BastionGPT does not carry an overarching memory from one chat to the next. This is a deliberate design choice rooted in patient safety and HIPAA compliance. In a healthcare AI assistant, any mechanism that automatically transfers context between sessions creates a pathway for protected health information belonging to one patient to surface in a conversation about another. For clinicians juggling dozens of encounters a day, that kind of cross-contamination is a documentation and privacy hazard inappropriate to introduce.
The underlying issue is accuracy. Filtering sensitive details out of a shared memory store would need to work flawlessly every single time, across every specialty, note type, and edge case. Current techniques do not reach that threshold. Until memory systems can demonstrate complete reliability in scrubbing identifiers and preventing patient data from crossing session boundaries, BastionGPT will continue to treat each chat as its own isolated workspace. This is part of why healthcare professionals, from physicians to therapists writing progress notes, trust the platform as a top choice for secure clinical documentation.
That said, we recognize clinicians do not want to retype the same background information every time they start a new session. To solve that without compromising privacy, BastionGPT offers a saved prompt feature. You can store reusable instructions, templates, formatting preferences, specialty-specific guidance, or standing context relevant to particular workflows, and drop them into any new chat with a click. Think of it as a personal library of building blocks for your AI medical scribe or therapy notes assistant, fully under your control and free of patient identifiers.
This approach gives you the efficiency benefits of continuity without the compliance exposure of persistent memory. A psychiatrist can keep a saved prompt for structuring mental health progress notes. An IT administrator can standardize prompts across a clinical team. An educator can store teaching frameworks for case discussions. In each scenario, the user decides exactly what information enters a conversation, and nothing carries over implicitly from prior sessions.
If and when memory technology matures to the point where sensitive information can be filtered with complete certainty, we will revisit the feature. Until then, session isolation combined with saved prompts reflects what a HIPAA compliant AI platform should look like: powerful enough to accelerate clinical work, disciplined enough to keep every patient's information exactly where it belongs.