Our client, a leading Canadian healthcare provider, sought to integrate OpenAI for innovation. With over two dozen independent lines of business, they aimed to consolidate patient health records and develop a secure chatbot for real-time assistance during consultations and care planning.
A leading Canadian home and community healthcare provider wanted to put generative AI to work, but it was facing a hard version of a common problem. The organization runs more than two dozen independent lines of business, each in its own system, and many of them serve the same patients. A patient's history was therefore scattered across systems that did not talk to each other, so no clinician could see the whole picture in one place.
What the provider wanted was an assistant that could pull that fragmented record together: consolidate and summarize a patient's health history, answer clinical questions in real time, summarize and analyze documents, and even transcribe physician notes during consultations. The non-negotiable was privacy. Whatever got built had to keep sensitive patient data secure and inside the provider's own environment.
The provider had already tried the obvious route, summarizing patient records by sending them straight to a GPT model, and found it expensive and hard to control. BITSUMMIT took a different approach: ground the model in the provider's own data through a private search index, so the assistant retrieves the relevant records first and generates from them, rather than reasoning over raw documents every time. That retrieval step is what brought the cost down and kept answers tied to real patient data.
Ground the model in a private index
BITSUMMIT built an industry-specific back-end search index over the unified records and wired it to Azure OpenAI through the Azure Chatbot framework. A clinician's question first retrieves the relevant material from the index, and the model answers from that grounded context, which both optimizes cost and keeps the response anchored to the provider's own information. The whole solution was built to run inside the provider's existing infrastructure, so patient data never leaves their environment.
Build for real clinical use cases
From there the team developed the use cases that mattered on the floor: comprehensive patient 360° summaries that draw a single view from across the lines of business, real-time question-and-answer, document summarization and analysis, and transcription of physician notes during consultations. At the provider's request, the project then grew into a tailored search bot for healthcare professionals, giving clinicians fast, individualized access to patient notes with privacy preserved per record.
Transfer the knowledge
Throughout, BITSUMMIT ran regular education sessions so the provider's own team could identify new use cases, move them into production, and get the most out of Azure OpenAI, leaving them able to keep building rather than depending on outside help for every next step.
The assistant gave clinicians something they had never had: one comprehensive view of a patient across every line of business. Documentation became faster and more accurate, with fewer manual errors, and staff productivity rose as summarization and Q&A took the friction out of everyday tasks.
That patient 360° view also changed the business. With a clear picture of patient interactions across services, the provider could build more personalized care plans and strengthen its position in negotiations with major third-party insurers, contributing to a 30 to 40 percent improvement in financial health. And because BITSUMMIT delivered the capability alongside the training to extend it, the provider came away with a framework for working with Azure OpenAI, other large language models, and Microsoft Fabric Copilot, ready to solve the next set of healthcare challenges on its own.
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