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Healthcare · head to head

Annalise.ai vs PathAI

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
PathAI logo

PathAI

Healthcare

Digital pathology image management with an FDA cleared platform for primary diagnosis

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.; PathAI aISight is labelled research use only and cannot be used for primary diagnosis; only AISight Dx carries the FDA clearance and CE-IVD mark, and laboratories regularly buy the wrong configuration and discover they cannot sign out on it.
  • They diverge on capability: Annalise.ai covers Annalise Enterprise CXR, PathAI covers AISight image management.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Annalise.ai and PathAI actually diverge.

Attributes where Annalise.ai and PathAI differ
AttributeAnnalise.aiPathAI
PlatformsWeb, Cloud, On-premiseWeb

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 PathAI

  • AISight image management
  • AISight Dx
  • Scanner interoperability
  • Case and worklist management
  • AI algorithm deployment
  • Biopharmaceutical research tooling
  • LIS integration

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 PathAI
  • A teleradiology provider covering many small hospitals that needs consistent triage before a human readsnot PathAI
  • 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 PathAI
  • 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 PathAI

PathAI

  • An academic medical centre going digital for primary diagnosis that needs the FDA cleared AISight Dx configuration rather than the research labelled versionnot Annalise.ai
  • A reference laboratory consolidating subspecialty sign out across sites so a specialist pathologist can read cases from any locationnot Annalise.ai
  • A pharmaceutical company needing consistent quantitative scoring of trial biopsies across many sites and readersnot Annalise.ai
  • A laboratory with a mixed scanner estate that needs one image management layer rather than each scanner vendor viewernot 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.

PathAI

  • AISight is labelled research use only and cannot be used for primary diagnosis; only AISight Dx carries the FDA clearance and CE-IVD mark, and laboratories regularly buy the wrong configuration and discover they cannot sign out on it.
  • The software licence is usually the smallest line in a digital pathology project, behind scanners, storage and network capacity, so a business case built around the software cost understates the real investment by a wide margin.
  • Whole slide images are very large, so a laboratory that does not model storage growth and retention policy from the start faces storage costs that grow faster than case volume and dominate the renewal.
  • Clinical validation is required per subspecialty rather than once for the platform, which means dermatopathology, gastrointestinal and breast each need their own concordance study and pathologist time before go live.
  • PathAI competes against pathology incumbents that also sell the scanners, and a laboratory buying an independent image management layer takes on the integration risk between scanner vendor and software vendor itself.

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

PathAI

On request
  • AISight$undefined/year
    • Priced by annual slide or case volume and by pathologist seats
    • AISight Dx, the clinically cleared configuration, quoted separately from research use AISight
    • Image storage priced by capacity and retention policy

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 PathAI if

  • You need aisight image management.
  • You also want aisight dx.
PathAI review

Questions people ask

Is Annalise.ai or PathAI better?
Neither clearly leads. Annalise.ai starts at On request and PathAI at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Annalise.ai or PathAI?
Annalise.ai starts at On request and PathAI at On request.
Does Annalise.ai or PathAI run on more platforms?
Annalise.ai runs on Web, Cloud, On-premise. PathAI runs on Web.
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 PathAI is typically brought in for.
What can Annalise.ai do that PathAI cannot?
Annalise.ai covers Annalise Enterprise CXR, Annalise Enterprise CTB, Triage and notification, Worklist reprioritisation. PathAI covers AISight image management, AISight Dx, Scanner interoperability, Case and worklist management.

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.

PathAI: What is the difference between AISight and AISight Dx?

AISight is for research use only and not for clinical diagnostic use. AISight Dx received FDA 510(k) clearance in June 2025 for primary diagnosis and is CE-IVD marked in the EEA, UK and Switzerland. Only the Dx configuration can be used to sign out cases.

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.

PathAI: Can we use our existing scanners?

Yes. AISight is designed to ingest images from multiple whole slide scanner vendors, which is one of the main reasons laboratories choose an independent image management layer.

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.

PathAI: Do the AI algorithms carry the same clearance as the platform?

No. The platform clearance covers image management for primary diagnosis. Individual algorithms have their own labelling, and many are research use only. Check each one separately.

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.

PathAI: Is pricing published?

No. It is quoted by slide or case volume, pathologist seats and storage, with the clinically cleared configuration priced separately.

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