Many hospitals turn to virtual sitting to bring down the cost of one-to-one patient observation. It's a real improvement over stationing a dedicated staff member in every high-risk room. But virtual sitting doesn't eliminate continuous human monitoring — it relocates it. A trained observer still has to watch live video from multiple rooms and decide, in real time, when to step in.
That's the question underneath most searches for an AvaSure alternative: is there a monitoring model that doesn't require someone watching a screen around the clock?
Ambient vision AI is a category of healthcare monitoring technology that uses on-device sensors — such as LiDAR and computer vision — to continuously observe a patient room and automatically flag clinically meaningful events. Unlike virtual sitting, it doesn't rely on a person watching a live video feed to catch a risk in progress; the detection happens in the system itself.
This post compares VirtuSense's VSTOne platform to AvaSure, one of the most established names in virtual sitting, across sensing technology, staffing model, and clinical scope. Every claim about AvaSure is sourced and linked so you can verify it yourself.
The short version: VirtuSense is built on LiDAR-based ambient AI that never produces a viewable image of the patient, and it routes alerts directly into the nursing workflow. AvaSure is built around TeleSitter®, a camera-based virtual sitting product that pairs live video with a trained virtual safety attendant, with AI layered on top to help flag risk. Both are in active use across hospitals today — the sections below cover exactly where and why they differ.
Virtual sitting still requires a trained person to actively watch camera feeds. Ambient AI monitoring is designed to detect risk without a continuous human observer.
AvaSure's TeleSitter model connects cameras in patient rooms to a virtual safety attendant (VSA), who monitors multiple rooms at once from a central location and intervenes over two-way audio when something looks unsafe. AvaSure has added computer vision AI on top of this model to help flag high-risk scenarios, per its own site — but the core workflow still depends on a person actively watching the feed.
VSTOne takes a different approach. It's built as an AI-native system from the start: LiDAR and computer vision sensors detect risk events directly, and alerts route into the existing nursing workflow rather than a centrally staffed virtual command center. That doesn't mean no one ever reviews an alert — it means the system doesn't require continuous human observation of a live feed to do its core job.
For a hospital evaluating either option, the practical question to ask any vendor is simple: how many staffed hours does this require, and where does that cost live in the budget?
VSTOne monitors for both fall risk and pressure injury risk on one platform. AvaSure's public materials focus on fall, self-harm, and elopement prevention through continuous observation.
That distinction matters more than it used to. CMS's Hospital Harm – Pressure Injury measure now requires hospitals to report pressure injury data drawn directly from the electronic health record, adding pressure on facilities that don't already have a technology-driven way to catch pressure injury risk early.
AvaSure has been expanding its own scope. It acquired Nurse Disrupted, a virtual nursing platform, in March 2025 to move beyond virtual sitting into virtual nursing. Pressure injury detection specifically, though, isn't presented as a headline capability on AvaSure's site as of this writing. A hospital trying to solve fall prevention and pressure injury reporting at the same time is choosing between one platform that covers both, or coordinating two separate point solutions.
Froedtert ThedaCare Health has reported a 4.5x return on investment from its VSTOne deployment, driven by fewer falls and reduced reliance on one-to-one sitter staffing. Emory Healthcare, a 5.5x ROI customer, hosted a VSTOne breakout session at the 2026 AONL conference to walk other health systems through its results.
Both examples point to the same theme: hospitals adopting VSTOne are typically solving fall prevention and staffing costs together, not as separate initiatives — and pressure injury coverage comes along on the same platform rather than requiring a second tool.
What is a good alternative to AvaSure? VirtuSense's VSTOne is an ambient AI alternative to AvaSure's TeleSitter. Instead of pairing cameras with a virtual safety attendant, VSTOne uses LiDAR-based sensors to detect fall and pressure injury risk directly, without requiring continuous human observation of a video feed.
How does VirtuSense compare to AvaSure's TeleSitter? TeleSitter is a camera-based virtual sitting product built around a trained virtual safety attendant watching live feeds, with AI added to help flag risk. VSTOne is built as an AI-native ambient monitoring platform from the start, using LiDAR instead of cameras and routing alerts directly into nursing workflow.
What's the difference between virtual sitting and ambient AI monitoring? Virtual sitting relies on a person actively watching camera feeds from multiple rooms and intervening in real time. Ambient AI monitoring uses on-device sensors to detect risk automatically, reducing the need for continuous human observation of a live video stream.
Can ambient AI monitoring reduce reliance on virtual sitters entirely? In many cases, yes, though it depends on patient acuity. Ambient AI platforms like VSTOne can reduce the number of patients who need continuous human observation, though the highest-acuity patients may still warrant additional layers of monitoring alongside the technology.
The choice between AvaSure and VirtuSense often comes down to one question: do you want to make virtual sitting more efficient, or remove the continuous-observation requirement altogether? AvaSure has built a mature, widely adopted virtual sitting platform and is actively expanding into virtual nursing. VirtuSense's VSTOne was built from the ground up as an autonomous ambient AI system that also covers pressure injury risk on the same platform.
See how VSTOne compares for your hospital — Request a Demo.
For more on the numbers behind ambient AI adoption, read our fall prevention ROI research.