Nithin Hadhge Girish Kumar@nithin_kumar_547

OncoFlow is an AI-powered oncology scheduling product that helps hospitals protect treatment timelines and unlock more clinical capacity, not just fill calendar slots. Built on IBM watsonx Orchestrate, it acts as an agentic copilot for care teams, coordinating doctors, patients, and systems so high-risk treatments stay on track even when availability changes at the last minute. The product is born from a real operational problem we see in cancer hospitals today, oncologists with rigid and shifting availability, schedules managed in spreadsheets and calls, and frequent disruptions like sick calls or equipment outages. When this happens, staff scramble, capacity is wasted, and some high-risk chemotherapy or radiation sessions slip beyond safe windows. That translates directly into poorer outcomes, lower patient satisfaction, and higher stress and overtime for staff. OncoFlow addresses this as a repeatable, deployable solution. A Scheduler Agent optimizes weekly oncology schedules based on doctor constraints, patient demand, and a treatment risk score, then automatically updates calendars. A Disruption Agent responds when a doctor or system is suddenly unavailable, finds safe alternatives, drafts empathetic messages, and escalates edge cases to humans instead of making unsafe decisions. An Orchestrator Agent routes requests between them and uses a PubMed-backed tool to surface oncology research when clinicians ask why a delay is risky, supporting evidence-aware decisions. As a product, OncoFlow-AI is designed to plug into hospital workflows as an AI layer on top of existing systems, reducing manual rescheduling effort, lowering the incidence of dangerous delays for high-risk patients, and improving patient communication. For hospital leadership, this translates into measurable value, better utilization of limited oncology capacity, fewer missed or unsafe treatment windows, and more transparent, defensible scheduling decisions that can scale across sites.

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