Human-in-the-Loop
Involving human judgment within AI processes (training, validation, decision review) to improve accuracy and accountability.
A hybrid approach where humans augment AI workflows - providing labels, verifying low-confidence predictions, or overriding model decisions. HITL ensures that edge-case, high-risk, or novel situations receive expert attention. Effective governance sets thresholds for human intervention, tracks human-AI performance comparisons, and prevents human biases from undermining automation gains.
A medical-diagnosis AI flags scans with model-confidence below 80% for radiologist review (HITL). Over six months, 95% of low-confidence cases were correctly classified by humans, and those labels feed back into model retraining - improving confidence calibration and reducing overall error rates.
We help you find answers
What problem does Enzai solve?
Enzai provides enterprise-grade infrastructure to manage AI risk and compliance. It creates a centralized system of record where AI systems, models, datasets, and governance decisions are documented, assessed, and auditable.
Who is Enzai built for?
How is Enzai different from other governance tools?
Can we start if we have no existing AI governance process?
Does AI governance slow down innovation?
How does Enzai stay aligned with evolving AI regulations?
Research, insights, and updates
Empower your organization to adopt, govern, and monitor AI with enterprise-grade confidence. Built for regulated organizations operating at scale.