LLM Integration
Large Language Models (LLMs) like GPT-4o, Claude and Gemini are powerful tools that can transform your existing applications and workflows. Neuropad specializes in seamlessly integrating LLMs into your infrastructure — from simple API connections to advanced RAG systems with your own knowledge base. We ensure secure, cost-efficient and reliable LLM implementations.
Neler dahil
- GPT-4o & Claude 3.5 integration
- RAG (Retrieval Augmented Generation)
- Fine-tuning & prompt engineering
- Vector database implementation
- Streaming responses
- Cost monitoring & optimization
- Fallback & failover logic
- On-premise LLM options
Çalışma sürecimiz
Requirements analysis
Establishing use cases, quality requirements, privacy constraints and budget.
Model selection
Benchmarking LLMs on your specific use case for optimal price-quality ratio.
Architecture design
Design of the full LLM pipeline including vector databases, caching and monitoring.
Implementation
Development of the integration with your existing systems.
Evaluation & fine-tuning
Systematic evaluation and optimization of model performance.
Live & scalable
Production deployment with scalable infrastructure and monitoring.
Sıkça sorulan sorular
Which LLM is best for my application?
It depends on your use case. GPT-4o is excellent for complex reasoning. Claude 3.5 for long contexts. Cheaper models are fine for simpler tasks. We help you make the best choice.
How do you handle privacy-sensitive data?
We advise you on privacy compliance, offer on-premise options and configure data masking where needed. Your data always remains under control.
What is RAG and do I need it?
RAG connects an LLM to your own knowledge base so it gives answers based on your specific documents and data. Essential if you want an LLM to work on your business data.
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