Inference Analytics is building the next generation of healthcare AI from first principles. Our suite of AI platforms and applications is already in use across major academic medical systems by more than 3,000 users, supporting physicians and researchers, infection control teams, revenue cycle operations, and other high-stakes healthcare workflows.
Healthcare doesn't need another AI feature bolted onto legacy infrastructure. It needs AI designed from the ground up for sensitive data, complex workflows, high-stakes decisions, and strict compliance. Our mission is to put intelligent, agentic AI directly in the hands of clinicians, administrators, researchers, and healthcare leaders, helping them automate complex work, improve productivity, and make better-informed decisions.
Across our technology suite, we combine model-agnostic AI infrastructure, agentic orchestration, healthcare-specific applications, and intelligent user experiences. Our architecture works across both the back-end systems healthcare runs on and the front-end applications clinicians and staff use every day.
Rather than forcing every problem through a single model or approach, we match the right models, agents, and inference strategies to each workflow, optimizing for accuracy, performance, token efficiency, and cost. The result is practical enterprise AI built for environments where security, reliability, and trust matter.
We were building healthcare generative AI before it became mainstream. Our work in AI-powered clinical text generation began in 2019, years before ChatGPT brought generative AI into the mainstream, and led to published IEEE research on generating clinical text from radiology reports. That foundation continues to shape our approach today: building AI around the realities of healthcare, rather than adapting healthcare to fit AI.
