Generative AI: An In-Depth Analysis from Jetlink's Perspective
- Semra Kartal
- Mar 17
- 3 min read
Introduction: The Evolution of AI and the Rise of Generative Models
One of the most significant transformations in the field of artificial intelligence in recent years has been the emergence of generative AI (Generative AI - GenAI) models. Unlike traditional machine learning (ML) and linear regression-based statistical models, generative AI possesses the ability to create new content through data-driven learning and optimization strategies.
Particularly with large language models (LLM - Large Language Models), natural language processing (NLP) techniques, and diffusion-based image generation systems, generative AI has the potential to revolutionize business customer interactions, data analytics capabilities, and operational efficiency.
Jetlink has designed generative AI not just as a conventional chatbot model but as an interactive, dynamic, and self-learning system, offering tailor-made solutions for companies through its Genius and Genius Plus platforms.
Generative Models and the Deep Structure of AI
The Role of Deep Neural Networks (DNN) in Generative AI
A core component of generative AI systems is deep neural networks (DNN - Deep Neural Networks). These networks mimic biological brain functions through layered architectures, enabling advanced data processing and knowledge generation. The LLM-based models used by Jetlink employ multi-layered learning mechanisms to understand context, derive meaning, and generate responses accordingly.
The Dominance of Transformer Models
One of the biggest breakthroughs in generative AI has been the widespread adoption of Transformer-based models such as GPT-4, BERT, T5, and Claude. These models leverage self-attention mechanisms to enhance contextual processing capabilities. Jetlink's Genius Plus system utilizes a dual-stage GPT-to-RAG-to-GPT process, maximizing data-driven decision-making.
Retrieval-Augmented Generation (RAG) Technology and Real-Time Response Systems
Jetlink integrates Retrieval-Augmented Generation (RAG) architecture into its LLM-based systems, providing businesses with an accurate, real-time, and dynamic knowledge acquisition framework. With RAG:
User messages are scanned to extract relevant keywords.
Real-time queries are executed across vast databases.
The model generates the most appropriate response based on retrieved information.
Unlike static learning models, this approach eliminates the risk of LLM models generating outdated responses.
Agentic AI: Autonomous and Intelligent Digital Assistants
Agentic AI refers to AI systems that can make independent decisions to accomplish specific tasks. These systems go beyond merely generating responses and are capable of taking actions to achieve predefined goals, optimizing processes, and personalizing user interactions.
Intelligent Process Management with Agentic AI
Jetlink’s generative AI infrastructure enhances user experience by developing autonomous systems based on Agentic AI principles. For example:
When a customer wants to apply for a loan, AI does not just explain the process but fills out the necessary forms and submits the application.
For technical support requests, the chatbot doesn’t merely direct users—it diagnoses issues and suggests the best solutions.
In the automotive sector, when a user expresses interest in a specific car model, the chatbot not only provides details but also schedules a test drive, analyzes financing options, and recommends the best deal.
Continuous Learning and Adaptation Mechanisms
Unlike traditional chatbots that rely on static knowledge, Agentic AI systems continuously learn from interactions and evolve. Jetlink’s AI solutions:
Analyze past user interactions to deliver more accurate recommendations.
Leverage real-time data to provide the most up-to-date information.
Integrate with CRM systems to offer personalized services.
The Future of Digital Assistants with Jetlink’s Agentic AI Solutions
Jetlink’s Agentic AI-powered chatbots automate business processes across industries such as customer service, banking, automotive, and e-commerce, delivering significant advantages to enterprises.
For instance, Jetlink’s customer service solutions enable:
Automation of frequently asked questions, reducing human representative workload.
Optimization of sales processes, allowing faster and more effective responses to customer needs.
Enhancement of complex processes, improving customer satisfaction.
Future Vision
Jetlink leverages Agentic AI technologies to help companies build smarter, more efficient, and customer-centric solutions.
In the coming years, fully autonomous decision-making Agentic AI systems will significantly reduce the need for human intervention in business processes. By shaping the future of AI today, Jetlink continues to deliver cutting-edge intelligent assistant solutions for the corporate world.