Identify support request urgency
using AI
Below is a free classifier to identify support request urgency. Just input your text, and our AI will predict the urgency level of your support request - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("support-request-urgency", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/support-request-urgency/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_text_here"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_text_here"}' \
https://www.nyckel.com/v1/functions/support-request-urgency/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict the urgency level of your support request.
This pretrained text model uses a Nyckel-created dataset and has 5 labels, including Critical, High, Informational, Low and Medium.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the urgency level of your support request).
Whether you're just curious or building support request urgency detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify support request urgency at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Customer Support Prioritization: Implement a system to classify incoming support requests based on their urgency. This allows support teams to prioritize urgent issues, ensuring that critical problems are addressed swiftly to maintain customer satisfaction and minimize downtime.
- Automated Triage for Helpdesk: Utilize the false text classification function to automatically triage helpdesk tickets. By identifying the urgency of each ticket, the helpdesk can allocate resources more effectively and reduce response times, leading to increased operational efficiency.
- Real-Time Chat Support Management: Enhance real-time chat support systems by classifying chat inquiries according to urgency. This ensures that urgent customer requests are routed to the most experienced support agents quickly, improving resolution times for time-sensitive issues.
- Predictive Maintenance Alerts: In industries reliant on machinery, classify maintenance requests to determine their urgency. This proactive approach helps teams prioritize maintenance activities that could prevent equipment failures, improving operational reliability and reducing costs.
- Compliance and Risk Management: Use the classification function to identify urgent compliance-related support requests in regulated industries. By addressing these requests promptly, organizations can mitigate risks associated with non-compliance, safeguarding reputations and financial stability.
- Customer Feedback Management: When processing customer feedback, classify submissions for urgency to assess critical issues impacting the customer experience. This allows businesses to respond to urgent feedback more rapidly, enhancing customer loyalty and driving improvements in product or service offerings.
- Escalation Protocol for Issue Resolution: Implement an escalation protocol that leverages urgency classification to manage complex support issues. By ensuring that highly urgent cases are escalated appropriately, organizations can resolve escalated issues efficiently, thereby enhancing overall service quality and customer satisfaction.