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PathAI vs Paige AI
This comparison was retrieved by database IDs selected from the catalog.
PathAI
PathAI
Paige AI
Paige
Enterprise and pharmaceutical partner licensing. No public pricing or individual access.
Enterprise licensing to health systems and pathology labs. No public pricing or individual access.
HIPAA compliant with BAA. ISO 13485. FDA clearance for specific indications. Enterprise data handling agreements.
HIPAA compliant with BAA. FDA De Novo authorisation (Paige Prostate). ISO 13485 medical device quality management. Enterprise data handling agreements.
Digital pathology slide data processed under HIPAA BAA. FDA clearance for clinical use is indication-specific — review regulatory status for each intended use.
Digital pathology slide data processed under HIPAA BAA with medical device security standards. FDA authorised for specific clinical indications.
- Demonstrable accuracy in specific cancer diagnosis tasks on large pathology slide datasets
- Pharmaceutical partner programme with BMS, AstraZeneca, and Gilead validates clinical credibility
- Consistent quantification across large sample sets improves on inter-pathologist variability
- FDA-cleared tools for specific clinical indications
- First FDA De Novo authorisation for AI clinical pathology — critical regulatory differentiator for clinical deployment
- Published clinical evidence shows improved cancer detection with AI-assisted pathologists
- Expanding cancer type coverage builds on the regulatory foundation for prostate cancer
- Academic medical centre partnerships provide credible clinical reference implementations
- Enterprise and pharmaceutical partner model — not accessible to individual pathology labs
- Regulatory clearance is indication-specific — clinical use requires FDA-cleared indications only
- ROI case requires high-volume pathology operation or significant clinical trial programme
- Enterprise licensing only — not accessible to individual pathologists or small labs
- FDA authorisation is indication-specific — Paige Prostate is cleared; other cancer types are in different regulatory stages
- Clinical AI pathology adoption requires significant workflow integration and pathologist training investment
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