. Not only the models developed by DS2.ai, but also those previously developed or currently operating externally can be managed using SKYHUB AI.
SKYHUB AI offers a real MLOps service including AI deployment, operations/management and advancement.
Easy to configure servers for AI operations.
By continuously utilizing data collected during AI operations, artificial intelligence re-learns and advances.
External Artificial Intelligence can also be easily uploaded to operate in an optimal environment in DS2.ai.
Deploy artificial intelligence quickly and easily using auto-generated APIs.
Monitor servers and respond to issues in real time.
You can configure server performance or customize servers optimized for AI operating environments such as regional settings to operate/manage them efficiently.
* Server configuration other than AWS can be accommodated via individual inquiries.
Artificial intelligence developed outside of DS2.ai can also be deployed or managed using SKYHUB AI.
In order to continuously advance artificial intelligence, data generated through artificial intelligence operation is added to the initial training data and accumulated for retraining.
* Data accumulation for AI learning is only available with SKYHUB AI.
Deploy and operate artificial intelligence by using a CLICK AI server for your environment or by configuring optimized cloud servers yourself.
 | | |
|---|---|---|
| Server Setting | using DS2.ai's server | configure your own server |
| Model Delay | occurs when downloading AI models (with delay) | download model when booting (no delay) |
| API Rate | 5 times/1sec | depends on the server |
| Billing | per API call | Hourly Server Usage |
| Region | Korea only | Available Worldwide |
Monitor the built artificial intelligence pipeline servers in real time and respond quickly to issues.
The completed artificial intelligence model can be deployed and applied to services right away through API integration. In addition, using sharing service apps allows you to view the artificial intelligence results through the provided URL on the web without separate interworking services.
Artificial intelligence developed with DS2.ai can be mounted on edge devices and the inference results can be managed on the integrated environment through SKYHUB AI. This allows the model to be re-trained to improve artificial intelligence accuracy.
By utilizing numerical data collected through various sensors, you can configure a hub for developing artificial intelligence and configure various artificial intelligence-based inference environments such as anomaly detection.
from ds2 import DS2
ds2 = DS2(apptoken="s2234k3b4")
ds2.deploy(
"people.zip",
cloud_type="AWS",
region="us-west-1",
server_type="g4dn.xlarge"
)
Build a data pipeline for MLOps at DS2.ai with Python. SDK gives you access to all of the processes from uploading and labeling data, to training and deploying the artificial intelligence model.
Learn more →You can configure server performance or customize servers optimized for AI operating environments such as regional settings to operate/manage them efficiently.
* Server configuration other than AWS can be accommodated via individual inquiries.
Artificial intelligence developed outside of DS2.ai can also be deployed or managed using SKYHUB AI.
In order to continuously advance artificial intelligence, data generated through artificial intelligence operation is added to the initial training data and accumulated for retraining.
* Data accumulation for AI learning is only available with SKYHUB AI.
Deploy and operate artificial intelligence by using a CLICK AI server for your environment or by configuring optimized cloud servers yourself.
| | |
|---|---|---|
| Server Setting | using DS2.ai's server | configure your own server |
| Model Delay | occurs when downloading AI models (with delay) | download model when booting (no delay) |
| API Rate | 5 times/1sec | depends on the server |
| Billing | per API call | Hourly Server Usage |
| Region | Korea only | Available Worldwide |
Monitor the built artificial intelligence pipeline servers in real time and respond quickly to issues.
The completed artificial intelligence model can be deployed and applied to services right away through API integration. In addition, using sharing service apps allows you to view the artificial intelligence results through the provided URL on the web without separate interworking services.
Artificial intelligence developed with DS2.ai can be mounted on edge devices and the inference results can be managed on the integrated environment through SKYHUB AI. This allows the model to be re-trained to improve artificial intelligence accuracy.
By utilizing numerical data collected through various sensors, you can configure a hub for developing artificial intelligence and configure various artificial intelligence-based inference environments such as anomaly detection.
Build a data pipeline for MLOps at DS2.ai with Python. SDK gives you access to all of the processes from uploading and labeling data, to training and deploying the artificial intelligence model.
Learn more →
from ds2 import DS2
ds2 = DS2(apptoken="s2234k3b4")
ds2.deploy(
"people.zip",
cloud_type="AWS",
region="us-west-1",
server_type="g4dn.xlarge"
)