Content Moderation

AI & ML solutions

MEDIA & PUBLISHING

Moderation of Reviews & Comments

User-generated content can have elements which can be inappropriate to certain users of the media. Strict regulations have also made it mandatory for publishers to moderate the content on their platforms. ML can help in this regard by screening the posts and content in real-time to adhere to the policy and standard

Moderation of Reviews & Comments

E-COMMERCE

Product Review Moderation

Ecommerce sites use product review pages as a tool for customers to engage with the platform and provide feedback. The website has no control over the way customers can respond to good or bad products, but it can choose which reviews to be displayed on site. It is important to make sure that no inappropriate language or content is posted on the product review page. This can be ensured and screened by the Natural Language Processing capabilities of AI.

Product Review Moderation

CUSTOMER SERVICE

Chat Moderation

Customer service platforms get a huge volume of chat messages from users. They face a tough task while dealing with toxic or offensive phrases from unhappy customers. The customer service industry uses NLP-based algorithms to analyze chat text in real-time and provide an immediate response to users. NLP is used to develop chat moderation solutions that detect normal messages and chats containing offensive language. These moderation solutions are more accurate and cost-effective than manual moderation systems.

Chat Moderation

BANKING

Regulatory Compliance Monitoring

Regulatory changes have increased exponentially for the financial industry in the past decade. Compliance officers have to interpret tons of regulatory documentation manually and run the risk of making mistakes and oversights. Employing AI, banks can automatically curate regulatory content from financial, federal and state-level regulatory sources. Using Named Entity Recognition (NER), meaningful insight can be extracted quickly from this content, saving banks time and reducing manual resource costs. Banks can then align their policies and workflows to meet these regulations much more efficiently.

Regulatory Compliance Monitoring

BANKING

Enterprise Correspondence Monitoring

Banks employ stringent data security laws to prevent breach of sensitive information. Misaddressed or unauthorized Emails / messages may lead to data loss or security threats. Using Natural Language Processing, AI systems can monitor and identify suspicious correspondence content. Messages having highly secretive data or recipients not suitable for their context are automatically flagged and escalated to the Compliance/Data Security personnel. Using this, AI helps Banks reduce costs from fines of data security laws infringement.

Enterprise Correspondence Monitoring

HR & RECRUITMENT

Chatbot Pre-screening

AI-enabled chatbots can remove the need for lengthy job application forms by performing candidate pre-screening. Recruiters employ these chatbots on their portals to engage in conversation with candidates. Chatbots can gather information like candidate location, contact details, experience level, and employment eligibility. NLP functionalities of chatbots can also interpret answers to predefined pre-screening questions that test the aptitude and behavior of the candidates. Based on this evaluation, the AI can create candidate profiles, and shortlist applicants, simplifying further assessment for recruiters. Chatbots also improve the candidate experience, as they can provide real-time assessment, feedback, and regular updates on the application process to the candidates.

Chatbot Pre-screening

More Case Studies and Blogs

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Check List

How to Ensure That Your Machine Learning Project Is Successful

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