Agentic Products / 2025
OncoMate
An AI workspace for oncology equipment teams that turns a fault description into a grounded, reviewable work plan using manuals, repair history, PM notes, and parts data.
Operational knowledge is fragmented
Equipment teams troubleshoot across manuals, fault-code tables, preventive-maintenance records, inventory, and the memory of experienced technicians. A generic chatbot can sound helpful while missing the exact machine, prior repair, or part constraint that changes the next action.
OncoMate begins with the asset and its evidence. A technician describes the problem in ordinary language; the agent identifies the equipment, retrieves relevant fault references and completed repairs, checks PM context and parts availability, then proposes a reviewable sequence of next checks.
A knowledge engine, not a chat wrapper
The ingestion layer parses PMI machine files such as XML and WOX into structured fault events, flow states, and board-temperature histories. Work orders, maintenance outcomes, and service notes flow back into the same retrieval layer when work closes.
The agent uses a multi-turn tool loop rather than one large RAG prompt. Each step can narrow the asset, query a different evidence source, or surface a constraint. The answer remains tied to records the user can inspect instead of hiding behind model confidence.
Designed for an accountable domain
Authenticated access and tenant boundaries protect operational records. Retrieval failures degrade explicitly instead of inviting unsupported generation. The system treats the proposed work plan as decision support: useful because its evidence is visible, and reviewable because the technician remains in control.