LLM Integration
We embed LLMs into your product and internal processes the way we'd want them built for our own systems: grounded in your actual data, evaluated against real outcomes, and monitored after ship.
RAG pipelines and context design so responses are grounded in your data, not the model’s training set alone.
Eval suites and prompt regression testing, so a model update doesn’t silently break behavior your team is relying on.
Streaming responses, structured outputs, and tool-calling wired directly into your existing product surface — not a bolted-on chat widget.
Model routing, caching, and prompt design that keeps inference costs and response times sane at real usage volume.
The models and frameworks behind the integrations we ship.
Anthropic Claude · OpenAI · LangChain · Python
Tell us what you’re building. We’ll reply within one business day.