Tag: AI

Customer satisfaction shows how well your business meets user expectations. CSAT (Customer Satisfaction Score) is widely used, but the way most businesses collect it—through delayed surveys—misses key moments that shape how users actually feel. What really affects satisfaction is the experience itself: how fast users get help, how the interaction ends, and whether the result…

Crypto companies deal with high volumes of data, constant user interactions, and fast-changing regulations. Managing this at scale is difficult with just manual processes. AI agents help by automating repetitive tasks, handling routine support queries, and improving how information is processed and used across the organisation. They reduce workload, improve response times, and bring more…

Large Language Models (LLMs) are increasingly used in different types of applications but they present several security risks. As their integration into daily technology grows, it is crucial to understand their vulnerabilities to protect users and systems. Hackers are finding ways to exploit these models, including hidden prompt injections and manipulation of training data. These…

Chain of Thought (CoT) prompting is a technique in artificial intelligence (AI) reasoning that is gaining widespread recognition. It enables AI to solve complex tasks by breaking them down into smaller, logical steps. Instead of delivering an answer directly, models following CoT prompting provide a more thoughtful and transparent solution process, similar to how we…

Human-in-the-Loop (HITL) brings human oversight into key stages of the AI lifecycle, improving model accuracy and enabling AI to handle complex, real-world scenarios. By combining human judgment HITL addresses common issues in AI systems, such as errors and biases, which can significantly impact outcomes. In sensitive sectors, HITL is essential to ensuring both accuracy and…

AI performs best when given structured tasks. Prompt chaining is a technique that breaks complex requests into sequential steps, allowing AI to process information more effectively. Instead of handling an entire task in one go, AI completes each step separately, refining responses at every stage. This leads to greater accuracy, reduced errors, and better control…