OpenAI
We ship on OpenAI's models when you need broad capability, voice and realtime interaction, or a model fine-tuned to your domain.
OpenAI's GPT models are a dependable, widely supported default for a huge range of tasks, which makes them a natural building block for production systems. The Realtime API lets us build genuine voice and low-latency conversational experiences, and fine-tuning lets us shape a model to your tone, formats, and edge cases when prompting alone is not enough.
We use OpenAI on its merits and keep it interchangeable. Whether you run it through OpenAI directly or through Azure OpenAI inside your own tenant, we put it behind the same routing layer as the rest of the stack. That gives you OpenAI's strengths today and the freedom to move workloads as price, performance, and policy shift.
What we use
- GPT models for general reasoning, generation, and classification at scale
- Realtime API for low-latency voice agents and live conversation
- Fine-tuning to lock in your tone, formats, and domain-specific behavior
- Structured outputs and function calling for reliable, system-ready responses
- Azure OpenAI option to run the same models inside your compliance boundary
We integrate OpenAI through your own keys or through Azure OpenAI when you need the models inside your enterprise tenant. Voice and realtime work connects to your telephony or app front end with latency budgets we hold to, and fine-tuned models are versioned and evaluated before they ever reach production. Everything runs behind a provider-agnostic layer with logging, rate-limit handling, and cost controls in place, so you get OpenAI's capability under your governance and can reroute workloads without touching application code.
Questions, answered
It depends on your constraints. Azure OpenAI keeps the models inside your own tenant and compliance boundary, which regulated clients often need. Direct OpenAI access can move faster on the newest features. We build so the choice is a configuration, not a commitment.
Often prompting and retrieval get you there first, and we try those before recommending a fine-tune. When your formats or edge cases are strict and high-volume, a fine-tuned model pays off, and we version and evaluate it so quality is measured rather than assumed.
Let's build the intelligence that moves your business.
Tell us where you're headed. We'll show you what's possible, and exactly how we'd get there together.