Patient engagement · Patient access voice AI
Assort Health
Assort Health makes AI voice agents for specialty practices that answer patient calls, book appointments using each practice's scheduling rules, and route complex calls to staff.
Strong fit
- Orthopedic and other specialty groups whose phone scheduling depends on strict provider rules
- Multi-site practices that want AI agents to book, triage, and route calls inside the EHR
- Groups ready to hand most routine calls to an AI agent and track how many it resolves
Weak fit
- Practices that mainly want call analytics and staff coaching
- Small offices with one front desk and low call volume
- Buyers who need a published price list
Bottom line
Assort Health builds AI voice agents that answer and place patient calls for specialty practices, starting with orthopedics. Each deployment loads the practice's own scheduling rules, so its agent books the right visit type with the right provider and hands harder calls to staff. It fits specialty groups with heavy call volume and complex scheduling rules.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Jeffery Liu and Jon Wang founded Assort Health in San Francisco and run it as co-CEOs. Liu was head of product engineering at Athelas and Commure, where he helped lead an AI scribe used by more than 100,000 physicians. Wang published seven papers on healthcare AI at Stanford and was an MD candidate at the University of California, San Francisco. Assort started in orthopedics, where surgeons often see only certain conditions, so its agent has to learn which provider takes which complaint. Its first deployment, with a group in Chicago in late 2023, resolved about 55 percent of calls without a person on day one, and that rate later rose above 95 percent.
Assort has raised more than $222 million. Its $120 million Series C, led by Menlo Ventures in June 2026, valued it at $1.2 billion, less than a year after a Series B led by Lightspeed Venture Partners. Paul Ricci, the founding CEO of Nuance, joined as a board advisor. Revenue grew 20-fold in the 15 months before the Series C, and headcount went from about 15 to nearly 250 in a year. Assort's own AI model, Synapse, learns specialty scheduling patterns from every deployment and generates the edge cases and tests each new practice needs, so a new customer's provider rules do not start from scratch. Customer stories on its site show unanswered calls down 34 percent at Barrington Orthopedic and call abandonment down 75 percent at Peninsula Orthopaedic.
Compare Hyro when a health system wants AI agents across its call center, website, and text messages, Keona Health when nurse triage protocols and a call-center CRM matter most, PatientPrism when the goal is coaching staff from call analytics, Hello Patient when a smaller outpatient group wants the agents run as a managed service, and Parakeet Health when a dermatology group wants pay-for-performance pricing.
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 |
| Hello Patient | 7.2 | 8.4 |
| Parakeet Health | 6.9 | 7.0 |
Pricing
| Item | Detail |
|---|---|
| Model | Custom contract quoted by Assort Health. |
| What usually drives cost | Call volume, the number of specialties and locations, and which workflows the agents handle, such as scheduling, intake, referrals, refills, and payments. |
| What to ask in diligence | The price per call or per resolved call, what happens to cost when calls go to staff, and what implementation and EHR integration cost. |
| Published pricing | No public list price. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Assort Health to function | |
| Written scheduling rules for every provider | The agent can only follow rules it is given. |
| EHR or practice management access | Booking happens inside the scheduling system. |
| Phone routing plan | Decide which calls go to the agent first. |
| Owner for escalated calls | Staff still take what the agent hands off. |
| Baseline call metrics | Hold time and abandonment show change later. |
| What will maximize your value | |
| Start with one specialty or region | Rules are easier to tune in one place. |
| Review resolution rates every week | Resolution rose over time at early customers. |
| Add outbound calls after inbound works | Refills and recalls use the same rules. |
| Deal-breakers | |
| No one can document scheduling rules | |
| No EHR scheduling access | |
| Wants analytics only | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Contract, security review, and EHR connection | 2-6 weeks |
| 2 | First calls live | 1-2 months |
| 3 | More specialties and outbound calls | 3-6 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.