FAQs

AI text analytics uses artificial intelligence and natural language processing (NLP) to analyse unstructured text such as emails, reviews or chat messages. It transforms raw text into structured insights that businesses can use to improve decision-making and customer experience.

Sentiment analysis applies AI and machine learning to detect the emotions and opinions within text. It categorises customer comments as positive, negative or neutral, and highlights trends over time. This helps businesses identify satisfaction drivers and address issues quickly.

Research shows that 90% of enterprise businesses say data is becoming critical to their success. Text analytics unlocks hidden value in conversations, allowing organisations to make smarter, data-driven decisions and stay competitive.

AI text analytics can process support tickets, customer emails, product reviews, surveys, social media comments and even transcribed voice calls. By centralising multiple data sources, it gives businesses a complete view of customer feedback.

Yes. 70% of customers say they are more loyal to companies that listen to their feedback and act on it. By analysing text at scale, businesses can spot issues earlier, improve service and build stronger relationships.

AI helps leaders focus on what matters most. Instead of manually reviewing thousands of conversations, the technology highlights trends and emerging topics. Studies show 73.5% of executives now base decisions on data, and text analytics makes that possible.

Yes. Modern platforms use encryption, role-based access, and secure integrations to ensure customer data is protected. Many are designed with compliance in mind, so businesses can analyse text without breaching regulations.

Industries with high customer interaction — such as retail, telecoms, financial services, travel, and healthcare — gain the most. Text analytics helps them manage large volumes of feedback, identify pain points, and improve customer service efficiency.

AI Engine is a text analytics platform that automates the analysis of customer conversations and feedback. It applies sentiment analysis, topic detection, and rule-based logic to uncover insights and trigger workflows in real time.

By monitoring sentiment across emails, chats, reviews and voice transcripts, AI Engine flags issues before they escalate. This enables faster responses, proactive engagement and better customer experiences overall.