Scaling with Confidence: Why Payoda’s Agentic AI Approach Wins
Introduction: Enterprises across industries are moving in the same direction when it comes to scaling up, controlling massive data, and maintaining quality. Nevertheless, the use of traditional automation and AI models has a threshold when the complexity goes up. They shine when it comes to performing routine tasks that follow strict rules but get stuck…
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Priyadharshini
Unlocking the Power of Sentence Transformers and Text Embeddings in LLMs
Introduction: Large Language Models (LLMs) have dramatically transformed the field of natural language processing (NLP). At the heart of their effectiveness lies one powerful concept: text embeddings. These text embeddings—dense vector representations of language—enable machines to understand, compare, and generate human-like text with remarkable precision. One of the most reliable tools for generating high-quality text…
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Priyadharshini
Fine-Tuning LLMs with LoRA Adapters: A Comprehensive Guide
Introduction Fine-tuning large language models (LLMs) can be computationally expensive and resource-intensive. Low-Rank Adaptation (LoRA) provides a more efficient and affordable way to fine-tune these models. In this blog, we’ll explore what Low-Rank Adaptation (LoRA) is, how it works, and how to apply it for fine-tuning an LLM. What is LoRA? Low-Rank Adaptation (LoRA) is…
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Priyadharshini
Why Agentic AI Isn’t Just a Buzzword: And How Payoda Makes It Real
Introduction Agentic AI is often referred to as the next level in artificial intelligence phenomena, but for many, it still sounds like a buzzword. Real-world agentic AI is now in the process of silently yet strongly creating a shift in how technology supports businesses. At Payoda, we help organizations discover their true value through real-world…
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Priyadharshini
The Payoda Difference: Moving Past Generic AI with Agentic AI
Introduction Organizations across industries are pressured to respond to customer needs, regulatory changes, and competitive markets with greater speed and integrity. Many have turned to AI for assistance. However, much of what exists today is generic AI. These tools automate mundane processes and generate data-driven insights but stop at task execution. They are unable to…
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Priyadharshini
The Fundamentals of NLP: How Machines Understand Human Language
Introduction In recent years, Natural Language Processing (NLP) has transformed the way humans interact with machines. From voice assistants like Siri and Alexa to chatbots providing customer support, NLP lies at the heart of many AI-driven technologies. However, a key question remains: how do machines actually understand human language, which is filled with nuance, slang,…
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Priyadharshini
Agentic AI: The Future of Independent and Purposeful Intelligence
Introduction Artificial intelligence (AI) is growing fast, and “Agentic AI” is a new type that’s changing how we think about technology. Unlike traditional AI, it focuses on being independent, flexible, and purposeful. But what does it really mean? Let’s explore Agentic AI, its uses, and its future, with a simple example to explain. What is…
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Priyadharshini
Agentic AI vs RPA: Payoda’s Edge in Measurable Business Outcomes
Introduction Enterprise automation is usually seen through the lens of Robotic Process Automation (RPA). Therefore, for many organizations, RPA has been the first and best step to minimize manual effort and streamline repetitive workflows. However, the business environments have become more complex, and customer expectations have risen. Hence, companies are beginning to realize that simple…
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Priyadharshini
AI in IT Operations: Predictive Analytics & Anomaly Detection
Introduction In today’s highly competitive and rapidly evolving digital landscape, businesses rely heavily on their IT infrastructure to maintain operations and deliver services seamlessly. However, managing and monitoring IT systems is a complex task, often requiring proactive measures to prevent downtime and ensure smooth performance. Traditional IT operations (ITOps) approaches can be reactive, where issues…
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Priyadharshini
AI for Cybersecurity: Threat Detection & Automated Incident Response
Introduction In today’s digital era, AI for cybersecurity is a critical priority for both businesses and individuals. Key factors driving this focus include the threat of regulatory fines and sanctions, the sophisticated tactics employed by cybercriminals to breach secure systems, and the potential fallout, such as reputational damage, a decline in brand image, reduced stock…
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