Population health & analytics · Workforce and capacity AI
Vitalize
Vitalize is AI software that helps health systems schedule nurses and other staff, forecast patient demand, and match staffing to bed capacity across the system, connected to EHR and time-and-payroll systems.
Strong fit
- Health systems spending heavily on overtime and agency nurses
- Nurse leaders who build schedules by hand in spreadsheets
- Systems that want staffing and bed planning in one place
Weak fit
- Single small hospitals with simple schedules
- Buyers who want a published price
- Organizations without clean time-and-payroll data
Bottom line
Vitalize automates staff scheduling and matches staffing to patient demand across health systems, and St. Luke's Health reports a 54% cut in premium labor spend in 12 weeks. It suits systems paying heavily for overtime and agency staff. Its results so far come from customers the company cites.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Vitalize is used by nurse leaders, staffing offices, and operations teams at health systems. It automates manual scheduling, forecasts patient demand, and moves staff across units and thousands of beds as needs change, according to its Series A announcement. It connects to EHR and time-and-payroll systems, and the company says it replaces the 10 or more separate tools clinical teams use for staffing, scheduling, and capacity planning.
Vitalize says it manages millions of shifts a week across dozens of health systems and saves clinical leaders more than 2,000 hours a day.
The closest competitors are LeanTaaS and Qventus, which sell capacity and patient flow software, and PerfectServe.
Veeraj Shah and Sanketh Andhavarapu, both University of Maryland graduates, co-founded Vitalize in 2021. It began as a mobile app to reduce burnout among clinicians, according to a 2021 profile, and now sells staffing and capacity software. On October 6, 2026 Vitalize announced a $31 million Series A led by Oak HC/FT, with Norwest, .406 Ventures, Constellation Ventures, Y Combinator, Rock Health Capital, and MemorialCare Innovation Fund. It is based in San Francisco.
Vitalize publishes no price, and its savings figures come from customers it cites.
What customers say
"In just 12 weeks, we saw a 54% reduction in premium labor spend across overtime and agency costs, and we're moving quickly to roll it out across the system." David Pereles, Chief Information Officer, St. Luke’s Health, in the Oak HC/FT announcement.
"Within weeks of deploying Vitalize, our clinical leaders were spending 50% less time on manual staffing and scheduling." Dan Ireland, Chief Nurse Executive, Rochester Regional Health, in the Oak HC/FT announcement.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| LeanTaaS | 7.8 | 7.2 |
| Vitalize | 7.4 | 7.0 |
| PerfectServe | 7.4 | 7.0 |
| Qventus | 7.2 | 6.8 |
Pricing
| Item | Detail |
|---|---|
| Model | Custom quote from Vitalize. |
| What usually drives cost | The number of hospitals, units, and staff scheduled, and whether capacity planning is included. |
| What to ask before you buy | Ask Vitalize for the price per bed or per scheduled employee and which payroll and EHR connections are included. |
| Published pricing | Vitalize does not publish a price list. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Vitalize to function | |
| Nursing and staffing leaders who own schedules | Vitalize changes their day. |
| Time-and-payroll and EHR access | Forecasts and schedules depend on them. |
| Baseline overtime and agency spend | Shows the savings later. |
| What will maximize your value | |
| Start with units that use the most agency staff | Fastest savings. |
| Add capacity planning after scheduling | Matches staff to beds. |
| Deal-breakers | |
| One small hospital | |
| No clean payroll data | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Contract and systems connected | 1-3 months |
| 2 | First units live | 2-4 months |
| 3 | Premium labor savings seen | About 12 weeks after go-live at St. Luke’s |
Leadership
Veeraj ShahCo-founder and CEO- Sanketh AndhavarapuCo-founder
Methodology
| Weight | Factor | What it measures |
|---|---|---|
| 35% | Customer outcomes | Whether buyers get measurable operational or clinical-workflow results after go-live |
| 30% | Product | Capability depth, reliability, and fit for the job the category buys |
| 20% | Implementation | How hard it is to stand up, integrate, train, and stabilize |
| 15% | Pricing clarity | Whether a buyer can model total cost without a mystery quote |
| Label | Meaning |
|---|---|
| Highly recommend | Strong outcomes and product with manageable caveats |
| Recommend | Solid fit for the right buyer; know the tradeoffs |
| Conditional | Only with a specific use case or heavy caveats |
| Not recommended | Avoid for most buyers in this category |
Read our full methodology for how we weight scores and assign recommend labels.