AI integration means adding intelligent features to your existing product — for example, adding a GPT-powered chatbot to a customer portal, automating document processing with AI, or building a recommendation engine into an e-commerce store. MA Dev Studio identifies the highest-value AI touchpoints in your product and integrates them cleanly without disrupting your existing architecture.

We work with OpenAI (GPT-4, GPT-4o), Anthropic Claude, LangChain for agent orchestration, Pinecone and pgvector for vector databases, and custom ML pipelines with Python/FastAPI. We recommend the right stack for your specific use case rather than defaulting to one approach.

RAG stands for Retrieval-Augmented Generation. It's a technique that lets an AI model answer questions based on your specific documents or database — rather than general training data. For example, a legal firm could build a RAG system that answers questions based on their own case law library.

Only if you choose an OpenAI-based integration. MA Dev Studio can also implement on-premise or self-hosted AI models (like Ollama with Llama 3) if data privacy is a concern. We discuss this upfront during scoping.