Mindpeak

Deep learning models are the whole company. The portfolio is a set of biomarker quantification algorithms operating on H and E, immunohistochemistry, and multiplex immunofluorescence images, with no platform, scanner, or assay of its own. That purity is also a commercial dependency: the algorithms need someone else's workspace to reach a pathologist, which is why they are distributed through PathAI's platform as well as directly.

Assistive quantification with the pathologist interpreting. The distinguishing design question in this category, as sector commentary notes, is whether the pathologist manually selects the region of interest or the system analyzes the whole slide unaided, and Mindpeak ships both patterns, with region of interest products named as such alongside broader analysis. Peer reviewed evaluation frames the tool as improving interobserver agreement rather than replacing the reader. Clear assistive positioning; the human sets the clinical meaning of the score.

The technical claim is specific and checkable: BreastIHC was described at launch as the first deep learning solution able to distinguish tumorous from non tumorous structures at the cellular level in single stained slides, classifying cells into positively stained tumor and unstained tumor populations. The company markets plug and play deployment without per site calibration, which is a meaningful robustness claim. Training data scale and architecture are not published, and the robustness claim is asserted rather than independently benchmarked, but independent studies have tested the tools across image variance.

Genuinely independent evidence exists, which is rarer than it should be here. A study by Abele and colleagues assessed the Breast Ki-67 and ER/PR products for quantifying Ki-67, ER, and PR, finding reliability across a wide range of image variance and pathologist confirmation, and concluding the tools can improve interobserver agreement in real world clinical settings. A separate PubMed indexed concordance study at Aga Khan University Hospital compared automated Ki67 scoring against expert pathologist eyeball assessment across 60 invasive ductal carcinoma cases and reported strong positive concordance. Both are third party rather than vendor run, though sample sizes are modest and endpoints are concordance rather than patient outcome.

No specific PHI handling or data governance framework was located. Distribution through a third party platform adds a party to the data path, making stewardship terms dependent on which route a laboratory uses.

No HIPAA or BAA commitment was located. The clinical portfolio is CE-IVD marked for European use rather than FDA cleared for US clinical use, so a US engagement would require establishing terms directly or through the hosting platform.

No SOC 2, ISO 27001, or equivalent attestation and no trust center were located in the materials reviewed.

Eleven CE-IVD marked algorithms is a substantial European portfolio, covering breast HER2, ER, PR, and Ki-67 plus lung PD-L1, and the company reached CE-IVD for primary diagnosis with BreastIHC as an early mover. No FDA clearance was located, and the company is explicit that its prostate and other tumor type assays are research use only rather than clinical. Graded C on the established basis: strong non US authorization, no US clinical clearance, with clear disclosure of which products are research use only.

No formal governance framework, monitoring commitment, or demographic subgroup analysis was located. Independent evaluation across varied image conditions addresses technical robustness but not population level performance differences.

Reach comes through platform distribution rather than direct integration engineering. Since 2025 the CE-IVD portfolio is accessible inside PathAI's AISight platform, which is separately indexed here and itself FDA cleared for primary diagnosis in the US and CE-IVD marked in Europe. For a laboratory already running that platform, adoption is algorithm selection rather than an integration project. For everyone else, integration depends on which host workspace is in place, and the vendor does not publish a broader connector list. This is the Archy and Pearl pattern: the algorithm reaches the pathologist through someone else's product.

No hosting, tenancy, or data residency terms were located. Where the algorithms run via a third party platform, residency is effectively determined by that platform rather than by this vendor.

No pricing is published. The dual route to market, direct and embedded in PathAI's platform, means commercial terms likely differ by channel, and neither is disclosed. A buyer should establish which route they are purchasing through, since it affects both cost structure and who holds the support and data relationship.

Concentrated on breast cancer immunohistochemistry, the highest volume biomarker workload in European pathology, extending to lung PD-L1 clinically and to prostate and other tumor types for research use only. Depth in a high demand area rather than breadth across pathology, and the clinical versus research use split means actual coverage is narrower than the full product list suggests.