Compliance & Validation — Documented
SOC 2 Type II, 21 CFR Part 11, GDPR
Kivo
Cloud document, RIM, and QMS platform for emerging pharma teams, with 21 CFR Part 11 workflows and submission tracking.
Kivo, founded in 2021 and headquartered in Portland, Oregon, provides a cloud platform for emerging pharma and biotech teams combining document management, eTMF, regulatory information management, and QMS with submission tracking, and reports use by more than 60 sponsors and service providers. The company raised a $3 million seed round in May 2025 led by Facet and Oregon Venture Fund (a larger Series A has been reported by data aggregators but not press-confirmed), and documents a SOC 2 Type 2 report alongside self-declared 21 CFR Part 11 and GDPR compliance. Its sweet spot is smaller teams consolidating tools; large-enterprise RIM depth should be evaluated carefully.
- Headquarters
- Portland, United States
- Founded
- 2021
- Compliance
- SOC 2 Type II, 21 CFR Part 11, GDPR
- Deployment options
- cloud
- Website
- https://kivo.io
- https://www.linkedin.com/company/kivoio
Categories
AI Use Cases
- Regulatory Submission Authoring
Vendor Scorecard
71% — Complete coverage. Coverage score — how completely Atlas documents Kivo 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, Regulatory Affairs, Clinical Operations
Solution Scope — Documented
Regulatory Submission Authoring
Company Viability — Documented
Seed, $3.0M 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 modules (DMS, eTMF, RIM, QMS) are most mature today?
- How does submission tracking handle our target markets beyond FDA?
- Which compliance claims are third-party audited versus self-assessed?
- What is the migration path if we outgrow the platform?