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Last updated: June 5, 2026
Back to directoryDeep 6 AI medical AI product profile
Clinical-trial acceleration platform that applies AI to structured and unstructured clinical data for cohort discovery and patient matching.
Precision medicine and data
Best fit
Research organizations that need faster protocol feasibility and patient identification while maintaining investigator, IRB, privacy, and site-review controls.
- Primary use case
- AI-supported cohort discovery, clinical trial matching, protocol feasibility, patient identification, and real-world data extraction
- Audience
- Clinical research operations, trial recruitment teams, academic medical centers, sponsors, CROs, and real-world data teams
- Risk level
- High
- Pricing signal
- Enterprise, research-network, and sponsor pricing; request current deployment and data-access terms.
- Official sources
- 4 official sources
Compare within workflow: Precision medicine and data · comparison shortlist · source index
Regulatory, privacy, evidence, and workflow lens
Product-specific review. These product-specific signals summarize what the cited sources imply before treating Deep 6 AI as safe for a local clinical, operational, or research workflow.
| Regulatory / FDA | Treat as research operations and trial-matching infrastructure; confirm IRB, recruitment, consent, and clinical-trial obligations before using matches for patient contact. |
|---|---|
| Privacy | Review EHR data access, PHI handling, site agreements, role permissions, audit trails, data retention, and whether sponsor-facing workflows expose identifiable data. |
| Evidence | Validate extraction accuracy against local charts, especially for nuanced inclusion and exclusion criteria, temporality, biomarkers, medications, and comorbidities. |
| Workflow | Best used with study-team review loops where AI-ranked candidates are confirmed by trained staff before outreach, enrollment, or protocol decisions. |
Where Deep 6 AI fits
Deep 6 AI describes a clinical-trial acceleration platform that uses AI and NLP to search clinical data, identify patients matching trial criteria, support feasibility, and connect research sites and sponsors.
Not for: Direct treatment recommendations, patient outreach without consent governance, or trial eligibility decisions without clinician and study-team confirmation.
What to verify before using Deep 6 AI
- Which workflow is in scope: cohort discovery, site feasibility, patient matching, chart abstraction, sponsor search, or network analytics.
- Data sources connected, NLP extraction performance, inclusion and exclusion criteria handling, missingness, and provenance for each matched patient.
- HIPAA, consent, IRB, recruitment-contact, data-use, retention, and role-based access controls for identified patient data.
- How study teams verify eligibility, document screening decisions, avoid bias in recruitment, and monitor false positives or missed eligible patients.
Source links
Use these links to confirm current claims, terms, regulatory status, pricing, and deployment requirements.
- deep6.ai
- deep6.ai / how-it-works
- deep6.ai / for-healthcare-organizations
- deep6.ai / for-sponsors-and-cros
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