Healthcare technology company LeanTaaS is expanding its iQueue platform beyond traditional hospital operations and capacity management into ambient intelligence, using computer vision to monitor patient rooms and turn signals into actions.
As part of this strategy, the company plans to launch iQueue for Virtual Care, using AI-powered patient-room monitoring to detect events such as fall risks, patient movement and other environmental signals, then route those insights into operational workflow.
LeanTaaS says ambient intelligence gives iQueue visibility into patient activity that electronic health records and other systems may miss or capture too late. The use of ambient intelligence extends virtual care beyond remote visits by monitoring patients between encounters, flagging events such as when a patient tries to stand without assistance or hasn’t gotten out of bed for hours, according to the company. The platform can then direct that information to care teams so they can prioritize and coordinate a response.
The system is designed to turn events like an attempted bed exit into prioritized tasks rather than additional alarms. AI monitors rooms and surfaces events to a virtual observation team, which can assess the situation, remotely engage the patient or escalate to bedside staff when needed, Mohan Giridharadas, founder and CEO of LeanTaaS, told Fierce Healthcare in an interview.
Urgency and routing are based on the patient’s context and the health system’s established protocols. Human clinicians remain responsible for clinical decisions, Giridharadas said, while iQueue provides context, prioritizes events and helps route information to the appropriate care team.
The company’s software and services are being used by nearly 200 health systems in more than 1,200 hospitals, centers and clinics in the U.S.
To accelerate this strategy, LeanTaaS acquired LookDeep Health, its second acquisition in about two months following its purchase of care transition platform Aidin. The deal brings computer vision technology, an open platform approach and virtual care deployment experience into LeanTaaS.
LeanTaaS provided Fierce Healthcare with a first look at the acquisition news. Financial details of the deal were not disclosed.
Giridharadas said the company is building the “central nervous system of the hospital,” and computer vision will be a key data source for this broader hospital operations platform.
The vision is to create a closed-loop system that can sense conditions, interpret their operational significance, coordinate responses and learn from interventions and outcomes.
“It is a move beyond retrospective dashboards toward continuous operational awareness and execution,” Giridharadas told Fierce Healthcare.
“A great operational brain needs more signal, so it can decide faster and decide better. Health systems generate hundreds of thousands of data points each day – but the vast majority of them are discarded after they have served their immediate purpose. The next frontier is building a robust and scalable approach to capture high-value signals from the physical care environment that may never reach the EHR, or may reach it too late to be useful. That includes whether a patient is alone, trying to stand or hasn’t been out of bed in days, when a nurse was last in the room, and whether a room is ready for the next patient, from compatible cameras and in-room devices, and potentially other device-generated or workflow signals,” Giridharadas said.
“The test is whether a signal is sufficiently accurate and timely, and whether it can be converted into a clear action for the care team. We intend to continuously expand the sources and uses of data from the entire end-to-end patient journey,” he added.
Narinder Singh, former CEO and co-founder of LookDeep who joined LeanTaaS as senior vice president of ambient intelligence, said the technology can support stretched care teams by monitoring patients when clinicians can’t be present. “Nurses and physicians cannot be in every room at every moment, and too often technology has added to their work instead of taking it away. Ambient intelligence keeps watch when they can’t be there, so staff finally feel the technology works for them, not the other way around,” he said in a statement.
LeanTaaS chose to acquire LookDeep rather than partner with a computer vision or virtual care company to integrate ambient intelligence technology deeply into the iQueue platform, executives said.
“We are building the central nervous system of healthcare operations—a highly functional nervous system must have audio and video sensory capabilities in order to be effective. This is why we needed to acquire the capability rather than rely on an arms-length partnership. We already had the intelligence that drives the car, 15 years of it. What we wanted was the best perception ever built for hospitals. Nobody confuses the cameras with the car, but there is no self-driving car without them,” Giridharadas said.
LookDeep brings three capabilities to LeanTaaS’ platform: peer-reviewed vision AI, an open technology platform that works with hospitals’ existing infrastructure and experience deploying virtual care. Its approach also focuses on using AI to ease care team capacity constraints rather than adding to clinicians’ workloads.
Health systems can build on compatible cameras and in-room devices already in place or deploy supported hardware as needed. This open approach helps preserve existing investments while creating a foundation for new capabilities, according to the company.
“The acquisition gives us the opportunity to make ambient intelligence a native part of iQueue and extend the technology across our broader portfolio. We also share a conviction that in something as complex as a hospital, before you can be smart, you must be open. Vendor-specific camera silos will not last as health systems demand greater interoperability,” Giridharadas said, noting that a camera alone “does not generate an ROI.” “The value comes when what it sees changes what happens next—earlier, with the right person acting. Nobody expects the barcode scanner to redefine the supply chain, yet no supply chain runs well without one.”
The new virtual care offering includes three services: virtual observation for AI-assisted patient monitoring and escalation, virtual nursing to support admissions, rounding, patient education and discharge preparation and virtual medicine to connect patients with remote physicians and specialists.
These offerings build on LookDeep’s experience deploying the technology in health systems. Across different deployments and operating models, reported results include a more than 70% reduction in fall rates, twice as much nursing contact, an 80% reduction in medication errors and threefold cost savings compared with traditional virtual sitting solutions, according to the companies.
Beyond virtual care, LeanTaaS plans to incorporate ambient intelligence into additional iQueue products and workflows to support capacity, patient flow and care coordination.
“We will bring the vision capability into all of our products beginning with inpatient flow and operating rooms and then moving on to infusion centers and other areas of the hospital,” Giridharadas said.
The company aims to find areas in hospital patient care where important signals are either missed or received too late by current systems. “We will prioritize use cases where the signal is reliable, the response is well defined and the impact can be measured,” he noted.
LeanTaaS aims to position iQueue as an intelligent orchestration layer that combines data from EHRs, clinical AI and ambient technologies and translates those signals into prioritized, coordinated action for care teams. “The value is in closing the gap between knowing and doing. Hospitals do not need another disconnected alert or dashboard. They need intelligence translated into coordinated execution, with clinicians and operational leaders remaining in control,” Giridharadas said.
As adoption of AI in healthcare grows, LeanTaaS says its competitive advantage comes from a proprietary knowledge base built from more than 15 years of health system deployments. “We have accumulated an enormous knowledge base of thousands of corner cases that make operational improvement and change management difficult to accomplish. We have built a multi-layered knowledge architecture of tens of thousands of ‘knowledge nodes’ that enables us to deliver an enterprise-grade AI capability where the data and knowledge is tightly curated to the unique needs of each site at each customer rather than relying on generic recommendations from foundation LLM models,” he said.