Identify if memo contains a profanity
using AI
Below is a free classifier to identify if memo contains a profanity. Just input your text, and our AI will predict if the memo contains profanity - in just seconds.
Contact us for API access
Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("if-memo-contains-a-profanity", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/if-memo-contains-a-profanity/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/if-memo-contains-a-profanity/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict if the memo contains profanity.
This pretrained text model uses a Nyckel-created dataset and has 2 labels, including Clean and Contains Profanity.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if the memo contains profanity).
Whether you're just curious or building if memo contains a profanity detection into your application, we hope our classifier proves helpful.
Related Classifiers
Need to identify if memo contains a profanity at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Customer Support Monitoring: This use case involves analyzing customer support communications for inappropriate language. By identifying memos containing profanity, organizations can flag interactions for review, ensuring that customer service representatives maintain professionalism and addressing any potential issues in communication.
- Content Moderation for User-Generated Platforms: Platforms that allow user-generated content, such as forums or social media, can use this function to filter out any inappropriate language. This ensures a safe and respectful environment for users, helping to enhance user experience and adhere to community guidelines.
- Employee Conduct Review: Companies can utilize this functionality to monitor internal communications for profanity in emails or memos. Identifying inappropriate language can inform HR policies, help manage workplace culture and ensure compliance with professional conduct standards.
- Compliance and Legal Monitoring: Financial institutions or regulated industries can implement profanity detection in memos to ensure compliance with conduct regulations. Identifying inappropriate language can assist in maintaining ethical standards and avoiding potential legal repercussions.
- Automated Content Filtering for Marketing: Marketing teams can use this function to ensure that promotional content does not include profanity before distribution. This helps protect the brand image and ensures that all public communications align with company values and expectations.
- Sentiment Analysis Enhancement: By integrating profanity detection into sentiment analysis tools, businesses can better gauge public sentiment related to their products or services. Memos with profanity could indicate higher levels of frustration or dissatisfaction, allowing companies to proactively address issues.
- Training and Development Feedback: During performance evaluations, organizations can analyze feedback memos for the presence of profanity to identify any possible communication breakdowns or conflicts. This can inform targeted training programs aimed at improving interpersonal communication skills among employees.