Large language models are powerful on their own, but they become transformative when connected to your business data and systems. We build the integrations that turn generic AI into a tool that understands your specific domain.

What We Do

• RAG systems — Retrieval-Augmented Generation pipelines that let LLMs answer questions using your documents, databases, and knowledge bases. We handle chunking, embedding, vector storage, and retrieval optimization.
• API integrations — connecting OpenAI, Anthropic Claude, and open-source models to your backend systems. Structured outputs, function calling, and tool use configured for your specific workflows.
• Prompt engineering and optimization — designing prompt chains and templates that reliably produce the outputs your application needs. We test systematically, not by trial and error.
• Fine-tuning and evaluation — when off-the-shelf models don't perform well enough on your domain, we fine-tune and build evaluation pipelines to measure and improve accuracy.

Infrastructure

We deploy LLM integrations on AWS with proper rate limiting, caching, fallback models, cost monitoring, and error handling. Production AI means handling edge cases, not just happy paths.