Sacra estimates Viz.ai hit $40 million in revenue in 2023, up approximately 100% year-over-year from around $23 million in 2022. The company expects revenue to increase to roughly $65M in 2024.

Viz.ai has seen rapid adoption of its AI-powered care coordination platform, now used in over 1,000 U.S. hospitals covering nearly two-thirds of the population. Annual recurring revenue (ARR), a key metric for its subscription-based model, reached $12 million in 2020 and is projected to hit $100 million by 2024.

Viz.ai was founded in 2016 by Dr. Chris Mansi, a neurosurgeon, and David Golan, a machine learning postdoc. The two met at Stanford and bonded over the lack of data-driven decision making in medicine. Their initial focus was using AI to improve stroke care by reducing time to treatment.

Viz.ai found product-market fit with primary stroke centers, using AI to rapidly detect large vessel occlusion (LVO) strokes from CT scans and alert the entire care team within 7 minutes, down from 58 minutes prior. This enabled faster patient transfer to comprehensive stroke centers for thrombectomy, with Viz.ai increasing surgery volumes 50-60% at large hubs. Medicare created a new reimbursement pathway for Viz.ai's software, establishing it as a new therapeutic class.

The Viz.ai platform ingests CT scans, uses AI algorithms to identify LVOs and other critical conditions, and immediately alerts the relevant care team members on their mobile devices. This allows for rapid triage, improved communication and coordination, and faster treatment times. The platform has expanded beyond stroke to cover other time-sensitive conditions like aortic disease and pulmonary embolism.

Key features of the Viz.ai platform include:

- AI-powered identification of LVOs and other critical conditions

- Mobile alerts and communication for the entire care team

- Seamless integration with hospital workflows and systems

- Expansion to multiple specialties beyond neurology

- Demonstrated improvement in patient outcomes and treatment times

Viz.ai is now deployed in over 1,000 hospitals in the U.S. and Europe. By building an effective AI-powered platform that integrates smoothly into clinical workflows, Viz.ai has established itself as a leader in the application of AI to improve patient outcomes and streamline care delivery for time-critical conditions.

Viz.ai is a subscription SaaS company that provides AI-powered disease detection and care coordination solutions to hospitals and health systems.

The company's core offering is a suite of FDA-approved algorithms that analyze medical images, such as CT scans, to identify potential issues like strokes, pulmonary embolisms, and aortic dissections. When the AI detects a concerning finding, it immediately alerts the appropriate specialists via a mobile app, enabling faster diagnosis and treatment.

Viz.ai generates revenue through a subscription model, charging hospitals an annual fee based on the number of algorithms they use and the size of the population they serve.

This pricing structure aligns with the value Viz.ai delivers, as its platform helps hospitals improve patient outcomes, reduce costs, and optimize resource utilization. By catching critical issues early and facilitating rapid care coordination, Viz.ai enables hospitals to treat more patients effectively and efficiently.

A key aspect of Viz.ai's business model is its focus on integrating seamlessly into existing clinical workflows.

The company's mobile app serves as a centralized communication platform, allowing specialists to collaborate, share images, and make treatment decisions quickly. This workflow integration not only enhances adoption but also positions Viz.ai as a valuable tool for driving operational improvements and reducing variability in care delivery.

As Viz.ai expands its suite of algorithms to cover more disease states, it creates opportunities for upselling and cross-selling to existing customers. The company currently has 12 FDA-approved algorithms for diseases including stroke, hypertrophic cardiomyopathy, and pulmonary embolism.

Viz.ai's land-and-expand strategy involves initially targeting high-impact areas like stroke care, then leveraging its proven value to secure broader adoption across the enterprise.

In addition to its hospital partnerships, Viz.ai has begun working with pharmaceutical and medical device companies.

As of January 2024, the company has strategic partnerships with 7 of the top 30 global life science companies. These collaborations aim to streamline product launches and accelerate patient access to new therapies.

Viz.ai competes with other companies providing AI-powered disease detection and care coordination solutions, as well as traditional medical imaging and workflow software providers. The competitive landscape can be segmented into AI diagnostic startups, established medical technology companies, and workflow software vendors.

Viz.ai faces competition from other AI-driven medical imaging analysis startups such as Aidoc, Qure.ai, and RapidAI. These companies also offer algorithms to detect specific conditions like stroke, pulmonary embolism, and aortic disease from CT scans.

Aidoc, a key competitor, has received 23 FDA clearances for its AI-enabled imaging devices as of May 2024. In June 2022, Aidoc raised $110 million in a Series D funding round, bringing its total funding to $250 million.

RapidAI, another competitor, has received FDA clearance for a product that identifies potential cases of central pulmonary embolism and alerts providers.

Large incumbent medical imaging companies like GE Healthcare, Siemens Healthineers, and Philips are investing in AI capabilities to enhance their existing offerings. These companies have deep relationships with hospitals and the scale to bundle AI tools with their scanner hardware.

As of May 2024, GE HealthCare leads with 72 AI-enabled devices cleared or authorized by the FDA. Siemens Healthineers follows with 64 approvals, Canon with 28, and Philips with 27.

In March 2024, Philips launched a partnership with Synthetic MR for AI-powered diagnostic decision support in neurological conditions. They also introduced the Zenition 90, a new motorized, mobile C-arm imaging system.

Siemens Healthineers announced FDA clearance for its TrueBeam and Edge radiotherapy systems with AI-powered HyperSight imaging programs.

While Viz.ai's AI is a key differentiator, it also competes with companies providing communication and workflow solutions for stroke care and other time-critical conditions. Companies like Pulsara offer mobile-based care coordination for stroke teams.

Viz.ai stands out by combining its AI diagnostics with streamlined communication, enabling faster triage and treatment decisions without toggling between systems. Viz.ai's platform becomes the place where specialists "do their work", spending more time in Viz than in traditional PACS systems. This integration of AI into clinical workflows is a key advantage.

Viz.ai has tailwinds from the growing adoption of AI in healthcare and the increasing focus on improving stroke care. The company has the opportunity to expand into adjacent markets like other time-sensitive medical conditions and become a comprehensive care coordination platform.

Viz.ai's success in using AI to quickly identify Large Vessel Occlusion (LVO) strokes demonstrates the potential for AI to revolutionize diagnostic processes. The company can leverage its expertise to develop algorithms for other time-sensitive conditions such as heart attacks, pulmonary embolisms, and sepsis. By expanding its diagnostic capabilities, Viz.ai can capture a larger share of the healthcare AI market, which is expected to reach $45.2 billion by 2026.

Moreover, Viz.ai's platform can be extended to support clinical decision-making in other specialties like oncology, where early detection and rapid treatment initiation are crucial. The company's ability to integrate AI seamlessly into clinical workflows positions it well to become a leading provider of intelligent diagnostic solutions across multiple disease areas.

Viz.ai's success in streamlining stroke care coordination highlights the potential for the company to become a comprehensive care coordination platform. By connecting healthcare providers, automating workflows, and facilitating real-time collaboration, Viz.ai can address the broader challenges of care fragmentation and communication breakdowns in healthcare.

The company can expand its platform to support care coordination for chronic conditions, post-acute care, and population health management. This expansion would allow Viz.ai to tap into the growing market for care coordination software, which is expected to reach $3.2 billion by 2025.

Furthermore, Viz.ai can leverage its partnerships with leading healthcare organizations to develop new solutions that address the unique care coordination needs of different healthcare settings, such as primary care, specialty care, and home health. By becoming a comprehensive care coordination platform, Viz.ai can position itself as an essential tool for healthcare organizations looking to improve patient outcomes, reduce costs, and enhance operational efficiency.

1. Reliance on hospital adoption and reimbursement: Viz.ai's business model depends on hospitals adopting its software and being able to get reimbursed for it. While Viz.ai has made good progress with over 1,000 hospitals signed up, it will need to continue driving adoption to sustain its growth trajectory. Changes to reimbursement policies, especially the New Technology Add-on Payment (NTAP) program, could significantly impact Viz.ai's revenue if hospitals are no longer able to get paid for using the software. Mitigating factors include Viz.ai's strong clinical evidence of improved patient outcomes and cost savings.

2. Expanding beyond stroke: Much of Viz.ai's traction and reimbursement to date has been in stroke detection and triage. To reach its full potential, it will need to successfully expand to other disease areas like aortic and pulmonary conditions. This will require getting new algorithms approved, establishing their clinical utility, and potentially navigating different reimbursement dynamics. Stumbles here could slow Viz.ai's growth. 3. Competition from other modalities: Viz.ai's AI primarily analyzes CT scans today. But other emerging technologies like portable ultrasound, digital biomarkers from wearables, or blood-based diagnostics could potentially leapfrog CTs for rapid triage of conditions like stroke. This might allow competitors to undermine Viz.ai's value proposition of saving critical minutes. Viz.ai will need to continue innovating to stay ahead of alternative diagnostic modalities.