Choose the right starting point for your model.
Share high-level, non-PHI context about the model, its intended use, the decision ahead, and whether a held-out evaluation set exists and where it can be evaluated.
Direct email
info@synset.aiFor fit evaluation, Translation Readiness Assessments, Model Hardening Pilots, regression evidence, specialist assessments, and local validation design paths.
Specialized assessments and clinical-world packages
Maintain
Regression Suite
Preserve fixed scenarios and observed failures for future model and workflow changes.
Enterprise
Local Validation
Discuss authorized evaluation where customer-controlled models and real data already live.
Assess
Documentation Model Assessment
Review grounding, omissions, contradictions, temporal errors, and documentation shifts.
Assess
Coding / CDI Model Assessment
Review missed codes, unsupported codes, upcoding risk, and evidence inconsistency.
Assess
Risk Model Assessment
Review calibration, false negatives, subgroup behavior, missingness, drift, and coverage.
Harden
Targeted Hardening Cohort
Checked synthetic clinical worlds built around one measured weakness.
Prove
Held-Out Hardening Study
Evaluate a frozen intervention on held-out real data under prespecified criteria.
Build
FHIR / EHR Sandbox
Synthetic populations for integration tests, staging, demonstrations, and simulation.
Build
Rare-State Scenario Pack
Controlled material for rare states, sparse evidence, and supported edge conditions.
Useful context to include
- model stage, model type, and declared clinical use
- clinical domain and target population
- suspected weakness or evidence gap
- intervention options already considered
- whether a held-out evaluation set exists and where it can be evaluated
- pilot timeline and the decision this evidence must support