When is Deep 6 AI the better choice?

It reads unstructured clinical data across notes, pathology, genomics and laboratory reports to match patients and sites in real time across therapeutic areas. Coverage spans feasibility and cohort building at study design through enrolment, so sponsors and sites use one platform. It quantifies how much decisive eligibility information sits in unstructured data, which is the argument for reading notes rather than filtering codes.

When is Dyania Health the better choice?

It publishes methods rather than claims, with peer reviewed real world evidence from a major academic health system where the platform screened across many hospitals. The clinician in the loop design was preserved inside the published study rather than described separately from it. Diversity was treated as a measured study endpoint rather than a marketing claim about equitable access.

Deep 6 AI vs Dyania Health

Last VerifiedAugust 4, 2026

Verdict

Two trial matching platforms, one broader and one better evidenced. Deep 6 covers the lifecycle from feasibility and cohort building through enrolment across therapeutic areas, reading unstructured notes, pathology, genomics and laboratory data. Dyania published methods rather than claims, with peer reviewed real world evidence from a major academic health system where its platform screened across many hospitals, and it kept the clinician in the loop inside the study rather than describing that separately, with diversity treated as a measured endpoint. For a health system that wants coverage, Deep 6. For one that will have to defend the screening process, Dyania has published what that looks like in practice. Neither publishes how often an eligible patient never surfaces at all.

Select Deep 6 AI if

It reads unstructured clinical data across notes, pathology, genomics and laboratory reports to match patients and sites in real time across therapeutic areas.
Coverage spans feasibility and cohort building at study design through enrolment, so sponsors and sites use one platform.
It quantifies how much decisive eligibility information sits in unstructured data, which is the argument for reading notes rather than filtering codes.

Select Dyania Health if

It publishes methods rather than claims, with peer reviewed real world evidence from a major academic health system where the platform screened across many hospitals.
The clinician in the loop design was preserved inside the published study rather than described separately from it.
Diversity was treated as a measured study endpoint rather than a marketing claim about equitable access.

Attribute Matrix

Side by Side

Axis	D Deep 6 AI	D Dyania Health
AI Centrality
Autonomy and Oversight Model
Model and Technology Transparency
Clinical and Operational Evidence
AI Safety and PHI Stewardship
HIPAA and BAA Posture
Security Certifications and Trust Center
FDA and Regulatory Status
AI Governance and Bias Disclosure
EHR and Interoperability Depth
Deployment Model and Data Residency
Commercial Transparency
Setting and Specialty Coverage

Keep Comparing

Related comparisons

Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Clinical Decision Support page.

Deep 6 AI vs Massive Bio→Deep 6 AI vs Mendel→Deep 6 AI vs Paradigm Health→Deep 6 AI vs Triomics→Deep 6 AI vs xCures→Dyania Health vs Mendel→Dyania Health vs Triomics→

Disclosure

Both should be asked for the false negative rate on eligibility screening, which neither publishes and which is the only real measure of a matching system, since a patient who was eligible and never surfaced is invisible in every metric either reports. Both inherit documentation bias, so patients with thin or fragmented records match less often regardless of eligibility, and that population overlaps with the one trials already under enrol. Deep 6 publishes no attestation scoped to the platform, no business associate terms and no governance framework. Neither publishes pricing.