Patient engagement · Patient access voice AI
Hyro
Hyro makes AI agents for health systems that answer patient calls, web chats, and text messages, handling scheduling, physician search, and routine requests.
Strong fit
- Health systems that want AI agents across the call center, website, text messages, and apps
- Large call centers handling scheduling, physician search, and routine patient requests
- Health systems that want a vendor with long-running deployments at other health systems
Weak fit
- Single-specialty practices that need deep specialty scheduling rules
- Practices that want a vendor to run the agents for them as a managed service
- Buyers who need a published price list
Bottom line
Hyro, based in New York, makes AI agents that answer patient calls, web chats, and text messages for health systems. Its agents handle scheduling, physician search, and routine requests, and pull answers from each organization's own data. It fits large health systems that want one AI agent platform across many channels.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Israel Krush and Rom Cohen started Hyro in 2018 after meeting at Cornell Tech in New York, where Krush was earning an MBA and Cohen a master's degree in computer science. Uri Valevski, an expert in how computers understand language, joined as the third co-founder.
Hyro builds a map of each organization's existing data, such as its physician directory. That lets its agents answer questions without anyone scripting every conversation in advance.
Early in the COVID-19 pandemic, Hyro gave health networks a chatbot that answered questions about the virus and ran symptom self-assessments.
Hyro raised $45 million in October 2025, led by Healthier Capital, with Norwest, Define Ventures, Bon Secours Mercy Health, and ServiceNow Ventures. The round doubled its valuation and brought total funding to $95 million.
In 2024 its agents saved more than 50 million agent minutes.
Its clients include Intermountain Health, Baptist Health, and Hackensack Meridian Health. Bon Secours Mercy Health has worked with Hyro for more than five years.
Assort Health fits a specialty group that needs agents trained on strict provider scheduling rules. Keona Health fits when nurse triage is the core of the phone operation.
PatientPrism fits when the goal is coaching staff using call data. Hello Patient fits an outpatient group that wants a managed service, and Parakeet Health fits buyers who want to pay based on results.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Assort Health | 8.2 | 7.6 |
| Hyro | 7.9 | 6.4 |
| PatientPrism | 7.7 | 7.1 |
| Keona Health | 7.4 | 7.7 |
| Infermedica | 7.4 | 7.1 |
| Hello Patient | 7.2 | 8.4 |
| Parakeet Health | 6.9 | 7.0 |
Pricing
| Item | Detail |
|---|---|
| Model | A custom contract quoted by Hyro. |
| What usually drives cost | Which channels you use (phone, web, text, app), call and conversation volume, and the number of tasks and system connections. |
| What to ask before you buy | The price per conversation or per resolved request, fees for adding channels, and the cost of connecting systems and setup. |
| Published pricing | Hyro does not publish a price list. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Hyro to function | |
| A call center leader who owns the rollout | Agents change call routing and staffing. |
| A clean physician directory and location data | The agent answers from these sources. |
| A connection to the phone system and scheduling | Booking needs access to the schedule. |
| A list of tasks to automate first | Scheduling, refills, and FAQs differ in risk. |
| A security and compliance review | Patient conversations leave the network. |
| What will maximize your value | |
| Start with the highest-volume call type | This shows savings fastest. |
| Use the same agent on web and text | One knowledge base serves every channel. |
| Review handoffs to staff each month | This finds gaps in what the agent knows. |
| Deal-breakers | |
| No one in the call center owns it | |
| Your directory data is out of date | |
| You need specialty scheduling rules first | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Contract, security review, and data connection | 4-8 weeks |
| 2 | First channel live | 2-3 months |
| 3 | More channels and tasks | 3-9 months |
Leadership
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.