Population health & analytics · Value-based care clinical AI
Navina
Navina makes clinical AI for value-based primary care that summarizes each patient's chart, claims, and outside records on one page before the visit, with suggested diagnoses, care gaps, and risk adjustment documentation.
Strong fit
- Primary care groups in value-based contracts that want a one-page summary of each patient before the visit
- Medicare Advantage and ACO groups that need accurate risk adjustment documentation
- Organizations that want clinicians, not only coders, to open Navina every week
Weak fit
- Payers that want claims analytics without a clinician-facing tool
- Small fee-for-service practices with no risk contracts
- Buyers who need a published price list
Bottom line
Navina makes clinical AI for primary care groups in value-based care. It reads the chart, claims, and outside documents and gives the clinician a one-page summary with suggested diagnoses, care gaps, and risk adjustment codes before each visit. It fits groups in risk contracts that want better documentation from their own clinicians.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Ronen Lavi and Shay Perera founded Navina in 2018 after years in Israeli military intelligence, where Lavi had founded and led its artificial intelligence lab. They looked at energy and agriculture before choosing healthcare, and started with small and mid-size primary care clinics. Navina reads the EHR, claims, labs, hospital records, and scanned documents and turns them into its Patient Portrait, a one-page summary the clinician opens before a visit. It suggests diagnoses that may be missing, open care gaps, and the documentation risk adjustment needs, and the clinician accepts or rejects each one.
Navina raised a $55 million Series C in March 2025 led by Goldman Sachs Alternatives, bringing total funding to $100 million. More than 10,000 clinicians at about 1,300 clinics use it, and customers include agilon health, InnovaCare, Millennium Physician Group, and Privia Health. It won Best in KLAS in 2025 for clinician digital workflow, and 86 percent of its users open it every week.
Compare Arcadia or Innovaccer when an organization wants a full data platform with analytics across its population, Persivia when care management and quality reporting matter as much as the visit, Azara Healthcare when the buyer is a community health center, Lightbeam Health Solutions when an ACO wants care management services, and Elligint Health when the buyer is a health plan.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Navina | 7.9 | 7.4 |
| Azara Healthcare | 7.6 | 7.2 |
| Persivia | 7.4 | 7.1 |
| Innovaccer | 7.4 | 7.0 |
| Arcadia | 7.0 | 6.7 |
| Elligint Health | 6.9 | 6.6 |
| Lightbeam Health Solutions | 6.8 | 6.5 |
Pricing
| Item | Detail |
|---|---|
| Model | Custom contract quoted by Navina. |
| What usually drives cost | Number of clinicians or attributed patients, data sources to connect, and which modules are used, such as risk adjustment, quality, and pre-visit summaries. |
| What to ask in diligence | The price per clinician or per patient, data integration fees, and whether pricing ties to measured results. |
| Published pricing | No public list price. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Navina to function | |
| Value-based care or quality lead | Owns risk and quality goals. |
| EHR and claims data access | The summary depends on both. |
| Clinician champions | Use spreads through peers. |
| Coding and compliance review | Suggested diagnoses need oversight. |
| Baseline risk scores and gap rates | Shows change later. |
| What will maximize your value | |
| Roll out by clinic, not all at once | Lets champions help peers. |
| Review accepted and rejected suggestions | Keeps documentation defensible. |
| Add hospital and outside records | More data finds more gaps. |
| Deal-breakers | |
| No value-based contracts | |
| No claims data access | |
| Clinicians will not open a pre-visit tool | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Contract and data connection | 1-3 months |
| 2 | First clinics live | 2-4 months |
| 3 | All clinics and more data sources | 6-12 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.