A critical engineering challenge while building Jarvis was converting unstructured data into precise, structured enterprise actions. We developed the Agentic Extraction Engine to solve this.

LLM wrappers have taken over the tech news, but real value comes from abstraction. The gap between infrastructure and enterprise software is far and wide.

From speech, to intelligent agents, back to speech, we explain how we've architected enterprise-grade voice agents for Life Sciences.

When shared context exists across accounts and journeys, the learning compounds. This marks a shift from systems that merely record activity to those that inform action.

We have raised $5 million in seed funding to build the first clinical-grade Voice AI Operating System designed to transform how the life sciences industry engages with clinicians and patients globally.

AI is accelerating the how of frontend development, but we have to deepen the human responsibility to solve the why