Clinical systems · Ambient documentation
Nabla
Nabla is an ambient clinical documentation assistant for ambulatory and specialty groups. It drafts notes from the visit and can support EHR write-back when the integration is scoped. Clinicians still review every note; it is not hands-off charting.
Strong fit
- Outpatient and specialty groups trying AI-drafted notes, with a plan for sending notes back to the EHR
- Teams comparing AI note vendors on how much clinicians edit, not on polished demos
- Groups with a clinical informatics owner to lead expansion into more specialties
Weak fit
- Buyers expecting AI notes that no clinician reviews
- Clinics that mainly need documentation that works offline
- Health systems that will only consider AI note tools built into Epic
Bottom line
Nabla is worth considering for medical groups that want AI-drafted notes and will run honest pilots. It suits groups with a clinical informatics owner who sets review rules. Groups whose IT team will only approve an Epic-embedded ambient tool from another vendor should look elsewhere.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Nabla makes AI that listens to visits and drafts clinical notes. It is for groups that want AI drafts in the note without building a full program from scratch.
Its product depth matches other AI note tools, though buyers focused on Epic often start with Abridge.
Sales talks often center on specialty models and assistant features. Those matter only when a chief medical information officer or informatics owner sets review rules and pauses expansion when quality slips.
Results depend on which specialties it covers and whether edit rates stay low after the first month.
Ask the same questions as for peers: how much clinicians edit by specialty, how the note gets back to the EHR, and whether clinicians still rewrite the note after the visit.
Setup needs IT and clinical owners for EHR write-back and the specialty rollout. Pricing is less clear than at AI note tools for small practices.
Nabla is a weaker fit when leaders expect no review at all, or when IT will only approve an AI note tool built into Epic from another vendor.
Among the AI note tools we review, it scores near Ambience and below Freed, which is geared to small practices.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Abridge | 8.4 | 7.8 |
| Freed | 8.0 | 7.6 |
| Suki | 7.8 | 7.6 |
| Heidi Health | 7.7 | 8.0 |
| Ambience | 7.6 | 7.3 |
| Nabla | 7.6 | 7.2 |
| Eleos Health | 7.4 | 7.0 |
| DeepScribe | 7.3 | 7.0 |
| Tali AI | 6.8 | 7.2 |
Pricing
| Item | Detail |
|---|---|
| Model | Contracts for large or mid-sized groups, usually per clinician or per visit. |
| What usually drives cost | EHR connection, adding specialties, and support for staff changes, on top of license fees. |
| What to ask before you buy | The total cost for your number of clinicians, with specialty pilots you must pass before expanding. |
| Published pricing | Nabla does not publish prices. Expect a custom quote, and confirm the total cost at your volume. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Nabla to function | |
| Epic or another supported EHR, with a plan for sending notes back to it | Drafts outside the chart turn into rework. |
| Support from the chief medical information officer or clinical informatics team | Adding specialties needs a clinical owner for review rules. |
| IT time for devices, single sign-on, and EHR setup | Connection work stalls behind other EHR projects. |
| Clinicians willing to review AI drafts every visit | Expecting no review breaks AI note programs. |
| A pilot in a few specialties before rolling out everywhere | Rolling out every specialty at once hides quality gaps. |
| What will maximize your value | |
| Track note edits and after-hours charting by specialty | Track rework in real use, not minutes saved in a demo. |
| Approval from health information management and compliance on recording rules | Workflows without approval get pulled after go-live. |
| Specialty champions who coach peers on when to rewrite and when to accept | Coaching from peers decides adoption. |
| Network and microphone standards for exam rooms | Bad audio looks like the AI failing. |
| Willingness to pause the rollout while clinicians are still editing heavily | Forcing expansion teaches distrust. |
| Deal-breakers | |
| Your EHR is not supported, or sending notes back to it has no date. | |
| Leaders expect AI notes without clinician review. | |
| No informatics owner will run specialty pilots and edit-rate targets. | |
| IT cannot make room for the setup work in the next two quarters. | |
| You mainly need clinic workflows that work offline. | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | From signing to kickoff | 2-6 weeks for security review, lining up EHR contacts, and choosing a pilot specialty |
| 2 | From kickoff to first use | 8-16 weeks for a pilot in one specialty on a supported EHR |
| 3 | From first use to steady results | 3-6 months of cutting down how often clinicians edit the notes before adding more specialties |
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.