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I will create agentic rag systems for accurate info retrieval
Mudassir J
Über diesen Service
I create agentic AI chatbots powered by advanced RAG (Retrieval-Augmented Generation) techniques like reranking, speculative, and fusion. Using tools such as Python or N8N, your chatbot will retrieve accurate and relevant information to give precise answers.
How It Can Help You
- Education: Answer student questions and provide study materials.
- Finance: Give investment insights and explain financial terms.
- Healthcare: Share health tips and help schedule appointments.
- E-commerce: Recommend products and track orders.
- And more: Can be tailored for your industry or use case.
Tech Stack
- LangChain, LangGraph, CrewAI and more
- LLMs: OpenAI, Llama, Deepseek and more
Why Choose Me?
- Provides accurate and intelligent responses
- Tailored for your industry
- Seamless website and social media integration
- Continuous monitoring and updates
- Fast delivery
Lerne Mudassir J kennen
Mudassir J
AI and ML Engineer with expertise in Tensorflow and Generative AI
- AusPakistan
- Mitglied seitAug. 2021
Sprachen
Englisch
Check out my portfolio: https://mudassir-junejo.vercel.app
Mein Portfolio
FAQ
What is Retrieval-Augmented Generation (RAG)?
RAG is an advanced AI technique that combines retrieval-based and generative AI models to improve accuracy, provide up-to-date information, and generate more contextually relevant responses.
What services do you offer related to RAG?
I provide the following services: Building RAG-based chatbots and applications Implementing document retrieval for AI systems Optimizing retrieval models for better performance Integrating RAG with OpenAI, LangChain, or other frameworks Fine-tuning models for domain-specific knowledge
How does RAG improve chatbot performance?
Unlike traditional AI models that rely only on pre-trained data, RAG dynamically retrieves external knowledge, reducing hallucinations and making responses more fact-based and reliable.
Can you integrate RAG with my existing chatbot or application?
Yes! I can integrate RAG with various chatbot platforms, APIs, and frameworks like LangChain, OpenAI GPT, or custom AI solutions.
What kind of documents can RAG retrieve information from?
RAG can retrieve data from PDFs, databases, websites, APIs, and structured/unstructured documents, making it useful for knowledge-based applications.
