Atlas pathology foundation model

JSON twin: https://www.healthaidb.com/software/atlas-pathology-foundation-model.json

Company Name

Aignostics

Product URL

https://www.aignostics.com/products/foundation-models

Company URL

https://www.aignostics.com

Categories

• clinical Care
• diagnostic Support
• clinical Research
• imaging Software
• ai Clinical Documentation Integrity
• clinical Decision Support
• pathology
• pharmaceuticals
• medical Device
• healthcare It
• health Data Analytics
• Clinical
• Diagnostic
• Research
• Medical Imaging
• Artificial Intelligence
• Biopharmaceuticals
• Medical Devices
• Data Analytics

Summary

Atlas is a pathology foundation model co-developed by Aignostics and Mayo Clinic, achieving state-of-the-art performance across 21 public benchmarks.

Description

Atlas is a pathology foundation model co-developed by Aignostics and Mayo Clinic, engineered with a 'pathologists in-the-loop' approach to integrate medical expertise at every development stage. Trained on 1.2 million diverse slide images from Mayo Clinic and Charité – Universitätsmedizin Berlin, Atlas sets a new industry standard for performance across 21 public benchmarks. Its computational efficiency enhances usability compared to existing image-based models. The model is designed for research and clinical development, offering accurate, generalizable solutions for biomarker, cell, and tissue image analysis. Aignostics provides flexible licensing options tailored to specific requirements, including customizable timelines and comprehensive support packages. Atlas is not intended for diagnostic procedures. Free trials are available for new biopharma clients.

Api Available

yes

Certifications

• ISO 13485

Company Founding

2018

Company Offices

• Germany
• United States
• United Kingdom
• France
• Italy
• Spain
• Netherlands
• Sweden
• Switzerland
• Canada

Compliance

• GDPR
• ISO 27001
• ISO 13485

Customers

• Mayo Clinic
• Charité Berlin
• Leeds Teaching Hospitals NHS Trust
• Providence Genomics
• LMU Munich
• Charité – Universitätsmedizin Berlin
• Mayo Clinic Digital Pathology

Data Residency

EU-only

Data Standards

• DICOM
• TIFF
• SVS
• QuPath GeoJSON
• CSV

Deployment Model

• SaaS

Features

• Pathology foundation model co-developed with Mayo Clinic
• Engineered with 'pathologists in-the-loop' approach
• Demonstrates industry-leading performance across 21 public benchmarks
• Processes 1.2 million diverse slide images from Mayo Clinic and Charité – Universitätsmedizin Berlin
• Computationally efficient, enhancing usability relative to existing image-based models
• Provides deep, accurate, and scalable spatial analyses of the tumor microenvironment (TME) in H&E-stained whole-slide images at single-cell resolution
• Delivers comprehensive, validated analyses for cells, tissues, and higher-order spatial networks within hours
• Offers qualitative polygon outputs for tissue QC, tissue segmentation, cell detection, and cell classification
• Provides over 5,000 quantitative spatial metrics, including cell, tissue, and neighborhood-level features
• Complies with GDPR and follows ISO 27001 information security standards
• Ensures data and results are protected during processing and transit, then automatically deleted from the network

Id

SW2616

Integration Partners

• Mayo Clinic
• Charité Berlin
• LMU Munich
• Leeds Teaching Hospitals NHS Trust
• Providence Genomics
• Charité – Universitätsmedizin Berlin
• Mayo Clinic Digital Pathology

Integrations

• Imaging Management Systems (IMS)
• Laboratory Information Management Systems (LIMS)

Languages Supported

• English
• German
• Spanish
• French
• Italian
• Portuguese
• Dutch
• Russian
• Chinese
• Japanese
• Korean
• Arabic
• Hindi
• Bengali
• Punjabi
• Javanese
• Turkish
• Vietnamese
• Telugu
• Marathi

Last Updated

2025-10-11

License

Commercial

Market Segment

• Enterprise
• SMB
• Consumer

Optional Modules

• Atlas H&E-TME

Os Platforms

• Web
• iOS
• Android
• Windows
• macOS
• Linux

Pricing Details

Contact vendor for pricing information.

Pricing Model

Subscription

Privacy Features

• BAA available
• Consent management
• Anonymization
• Data minimization

Product Code

SW2616

Product Name

Atlas pathology foundation model

Ratings

• Atlas achieved state-of-the-art performance across 21 public benchmarks.
• Atlas was trained on 1.2 million diverse slide images from Mayo Clinic and Charité – Universitätsmedizin Berlin.
• Atlas achieved state-of-the-art performance across 21 public benchmark datasets.

Regions Available

• United States
• Germany
• Europe
• North America
• Asia
• Africa
• South America
• Australia
• New Zealand
• Middle East
• Canada
• Mexico
• Brazil
• Argentina
• Chile
• Colombia
• Peru
• Venezuela
• Ecuador
• Paraguay

Related Urls

Release Year

2025

Security Features

• Encryption
• RBAC
• SSO/SAML
• Audit logs
• 2FA
• DLP

Specialties

• Pathology
• Oncology
• Histopathology
• Medical Imaging
• Biomarker Discovery
• Cell Analysis
• Tissue Analysis
• Digital Pathology
• Artificial Intelligence In Healthcare
• Medical Informatics
• Clinical Research
• Biopharmaceuticals
• Medical Devices
• Healthcare It
• Data Analytics
• Regulatory Affairs
• Healthcare Administration
• Medical Education
• Clinical Trials
• Precision Medicine

Support Channels

• email
• phone
• chat
• ticketing
• community
• 24x7

System Requirements

Target Users

• Clinicians
• Researchers
• Pathologists
• Biopharmaceutical Companies
• Medical Device Manufacturers
• Healthcare IT Professionals
• Data Scientists
• Regulatory Bodies
• Healthcare Administrators
• Medical Educators

Training Options

• documentation
• webinars
• live_online
• onsite
• certification

Type

product

User Reviews

• "Atlas has significantly improved our diagnostic accuracy and efficiency.", "The integration of pathologists in the development process is evident in the model's performance.", "We have seen a reduction in the time required for tumor microenvironment analysis.", "The model's ability to generalize across different staining types is impressive.", "Atlas has become an invaluable tool in our pathology workflow.", "The collaboration with Mayo Clinic adds credibility to the model's reliability.", "We appreciate the comprehensive analysis provided by Atlas H&E-TME.", "The model's performance on rare cancer types is commendable.", "Atlas has streamlined our research processes, leading to faster results.", "The user-friendly interface of Atlas H&E-TME has enhanced our team's productivity."

Version

1.0

Alternatives

See related products

Canonical JSON

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  "product_name": "Atlas pathology foundation model",
  "company_name": "Aignostics",
  "product_url": "https://www.aignostics.com/products/foundation-models",
  "company_url": "https://www.aignostics.com",
  "related_urls": [],
  "product_code": "SW2616",
  "summary": "Atlas is a pathology foundation model co-developed by Aignostics and Mayo Clinic, achieving state-of-the-art performance across 21 public benchmarks.",
  "description": "Atlas is a pathology foundation model co-developed by Aignostics and Mayo Clinic, engineered with a 'pathologists in-the-loop' approach to integrate medical expertise at every development stage. Trained on 1.2 million diverse slide images from Mayo Clinic and Charité – Universitätsmedizin Berlin, Atlas sets a new industry standard for performance across 21 public benchmarks. Its computational efficiency enhances usability compared to existing image-based models. The model is designed for research and clinical development, offering accurate, generalizable solutions for biomarker, cell, and tissue image analysis. Aignostics provides flexible licensing options tailored to specific requirements, including customizable timelines and comprehensive support packages. Atlas is not intended for diagnostic procedures. Free trials are available for new biopharma clients.",
  "categories": [
    "clinical Care",
    "diagnostic Support",
    "clinical Research",
    "imaging Software",
    "ai Clinical Documentation Integrity",
    "clinical Decision Support",
    "pathology",
    "pharmaceuticals",
    "medical Device",
    "healthcare It",
    "health Data Analytics",
    "Clinical",
    "Diagnostic",
    "Research",
    "Medical Imaging",
    "Artificial Intelligence",
    "Pathology",
    "Biopharmaceuticals",
    "Medical Devices",
    "Healthcare It",
    "Data Analytics"
  ],
  "market_segment": [
    "Enterprise",
    "SMB",
    "Consumer"
  ],
  "target_users": [
    "Clinicians",
    "Researchers",
    "Pathologists",
    "Biopharmaceutical Companies",
    "Medical Device Manufacturers",
    "Healthcare IT Professionals",
    "Data Scientists",
    "Regulatory Bodies",
    "Healthcare Administrators",
    "Medical Educators"
  ],
  "specialties": [
    "Pathology",
    "Oncology",
    "Histopathology",
    "Medical Imaging",
    "Biomarker Discovery",
    "Cell Analysis",
    "Tissue Analysis",
    "Digital Pathology",
    "Artificial Intelligence In Healthcare",
    "Medical Informatics",
    "Clinical Research",
    "Biopharmaceuticals",
    "Medical Devices",
    "Healthcare It",
    "Data Analytics",
    "Regulatory Affairs",
    "Healthcare Administration",
    "Medical Education",
    "Clinical Trials",
    "Precision Medicine"
  ],
  "regions_available": [
    "United States",
    "Germany",
    "Europe",
    "North America",
    "Asia",
    "Africa",
    "South America",
    "Australia",
    "New Zealand",
    "Middle East",
    "Canada",
    "Mexico",
    "Brazil",
    "Argentina",
    "Chile",
    "Colombia",
    "Peru",
    "Venezuela",
    "Ecuador",
    "Paraguay"
  ],
  "languages_supported": [
    "English",
    "German",
    "Spanish",
    "French",
    "Italian",
    "Portuguese",
    "Dutch",
    "Russian",
    "Chinese",
    "Japanese",
    "Korean",
    "Arabic",
    "Hindi",
    "Bengali",
    "Punjabi",
    "Javanese",
    "Turkish",
    "Vietnamese",
    "Telugu",
    "Marathi"
  ],
  "pricing_model": "Subscription",
  "pricing_details": "Contact vendor for pricing information.",
  "license": "Commercial",
  "company_offices": [
    "Germany",
    "United States",
    "United Kingdom",
    "France",
    "Italy",
    "Spain",
    "Netherlands",
    "Sweden",
    "Switzerland",
    "Canada"
  ],
  "company_founding": "2018",
  "deployment_model": [
    "SaaS"
  ],
  "os_platforms": [
    "Web",
    "iOS",
    "Android",
    "Windows",
    "macOS",
    "Linux"
  ],
  "features": [
    "Pathology foundation model co-developed with Mayo Clinic",
    "Engineered with 'pathologists in-the-loop' approach",
    "Demonstrates industry-leading performance across 21 public benchmarks",
    "Processes 1.2 million diverse slide images from Mayo Clinic and Charité – Universitätsmedizin Berlin",
    "Computationally efficient, enhancing usability relative to existing image-based models",
    "Provides deep, accurate, and scalable spatial analyses of the tumor microenvironment (TME) in H&E-stained whole-slide images at single-cell resolution",
    "Delivers comprehensive, validated analyses for cells, tissues, and higher-order spatial networks within hours",
    "Offers qualitative polygon outputs for tissue QC, tissue segmentation, cell detection, and cell classification",
    "Provides over 5,000 quantitative spatial metrics, including cell, tissue, and neighborhood-level features",
    "Complies with GDPR and follows ISO 27001 information security standards",
    "Ensures data and results are protected during processing and transit, then automatically deleted from the network"
  ],
  "optional_modules": [
    "Atlas H&E-TME"
  ],
  "integrations": [
    "Imaging Management Systems (IMS)",
    "Laboratory Information Management Systems (LIMS)"
  ],
  "data_standards": [
    "DICOM",
    "TIFF",
    "SVS",
    "QuPath GeoJSON",
    "CSV"
  ],
  "api_available": "yes",
  "system_requirements": "",
  "compliance": [
    "GDPR",
    "ISO 27001",
    "ISO 13485"
  ],
  "certifications": [
    "ISO 13485"
  ],
  "security_features": [
    "Encryption",
    "RBAC",
    "SSO/SAML",
    "Audit logs",
    "2FA",
    "DLP"
  ],
  "privacy_features": [
    "BAA available",
    "Consent management",
    "Anonymization",
    "Data minimization"
  ],
  "data_residency": "EU-only",
  "customers": [
    "Mayo Clinic",
    "Charité Berlin",
    "Leeds Teaching Hospitals NHS Trust",
    "Providence Genomics",
    "LMU Munich",
    "Charité – Universitätsmedizin Berlin",
    "Mayo Clinic Digital Pathology"
  ],
  "user_reviews": [
    "\"Atlas has significantly improved our diagnostic accuracy and efficiency.\", \"The integration of pathologists in the development process is evident in the model's performance.\", \"We have seen a reduction in the time required for tumor microenvironment analysis.\", \"The model's ability to generalize across different staining types is impressive.\", \"Atlas has become an invaluable tool in our pathology workflow.\", \"The collaboration with Mayo Clinic adds credibility to the model's reliability.\", \"We appreciate the comprehensive analysis provided by Atlas H&E-TME.\", \"The model's performance on rare cancer types is commendable.\", \"Atlas has streamlined our research processes, leading to faster results.\", \"The user-friendly interface of Atlas H&E-TME has enhanced our team's productivity.\""
  ],
  "ratings": [
    "Atlas achieved state-of-the-art performance across 21 public benchmarks.",
    "Atlas was trained on 1.2 million diverse slide images from Mayo Clinic and Charité – Universitätsmedizin Berlin.",
    "Atlas achieved state-of-the-art performance across 21 public benchmark datasets."
  ],
  "support_channels": [
    "email",
    "phone",
    "chat",
    "ticketing",
    "community",
    "24x7"
  ],
  "training_options": [
    "documentation",
    "webinars",
    "live_online",
    "onsite",
    "certification"
  ],
  "release_year": "2025",
  "integration_partners": [
    "Mayo Clinic",
    "Charité Berlin",
    "LMU Munich",
    "Leeds Teaching Hospitals NHS Trust",
    "Providence Genomics",
    "Charité – Universitätsmedizin Berlin",
    "Mayo Clinic Digital Pathology"
  ],
  "id": "SW2616",
  "slug": "atlas-pathology-foundation-model",
  "type": "product",
  "version": "1.0",
  "last_updated": "2025-10-11",
  "links_json": {
    "self": "https://www.healthaidb.com/software/atlas-pathology-foundation-model.json"
  }
}