Compliance & Validation — Documented
ISO 27001, SOC 2 Type II
Ketryx
AI platform for regulated product development that generates traceability and compliance documentation for life-sciences software.
Ketryx, founded in 2021 and headquartered in Cambridge, Massachusetts (with an office in Vienna, Austria), builds an AI platform for regulated product development that connects engineering tools with quality and regulatory processes, automatically generating traceability and documentation for FDA-regulated software and AI applications. The company reports more than $55M raised, including a 2025 Series B. Its trust center documents an ISO/IEC 27001:2022 certification and a SOC 2 Type 2 report, plus UL certifications to medical-device software standards (IEC 62304, ISO 13485, ISO 14971) that fall outside Atlas's security-certification tags; 21 CFR Part 11 is documented as a self-assessment and is therefore noted in prose rather than tagged.
- Headquarters
- Cambridge, United States
- Founded
- 2021
- Compliance
- ISO 27001, SOC 2 Type II
- Deployment options
- cloud
- Website
- https://www.ketryx.com
- https://www.linkedin.com/company/ketryx
Categories
Vendor Scorecard
57% — Partial coverage. Coverage score — how completely Atlas documents Ketryx across 7 buyer-evaluation areas. Reflects available Atlas data, not solution quality.
Deployment & Hosting — Documented
cloud
Pricing Transparency — Not documented by Atlas
Ask the vendor: What is your pricing model, and what drives total cost of ownership?
Implementation & Onboarding — Not documented by Atlas
Ask the vendor: What is a realistic implementation timeline, and what onboarding support is included?
Organization & Role Fit — Documented
Biotech Startup, Mid-Size Biotech, Large Pharma, Top 20 Pharma, Regulatory Affairs, IT / Digital
Solution Scope — Not documented by Atlas
Regulatory Affairs
Company Viability — Documented
Series B, $55.0M raised, Founded 2021
Always ask the vendor
Not captured in Atlas data — confirm directly. Excluded from the score above.
Data Rights & IP
Who owns model outputs? Is our proprietary data used to train models others can access, and where does our data reside?
Model Credibility & Explainability
Can you share validation studies or benchmarks, explain how the model reaches its conclusions, and describe how bias and drift are monitored?
Questions to Ask This Vendor
- Which regulated-software workflows and toolchains does the platform integrate with?
- How is AI-generated traceability reviewed and approved before use?
- What is covered by the ISO 27001 and SOC 2 scopes, and can you share the reports?
- How does the platform support our own 21 CFR Part 11 validation obligations?