GPT integration is not a demo. We have built production AI systems with structured outputs, token cost management, fallback strategies, and evaluation pipelines.
Chat, function calling, embeddings, fine-tuning, vision — OpenAI's APIs cover the full spectrum of LLM use cases we encounter.
Uptime, latency guarantees, and structured output support that lets us build reliable AI features, not experimental prototypes.
Model selection strategy — GPT-4o for complex reasoning, GPT-4o-mini for high-volume tasks — keeps costs proportional to value.
System prompt design, few-shot examples, and output schema enforcement for consistent, reliable AI responses.
Vector embeddings, semantic search, and retrieval-augmented generation for grounding LLMs in proprietary data.
Streaming responses, token budgeting, model routing, and caching to build AI features that are fast and economical.
Every great product starts with a conversation. Tell us about your vision and let's explore how we can bring it to life.