OpenAI & LLM Integration
Embed intelligence directly into your products. From RAG systems that chat with your private data to automated content generation workflows — I build production-grade LLM integrations that don't break when scaled.
Integration Capabilities
Common Questions
How do you prevent the AI from hallucinating?
I use RAG (Retrieval-Augmented Generation) architectures where the AI is forced to cite its sources from your private data (stored in a vector database like Pinecone). I also use strict prompt engineering and system instructions to bound the model's behavior.
Can you use open-source models instead of OpenAI?
Absolutely. Depending on your data privacy requirements, we can use open-source models like Llama 3 via Ollama, Hugging Face, or Groq. This is especially useful for healthcare or finance sectors.
How much does it cost to run these models in production?
It depends on volume, but I optimize costs heavily by caching repeated queries, using embeddings effectively, and routing simple tasks to cheaper models (like GPT-4o-mini or Claude 3 Haiku) while reserving GPT-4 for complex reasoning.