Compliance & Validation — Documented
HIPAA, SOC 2 Type II, 21 CFR Part 11
Trially AI
AI-native clinical trial enrollment platform that matches, engages, and enrolls patients from health-system records.
Trially AI, founded in 2023 and headquartered in Kansas City, Missouri, builds an AI-native clinical trial enrollment platform that matches, engages, and enrolls eligible patients by reading structured and unstructured health-system data. The company raised a $4.7M seed round led by Flyover Capital in 2025. Trially states on its own site that its product is HIPAA compliant and displays an AICPA SOC 2 attestation badge and an FDA 21 CFR Part 11 compliance badge; buyers should request the current SOC 2 report and Part 11 validation documentation to confirm scope.
- Headquarters
- Kansas City, United States
- Founded
- 2023
- Compliance
- HIPAA, SOC 2 Type II, 21 CFR Part 11
- Deployment options
- cloud
- Website
- https://www.trially.ai
- https://www.linkedin.com/company/trially
Categories
AI Use Cases
- Patient Recruitment & Enrollment
- Site Selection & Performance
Vendor Scorecard
64% — Partial coverage. Coverage score — how completely Atlas documents Trially AI 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, CRO / CDMO, Clinical Operations, Data Management
Solution Scope — Documented
Natural Language Processing, Patient Recruitment
Company Viability — Partially documented
Seed, Founded 2023
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
- How is patient-matching accuracy measured on our therapeutic area and site population?
- Which EHR and health-system data sources can the platform ingest, and what does integration require?
- Can you share the current SOC 2 Type II report and 21 CFR Part 11 validation package under NDA?
- What site or sponsor deployments can serve as references for our indication?