Cloud MLOps at DS2.ai

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.

Optimal environment for using artificial intelligence

SKYHUB AI offers a real MLOps service including AI deployment, operations/management and advancement.

Optimized Cloud Reasoning Server

Easy to configure servers for AI operations.

Artificial intelligence re-learning

By continuously utilizing data collected during AI operations, artificial intelligence re-learns and advances.

Compatible with External Artificial Intelligence Models

External Artificial Intelligence can also be easily uploaded to operate in an optimal environment in DS2.ai.

Rapid deployment through API integration

Deploy artificial intelligence quickly and easily using auto-generated APIs.

Dashboard visualizing Real-time server

Monitor servers and respond to issues in real time.

Maximize AI's Efficiency with Reasoning Cloud Servers

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.

Easy deployment of AI by a simple upload

Artificial intelligence developed outside of DS2.ai can also be deployed or managed using SKYHUB AI.

Framework uploadable to SKYHUB AI

Advanced artificial intelligence through continuous learning

Through the operation of artificial intelligence, you can continuously advance artificial intelligence by adding data to the initial learning data and relearning it.

* Data accumulation for AI learning is only available with SKYHUB AI.

Optimized server configuration for 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

Real-time monitoring of AI operating environments

Monitor the built artificial intelligence pipeline servers in real time and respond quickly to issues.

Rapid AI deployment using APIs

DS2.ai's SKYHUB AI automatically creates APIs in four programming languages for rapid deployment and use of complete AI.

var data = JSON.stringify({
    "modelid": 228551,
    "apptoken": "sd12124dfsd11",
    "parameter": {
        "age__marketing.csv":0,
        "job__marketing.csv":"",
        "marriage__marketing.csv":"",
        "graduate__marketing.csv":"",
        "creditcard__marketing.csv":"",
        "salary__marketing.csv":0,
        "mortgageLoan__marketing.csv":"",
        "etcLoan__marketing.csv":"",
        "contact__marketing.csv":"",
        "latelyContact_day__marketing.csv":0,
        "latelyContact_month__marketing.csv":"",
        "latelyContact__marketing.csv":0,
        "latelyCampaign__marketing.csv":0,
        "pastMarketingSuccess__marketing.csv":""
    }
});
var xhr = new XMLHttpRequest();
xhr.withCredentials = true;

xhr.addEventListener("readystatechange", function () {
    if (this.readyState === 4) {
        console.log(this.responseText);
        }
});

xhr.open("POST", "https://api.clickai.ai/159/predict/");
xhr.setRequestHeader("content-type", "application/json");

xhr.send(data);

import requestsimport json
url = "https://api.clickai.ai/159/predict/"
payload = {
    "modelid":228551,
    "apptoken":"1c4f41ac9a02404dada5023f3e20a3b9",
    "parameter": {
            "age__marketing.csv":0,
        "job__marketing.csv":"",
        "marriage__marketing.csv":"",
        "graduate__marketing.csv":"",
        "creditcard__marketing.csv":"",
        "salary__marketing.csv":0,
        "mortgageLoan__marketing.csv":"",
        "etcLoan__marketing.csv":"",
        "contact__marketing.csv":"",
        "latelyContact_day__marketing.csv":0,
        "latelyContact_month__marketing.csv":"",
        "latelyContact__marketing.csv":0,
        "latelyCampaign__marketing.csv":0,
        "pastMarketingSuccess__marketing.csv":""
        "age__marketing.csv":0,
        "job__marketing.csv":"",
        "marriage__marketing.csv":"",
        "graduate__marketing.csv":"",
        "creditcard__marketing.csv":"",
        "salary__marketing.csv":0,
        "mortgageLoan__marketing.csv":"",
        "etcLoan__marketing.csv":"",
        "contact__marketing.csv":"",
        "latelyContact_day__marketing.csv":0,
        "latelyContact_month__marketing.csv":"",
        "latelyContact__marketing.csv":0,
        "latelyCampaign__marketing.csv":0,
        "pastMarketingSuccess__marketing.csv":""
        }
}
headers = {
'content-type': "application/json",
'cache-control': "no-cache",
}
response = requests.request(
    "POST",
    url,
    data=json.dumps(payload),
    headers=headers
)
print(response.text)

wget \
    --method POST \
    --header 'content-type: application/json' \
    --body-data '{"modelid":228551,"apptoken":"1c4f41ac9a02404dada5023f3e20a3b9","parameter": {"age__marketing.csv":0,"job__marketing.csv":"","marriage__marketing.csv":"","graduate__marketing.csv":"","creditcard__marketing.csv":"","salary__marketing.csv":0,"mortgageLoan__marketing.csv":"","etcLoan__marketing.csv":"","contact__marketing.csv":"","latelyContact_day__marketing.csv":0,"latelyContact_month__marketing.csv":"","latelyContact__marketing.csv":0,"latelyCampaign__marketing.csv":0,"pastMarketingSuccess__marketing.csv":""}'} \
    -O predict_result.txt \
    - https://api.clickai.ai/159/predict/

OkHttpClient client = new OkHttpClient();

MediaType mediaType = MediaType.parse("application/json");
RequestBody body = RequestBody.create(mediaType, "{"modelid":228551,"apptoken":"1c4f41ac9a02404dada5023f3e20a3b9","parameter":{"age__marketing.csv":0,"job__marketing.csv":"","marriage__marketing.csv":"","graduate__marketing.csv":"","creditcard__marketing.csv":"","salary__marketing.csv":0,"mortgageLoan__marketing.csv":"","etcLoan__marketing.csv":"","contact__marketing.csv":"","latelyContact_day__marketing.csv":0,"latelyContact_month__marketing.csv":"","latelyContact__marketing.csv":0,"latelyCampaign__marketing.csv":0,"pastMarketingSuccess__marketing.csv":""}}");
Request request = new Request.Builder()
.url("https://api.clickai.ai/159/predict/")
.post(body)
.addHeader("content-type", "application/json")
.build();

Response response = client.newCall(request).execute();

Cloud

Easy deployment and sharing of service apps

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.

Edge

Introduction of edge system and support of artificial intelligence data hub

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.

Sensor

Supports sensor-based artificial intelligence hub for anomaly detection

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.

SDK support for convenient programming development

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"
)

Maximize AI's Efficiency with Reasoning Cloud Servers

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.

Easy deployment of AI by a simple upload

Artificial intelligence developed outside of DS2.ai can also be deployed or managed using SKYHUB AI.

Framework uploadable to SKYHUB AI

Advanced artificial intelligence through continuous learning

Through the operation of artificial intelligence, you can continuously advance artificial intelligence by adding data to the initial learning data and relearning it.

* Data accumulation for AI learning is only available with SKYHUB AI.

Optimized server configuration for 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

Real-time monitoring of AI operating environments

Monitor the built artificial intelligence pipeline servers in real time and respond quickly to issues.

Rapid AI deployment using APIs

DS2.ai's SKYHUB AI automatically creates APIs in four programming languages for rapid deployment and use of complete AI.

var data = JSON.stringify({
    "modelid": 228551,
    "apptoken": "sd12124dfsd11",
    "parameter": {
        "age__marketing.csv":0,
        "job__marketing.csv":"",
        "marriage__marketing.csv":"",
        "graduate__marketing.csv":"",
        "creditcard__marketing.csv":"",
        "salary__marketing.csv":0,
        "mortgageLoan__marketing.csv":"",
        "etcLoan__marketing.csv":"",
        "contact__marketing.csv":"",
        "latelyContact_day__marketing.csv":0,
        "latelyContact_month__marketing.csv":"",
        "latelyContact__marketing.csv":0,
        "latelyCampaign__marketing.csv":0,
        "pastMarketingSuccess__marketing.csv":""
    }
});
var xhr = new XMLHttpRequest();
xhr.withCredentials = true;

xhr.addEventListener("readystatechange", function () {
    if (this.readyState === 4) {
        console.log(this.responseText);
        }
});

xhr.open("POST", "https://api.clickai.ai/159/predict/");
xhr.setRequestHeader("content-type", "application/json");

xhr.send(data);

import requestsimport json
url = "https://api.clickai.ai/159/predict/"
payload = {
    "modelid":228551,
    "apptoken":"1c4f41ac9a02404dada5023f3e20a3b9",
    "parameter": {
            "age__marketing.csv":0,
        "job__marketing.csv":"",
        "marriage__marketing.csv":"",
        "graduate__marketing.csv":"",
        "creditcard__marketing.csv":"",
        "salary__marketing.csv":0,
        "mortgageLoan__marketing.csv":"",
        "etcLoan__marketing.csv":"",
        "contact__marketing.csv":"",
        "latelyContact_day__marketing.csv":0,
        "latelyContact_month__marketing.csv":"",
        "latelyContact__marketing.csv":0,
        "latelyCampaign__marketing.csv":0,
        "pastMarketingSuccess__marketing.csv":""
        "age__marketing.csv":0,
        "job__marketing.csv":"",
        "marriage__marketing.csv":"",
        "graduate__marketing.csv":"",
        "creditcard__marketing.csv":"",
        "salary__marketing.csv":0,
        "mortgageLoan__marketing.csv":"",
        "etcLoan__marketing.csv":"",
        "contact__marketing.csv":"",
        "latelyContact_day__marketing.csv":0,
        "latelyContact_month__marketing.csv":"",
        "latelyContact__marketing.csv":0,
        "latelyCampaign__marketing.csv":0,
        "pastMarketingSuccess__marketing.csv":""
        }
}
headers = {
'content-type': "application/json",
'cache-control': "no-cache",
}
response = requests.request(
    "POST",
    url,
    data=json.dumps(payload),
    headers=headers
)
print(response.text)

wget \
    --method POST \
    --header 'content-type: application/json' \
    --body-data '{"modelid":228551,"apptoken":"1c4f41ac9a02404dada5023f3e20a3b9","parameter": {"age__marketing.csv":0,"job__marketing.csv":"","marriage__marketing.csv":"","graduate__marketing.csv":"","creditcard__marketing.csv":"","salary__marketing.csv":0,"mortgageLoan__marketing.csv":"","etcLoan__marketing.csv":"","contact__marketing.csv":"","latelyContact_day__marketing.csv":0,"latelyContact_month__marketing.csv":"","latelyContact__marketing.csv":0,"latelyCampaign__marketing.csv":0,"pastMarketingSuccess__marketing.csv":""}'} \
    -O predict_result.txt \
    - https://api.clickai.ai/159/predict/

OkHttpClient client = new OkHttpClient();

MediaType mediaType = MediaType.parse("application/json");
RequestBody body = RequestBody.create(mediaType, "{"modelid":228551,"apptoken":"1c4f41ac9a02404dada5023f3e20a3b9","parameter":{"age__marketing.csv":0,"job__marketing.csv":"","marriage__marketing.csv":"","graduate__marketing.csv":"","creditcard__marketing.csv":"","salary__marketing.csv":0,"mortgageLoan__marketing.csv":"","etcLoan__marketing.csv":"","contact__marketing.csv":"","latelyContact_day__marketing.csv":0,"latelyContact_month__marketing.csv":"","latelyContact__marketing.csv":0,"latelyCampaign__marketing.csv":0,"pastMarketingSuccess__marketing.csv":""}}");
Request request = new Request.Builder()
.url("https://api.clickai.ai/159/predict/")
.post(body)
.addHeader("content-type", "application/json")
.build();

Response response = client.newCall(request).execute();

Cloud

Easy deployment and sharing of service apps

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.

Edge

Introduction of edge system and support of artificial intelligence data hub

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.

Sensor

Supports sensor-based artificial intelligence hub for anomaly detection

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.

SDK support for convenient programming development

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"
)

Deploy your AI model right away.