Healthcare · head to head
PathAI vs Rad AI
PathAI
Healthcare
Digital pathology image management with an FDA cleared platform for primary diagnosis
- From
- On request
- Rated
- -
Rad AI
Healthcare
Generative reporting and follow-up tracking for radiology, positioned outside the diagnostic device boundary
- From
- On request
- Rated
- -
The short version
- Each has a real cost: 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.; 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: PathAI covers AISight image management, Rad AI covers Impressions.
- Prices and features above were last checked on 1 September 2026.
Where they differ
Only the attributes on which PathAI and Rad AI actually diverge.
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 PathAI
- AISight image management
- AISight Dx
- Scanner interoperability
- Case and worklist management
- AI algorithm deployment
- Biopharmaceutical research tooling
- LIS integration
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.
PathAI
- An academic medical centre going digital for primary diagnosis that needs the FDA cleared AISight Dx configuration rather than the research labelled versionnot Rad AI
- A reference laboratory consolidating subspecialty sign out across sites so a specialist pathologist can read cases from any locationnot Rad AI
- A pharmaceutical company needing consistent quantitative scoring of trial biopsies across many sites and readersnot Rad AI
- A laboratory with a mixed scanner estate that needs one image management layer rather than each scanner vendor viewernot 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 PathAI
- A health system losing revenue and exposing itself to liability because recommended follow-up imaging on incidental findings is never bookednot PathAI
- A radiology department standardising impression quality across a mixed group of employed and locum radiologistsnot PathAI
- 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 PathAI
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal 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.
- 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.
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
PathAI
On request- AISight$undefined/year
- Priced by annual slide or case volume and by pathologist seats
- AISight Dx, the clinically cleared configuration, quoted separately from research use AISight
- Image storage priced by capacity and retention policy
Rad AI
On request- Rad AI platform$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 Rad AI if
- You need impressions.
- You work on Windows, Web, Cloud.
- You also want reporting.
Questions people ask
- Is PathAI or Rad AI better?
- Neither clearly leads. PathAI 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, PathAI or Rad AI?
- PathAI starts at On request and Rad AI at On request.
- Does PathAI or Rad AI run on more platforms?
- PathAI runs on Web. Rad AI runs on Windows, Web, Cloud.
- What is PathAI best used for?
- PathAI is most often used for an academic medical centre going digital for primary diagnosis that needs the fda cleared aisight dx configuration rather than the research labelled version, a reference laboratory consolidating subspecialty sign out across sites so a specialist pathologist can read cases from any location, a pharmaceutical company needing consistent quantitative scoring of trial biopsies across many sites and readers, a laboratory with a mixed scanner estate that needs one image management layer rather than each scanner vendor viewer. Of those, an academic medical centre going digital for primary diagnosis that needs the fda cleared aisight dx configuration rather than the research labelled version and a reference laboratory consolidating subspecialty sign out across sites so a specialist pathologist can read cases from any location are not what Rad AI is typically brought in for.
- What can PathAI do that Rad AI cannot?
- PathAI covers AISight image management, AISight Dx, Scanner interoperability, Case and worklist management. Rad AI covers Impressions, Reporting, Continuity, Style learning.
Answered from the vendors’ own pages
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.
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.
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.
Rad AI: Does the radiologist still sign the report?
Yes. Output is a draft that the radiologist reviews and signs; nothing is released autonomously.
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.
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.
PathAI: Is pricing published?
No. It is quoted by slide or case volume, pathologist seats and storage, with the clinically cleared configuration priced separately.
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.
Related pages
Other head to heads
- PathAI vs Techcyte
- PathAI vs Ambra Health
- PathAI vs Paige
- PathAI vs Sysmex
- PathAI vs Sectra
- PathAI vs Lunit
- PathAI vs Aidoc
- PathAI vs Ibex Medical Analytics
- PathAI vs Therapixel
- PathAI vs Gleamer
- PathAI vs Philips IntelliSpace PACS
- PathAI vs Annalise.ai
- PathAI vs Quantum Health
- PathAI vs TherapyNotes
- PathAI vs Zocdoc
- PathAI vs Allscripts Professional EHR
- PathAI vs Visage Imaging
- PathAI vs Fujifilm Synapse
- PathAI vs Cerner PowerChart
- PathAI vs Clue
- PathAI vs Flo
- PathAI vs Koa Health
- Rad AI vs Techcyte
- Rad AI vs Ambra Health
- Rad AI vs Paige
- Rad AI vs Sysmex
- Rad AI vs Sectra
- Rad AI vs Lunit
- Rad AI vs Aidoc
- Rad AI vs Ibex Medical Analytics
- Rad AI vs Therapixel
- Rad AI vs Gleamer
- Rad AI vs Philips IntelliSpace PACS
- Rad AI vs Annalise.ai
- Rad AI vs Quantum Health
- Rad AI vs TherapyNotes
- Rad AI vs Zocdoc
- Rad AI vs Allscripts Professional EHR
- Rad AI vs Visage Imaging
- Rad AI vs Fujifilm Synapse
- Rad AI vs Cerner PowerChart
- Rad AI vs Clue
- Rad AI vs Flo
- Rad AI vs Koa Health