`AI AGENTS & VOICE`
Agents that hold up on a real call.
Voice and workflow agents that take routine calls and tasks, decide the next action and write it back to your system of record, with a person kept in the loop where it matters.
Start a conversationWhat we build
Voice agents with STT, LLM and TTS orchestration
Inbound and outbound call flows: intake, follow-up, scheduling
Workflow agents that read, decide and write back to CRM, EMR or core systems
Hybrid deployments: sensitive steps on local open-weight models, the rest in your cloud tenant
What we own in production
Turn-taking and interruption handling
Escalation rules and human handoff
Scripted conversation evals on every prompt change
Audit logging of every decision
Monitoring on real conversation outcomes
Typical team shape
** PM, AI engineer, back-end engineer, evaluation engineer, QA.
QUESTIONS
Frequently asked questions
Which models do you use?
Whatever fits your data and latency constraints. We have shipped on Azure OpenAI, Azure AI Speech and local open-weight models via ONNX Runtime.
Can an agent run without sending PHI to a third party?
Yes. In our healthcare work, PHI-touching steps ran on local models and only de-identified reasoning went to a covered cloud tenant.
How do you know an agent is ready?
It passes a scripted eval set and runs in shadow mode before it takes live traffic.
What does it cost to run?
We log cost per call from day one. Sometimes a model call costs more than the task is worth, and you should know that before scaling.
START
One line is enough.
Tell us what is slowing your engineering down. We reply with what we would do about it.