Compliance & Validation — Documented
HIPAA
Datavant
Health data connectivity company providing privacy-preserving record linkage and exchange across the healthcare ecosystem.
Datavant, founded in 2017 and headquartered in San Francisco, provides privacy-preserving tokenization and record-linkage technology that lets healthcare and life sciences organizations connect patient-level data across sources without exchanging identifiable information, alongside health-data exchange capabilities from its 2021 merger with Ciox Health. Datavant acquired real-world evidence platform Aetion in July 2025 as part of its life sciences business. Its de-identification workflows are built around HIPAA expert-determination standards.
- Headquarters
- San Francisco, United States
- Founded
- 2017
- Compliance
- HIPAA
- Deployment options
- cloud
- Website
- https://www.datavant.com
- https://www.linkedin.com/company/datavant
Categories
Vendor Scorecard
50% — Partial coverage. Coverage score — how completely Atlas documents Datavant 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
Mid-Size Biotech, Large Pharma, Top 20 Pharma, CRO / CDMO, Data Management, IT / Digital, R&D Leadership
Solution Scope — Not documented by Atlas
Data & AI Infrastructure
Company Viability — Partially documented
Private, Founded 2017
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 of our data partners already participate in the token ecosystem?
- How does expert-determination de-identification work across linked datasets?
- What does token adoption require from our internal data infrastructure?
- How does the Aetion acquisition change the analytics offering?