Abridge Assistant Is the AI Assistant for Healthcare
The next era of clinical software won’t be clicked through. It’ll be talked to.
Abridge led the shift to ambient AI in clinical documentation, centering the patient conversation and cutting the after-hours charting clinicians used to take home. Yet, the rest of the day is still spent on tabs, clicks, and navigating fields. Clinicians should be able to do what everyone else can now do with consumer chatbots and agents: say what they need and get it.
That’s why we built Abridge Assistant, the AI assistant for healthcare. Assistant is built from the same AI research and clinician-led evaluation that brought Abridge’s ambient notes to more than 300 enterprise health systems. Clinicians can ask questions and delegate tasks to Assistant in their own words. As of our September release, every clinician at every Abridge health system has access to Assistant, whether or not they use Abridge for documentation.
Ask Assistant about a patient, and it pulls together the relevant details from across that patient’s chart, with each source cited. Clinical questions come back with current guidelines, and calculators open with chart values already filled in. Assistant also personalizes the note and drafts artifacts such as referrals and handoffs for the clinician to review. All of it runs inside the security and governance review framework of the health system.
Below, Matt Troup, a PA-C and Abridge Clinical Strategy Principal, explains what clinicians need from an AI assistant. Janie Lee, Abridge VP of Product, explains what it took to build it.
What Clinicians Need From Their AI Assistant: Matt Troup
In hospital medicine, questions often come at inopportune times: walking out of a room, halfway through a note, overnight when a lab comes back. The tasks pile up right behind them, and each one means more time clicking through the chart before the shift ends.
Most of the standalone tools I’ve used share the same problem, regardless of how much they tout AI. They know a lot of medicine, but they don’t know my patient. A response is only as specific as the data preceding it, so I end up doing the prompting myself: retyping comorbidities, current meds, and what we tried last admission, then filtering out whatever doesn’t apply. These tools rarely show how they got to a response, leaving me uncertain how they generate information or where it’s pulled from.
The chart has the opposite problem. It holds every detail collected about the patient, sometimes years of notes, results, and outside records, but I have to piece the story together myself, and it’s easy to miss something. Add the documentation that follows, and a lot of my time is wasted hunting for information and clicking through screens to act on it, and there’s no guarantee that I will find everything I need in the time I have.
Health systems have their own requirements. Some of the tools clinicians reach for have not been reviewed and integrated by their organizations, which creates its own set of problems. And institutional knowledge, like clinical pathways, often lives in a policy library that too few people consult.
When we started building Assistant, this was my wish list:
- It knows the patient: Responses should reflect the chart and the conversation, not just general knowledge.
- It’s where the work happens: No new tab, no copy and paste, no starting over.
- I stay in charge: It does the digging and the first draft but signing off is up to me.
- It shows the work: It cites which parts of the chart it pulled and which sources it checked, so I can follow the reasoning before I act on it.
- My health system stands behind it: It has to clear security and governance review and be fully integrated into the technology I’m already using.
How We Built Abridge Assistant: Janie Lee
We built Assistant for the clinicians at Abridge like Matt and clinicians who work at every one of our partner health systems—for those who are stuck between two eras of software. They deserve better than a broken workflow of legacy software built around a thousand clicks, with newer AI tools that fall short layered on top. Assistant is built to close both gaps, working from the patient’s chart and arriving via a simple chat or voice interface, backed by robust and evaluated intelligence.
Input from clinicians and health systems shaped our key development decisions:
- Start with the context. Assistant draws on the chart, the conversation, and the evidence clinicians already trust, so each response is shaped to the patient in front of them. Context includes a health system’s own clinical pathways, so responses further reflect how care is delivered in that organization.
- Keep it simple, wherever clinicians work. The Assistant interface is consistent inside the EHR and on the clinician’s phone, and it stays simple as capabilities grow. The clinician orchestrates, and Assistant carries the context from one step to the next. Ask what changed since a patient’s last admission, for example, and the response can become a draft handoff in the same thread.
- Show the work. A request like “compare treatments for this patient” sets off a chain of work behind the scenes, from pulling the right context to checking that the response is complete. Assistant shows those steps as they happen, so the clinician can see the reasoning and which sources are referenced as a response is compiled.
- Evaluate continuously. We evaluate Assistant with human and LLM judges, using clinician-built rubrics for clinical quality and safety, before and after a capability ships. Testing also includes a fresh review of existing PHI protections, so patient data stays under the same controls across Abridge.
Assistant’s simplicity hides most of the effort behind it. A lot of this work was in progress before Assistant existed: Abridge was already connected to multiple EHRs and embedded in the clinical workflow, with security, compliance, and AI governance built in from day one. Few products start with that foundation, and Assistant was built on it. Because clinicians can open Assistant inside Abridge, under approvals their health systems have already granted, it’s been adopted at scale already.
How Clinicians Use Assistant in Practice: Matt Troup
Take a typical morning in the hospital. Before rounds, Assistant shows me what has changed for each patient on my list, so I’m not starting from scratch.
For a patient I’m meeting for the first time, using only my voice, I ask what happened at their last admission. The first response from Assistant surfaces key details , which means my follow-up question is more precise. I might ask how the patient’s kidney function affects an antibiotic choice. The response brings the evidence together with this patient’s history, with guidelines cited and the health system’s own pathway included. Assistant can then open a calculator with chart values already filled in for me to check. When care moves to another team, I can ask Assistant to turn what we’ve just worked through into a draft handoff, then review and edit it.
That’s what we mean by orchestrating the workflow instead of clicking through it. I decide what I need from the past, combine it with what’s happening now, and choose the next action. Assistant does the searching and the first draft. I make the clinical judgments.
Unlike the standalone apps I described before, I can follow the clinical question through to the work it creates, rather than rebuilding the context each time I move from sorting out what matters from the chart, to considering a decision, and, finally, to communicating a plan. The setting may change—a hospital ward, a clinic, an emergency department—but the need is familiar. We need to understand the patient, decide what comes next, and make sure the plan reaches the people who depend on it.
Better-informed decisions flow into the documentation and into how we talk with the patient. This is why the ambition has to be bigger than fewer clicks. We’re building toward a more connected way of working, where the effort that goes into understanding a patient carries forward into the decisions, documentation, and conversations that follow.
The best clinicians I’ve worked with weren’t simply the ones who knew the most facts. They were the ones who knew how to apply what they knew to the person in front of them. Abridge Assistant is designed to support that work: less effort piecing the story together, more attention to the person living it.
Where We Are Taking Assistant and What This Means for the Future of Care: Janie Lee
Near term, we’re focused on taking on more of the clinical and clerical work clinicians have asked us to offload. We partner closely with clinicians at our 300+ health systems and are always working with them on improving Assistant’s capabilities.
Longer term, we want Assistant to stay with clinicians across devices, and to work across systems. A clinician’s work can span multiple EHRs and the systems that payers and life sciences organizations manage. Assistant will help clinicians across those boundaries.
Our goal is for clinicians to spend less time on tasks and more on what they’re trying to accomplish for the patient. Getting a patient the right outcome, whether that’s a medication or a spot in a clinical trial, takes front office and back office work from clinicians, nurses, payers, and life sciences. Assistant is how we plan to move that coordination into the background, while the experience stays simple for clinicians.