OpenAI GPT-4

GPT-4 offers best-in-class reasoning, instruction following, and function calling out of the box — with no infrastructure burden for training or serving. For most production applications where latency under 3s and accuracy matter more than cost at low-to-medium scale, GPT-4 delivers faster time-to-production than fine-tuning an open-source alternative. We choose open-source models when cost at high scale, data privacy, or custom fine-tuning requirements make them the better fit.

A production OpenAI integration typically includes: a rate-limit-aware request queue, prompt versioning and management, streaming response handling, token cost tracking, semantic caching to reduce redundant API calls, fallback logic to a secondary model, and an evaluation framework measuring accuracy, latency, and cost per query. We instrument every deployment with observability so you can monitor real-user performance and catch regressions early.

Simple integrations (chat interface, document Q&A, summarization) typically take 3-6 weeks including evaluation and production hardening. Complex systems with RAG pipelines, multi-agent architectures, or fine-tuning workflows run 6-10 weeks. The majority of time goes into retrieval quality, output validation, and production reliability — not the API call itself.