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Healthcare · head to head

Annalise.ai vs Rad AI

Annalise.ai logo

Annalise.ai

Healthcare

Multi-finding chest X-ray and head CT triage AI with FDA clearance on named findings, not on the whole model

From
On request
Rated
-
Full reviewWebsite
Rad AI logo

Rad AI

Healthcare

Generative reporting and follow-up tracking for radiology, positioned outside the diagnostic device boundary

From
On request
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Annalise.ai the United States cleared indication covers roughly ten findings for triage and notification, far fewer than the model reports, so a buyer who evaluates the full multi-finding output and then contracts in the United States gets a much narrower cleared use.; Rad AI the products are not FDA cleared devices and are not intended to be, so any claim that Rad AI improves diagnostic accuracy is unsupported; what has been measured is reporting speed and follow-up completion, not detection.
  • They diverge on capability: Annalise.ai covers Annalise Enterprise CXR, Rad AI covers Impressions.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Annalise.ai and Rad AI actually diverge.

Attributes where Annalise.ai and Rad AI differ
AttributeAnnalise.aiRad AI
PlatformsWeb, Cloud, On-premiseWindows, Web, Cloud

Identical on both: starting price (On request), pricing model (quote), free tier (No), user rating (Not yet rated), category (Healthcare).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Annalise.ai

  • Annalise Enterprise CXR
  • Annalise Enterprise CTB
  • Triage and notification
  • Worklist reprioritisation
  • Localisation overlays
  • Confidence output
  • PACS-native deployment
  • On-premise or cloud inference

Only in Rad AI

  • Impressions
  • Reporting
  • Continuity
  • Style learning
  • Omni Reconcile
  • PACS and dictation embedding
  • Patient outreach workflows
  • Audit reporting

What people use each for

The jobs each tool is most often brought in to do.

Annalise.ai

  • An emergency department wanting pneumothorax and intracranial haemorrhage pushed to the front of the reading queue overnight when cover is thinnestnot Rad AI
  • A teleradiology provider covering many small hospitals that needs consistent triage before a human readsnot Rad AI
  • A screening programme in Europe where the broader CE marked decision support indication, rather than the narrow United States triage clearance, is what is being deployednot Rad AI
  • A radiology department building an AI governance programme that wants one vendor covering both chest radiograph and head CT rather than contracting two separate algorithm suppliersnot Rad AI

Rad AI

  • A private radiology practice whose read volume has grown faster than it can recruit and that wants dictation time per study reduced without changing PACSnot Annalise.ai
  • A health system losing revenue and exposing itself to liability because recommended follow-up imaging on incidental findings is never bookednot Annalise.ai
  • A radiology department standardising impression quality across a mixed group of employed and locum radiologistsnot Annalise.ai
  • A group deploying an AI tool that must not trigger a device validation programme, because governance capacity is already consumed by a triage algorithm rolloutnot Annalise.ai

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Annalise.ai

  • The United States cleared indication covers roughly ten findings for triage and notification, far fewer than the model reports, so a buyer who evaluates the full multi-finding output and then contracts in the United States gets a much narrower cleared use.
  • Triage AI reprioritises a worklist but does not change clinical decisions on its own, so departments that do not redesign how urgent studies are picked up see no measurable improvement in time to treatment.
  • Published validation is largely reader study evidence on detection of individual findings; prospective evidence of shorter time to treatment in routine emergency care is thin.
  • The Annalise brand is being migrated under the Harrison.ai name for the critical care offering, which creates ambiguity in multi-year contracts about what product name is actually being supported.
  • A high finding count raises the alert burden, and departments report that low prevalence findings generate false positives that erode radiologist trust unless the alerting thresholds are tuned locally.

Rad AI

  • The products are not FDA cleared devices and are not intended to be, so any claim that Rad AI improves diagnostic accuracy is unsupported; what has been measured is reporting speed and follow-up completion, not detection.
  • Generated impressions require radiologist review and signature, so the time saving evaporates in any group whose radiologists rewrite the draft rather than edit it, and adoption varies sharply by individual.
  • It is bound to your dictation platform, so a group planning to move off PowerScribe should sequence that decision first or expect to redo the Rad AI integration.
  • Continuity depends on the quality of recommendation language in historical reports, and departments with inconsistent phrasing get poor recall until reporting practice is standardised.
  • Pricing is not published and is structured per radiologist or per study depending on the product mix, which makes it hard to compare against image-analysis AI vendors that price per scan.

Pricing, plan by plan

Annalise.ai

On request
  • Annalise Enterprise$undefined/year
    • Priced per study analysed or as an annual volume subscription
    • CXR and CTB licensed separately
    • Cleared finding set differs by market, which changes what you are buying

Rad AI

On request
  • Rad AI platform$undefined/year
    • Priced per radiologist or per study volume depending on product and contract
    • Impressions, Reporting and Continuity licensed separately
    • Annual subscription with implementation and integration scoped per site

Which should you pick?

Choose Annalise.ai if

  • You need annalise enterprise cxr.
  • You work on Web, Cloud, On-premise.
  • You also want annalise enterprise ctb.
Annalise.ai review

Choose Rad AI if

  • You need impressions.
  • You work on Windows, Web, Cloud.
  • You also want reporting.
Rad AI review

Questions people ask

Is Annalise.ai or Rad AI better?
Neither clearly leads. Annalise.ai starts at On request and Rad AI at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Annalise.ai or Rad AI?
Annalise.ai starts at On request and Rad AI at On request.
Does Annalise.ai or Rad AI run on more platforms?
Annalise.ai runs on Web, Cloud, On-premise. Rad AI runs on Windows, Web, Cloud.
What is Annalise.ai best used for?
Annalise.ai is most often used for an emergency department wanting pneumothorax and intracranial haemorrhage pushed to the front of the reading queue overnight when cover is thinnest, a teleradiology provider covering many small hospitals that needs consistent triage before a human reads, a screening programme in europe where the broader ce marked decision support indication, rather than the narrow united states triage clearance, is what is being deployed, a radiology department building an ai governance programme that wants one vendor covering both chest radiograph and head ct rather than contracting two separate algorithm suppliers. Of those, an emergency department wanting pneumothorax and intracranial haemorrhage pushed to the front of the reading queue overnight when cover is thinnest and a teleradiology provider covering many small hospitals that needs consistent triage before a human reads are not what Rad AI is typically brought in for.
What can Annalise.ai do that Rad AI cannot?
Annalise.ai covers Annalise Enterprise CXR, Annalise Enterprise CTB, Triage and notification, Worklist reprioritisation. Rad AI covers Impressions, Reporting, Continuity, Style learning.

Answered from the vendors’ own pages

Annalise.ai: How many findings are FDA cleared?

Around ten across chest X-ray and head CT, for triage and notification only. The model reports far more findings than that; the rest are not cleared in the United States.

Rad AI: Is Rad AI FDA cleared?

No, and by design. The products draft text and manage follow-up workflow rather than interpreting images, so they fall outside the device pathway. Treat any diagnostic accuracy claim with scepticism.

Annalise.ai: Is the European position different?

Yes. CE marking under the medical device regulation covers a broader decision support indication than the United States triage and notification clearances, so the same software is a different regulatory product depending on where you deploy it.

Rad AI: Does the radiologist still sign the report?

Yes. Output is a draft that the radiologist reviews and signs; nothing is released autonomously.

Annalise.ai: Does it diagnose?

No. In the United States it is a triage and notification device: it flags studies for earlier review, and the radiologist makes the diagnosis.

Rad AI: Which product actually pays for itself?

Continuity has the clearest financial case, because recommended follow-up imaging that gets completed is billable work that currently does not happen.

Annalise.ai: Is Annalise.ai becoming Harrison.ai?

The critical care offering is now marketed under the Harrison.ai name. Ask the vendor to name the contracted product explicitly before signing a multi-year deal.

Rad AI: Will it work with our dictation system?

It is deepest with Nuance PowerScribe. Confirm your specific dictation and PACS combination before contracting, because integration depth is the main deployment variable.

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