Custom ChatBot, Local/Custom LLM, OpenAI & RAG Development
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About this service
Summary
FAQs
How long does it take to develop a chatbot or LLM?
Development time varies by complexity. Chatbots typically take 4-8 weeks, while custom LLMs can take 8-12 weeks or more.
Can you integrate the chatbot with existing systems?
Yes, I can integrate chatbots with various systems such as CRM, ERP, and customer service platforms.
What platforms do you use for LLM training?
I use state-of-the-art platforms and frameworks like TensorFlow, PyTorch, or custom solutions based on project needs.
How do you ensure the security of the AI systems?
I implement robust security measures, including encryption, secure APIs, and compliance with data protection regulations.
Can you customize OpenAI models for specific use cases?
Yes, I can fine-tune and customize OpenAI models to suit specific business needs and use cases.
What kind of support do you offer after deployment?
Post-deployment support includes monitoring, bug fixes, updates, and user training.
How do you handle performance optimization for LLMs?
I optimize LLM performance through efficient training, fine-tuning, and implementing scalable inference pipelines.
Do you provide documentation and training for the AI solutions?
Yes, I provide detailed documentation and training to ensure effective use and management of the AI systems.
What is your approach to integrating retrieval systems with RAG?
I design and implement retrieval systems that work seamlessly with generative models to enhance response accuracy and relevance.
What's included
Custom ChatBot Development
1. Fully functional chatbot with multi-platform integration. 2. Customized conversational flows and NLP capabilities. 3. Analytics dashboard and documentation. 4. Post-deployment support.
Local/Custom LLM Development
1. Locally trained and optimized LLM. 2. Model deployment with API integration. 3. Inference pipeline and ethical considerations. 4. Performance reports and documentation.
OpenAI API Integration
1. Integration of OpenAI models with custom APIs. 2. Prompt engineering and use case customization. 3. Monitoring tools and compliance measures. 4. Detailed documentation and ongoing support.
RAG Development
1. RAG pipeline with integrated knowledge base. 2. Custom retrieval algorithms and real-time inference. 3. Deployment, analytics tools, and feedback loop. 4. Documentation and maintenance plan.
