Explainable
A recommendation should show the evidence, criteria and weighting that shaped it.
Data & AI Principles
Automation proposes. An accountable human decides.
UPDATED · AUGUST 2026
BAYTECH uses AI to organize evidence and surface potential fit. Human review remains responsible for every qualified introduction and programme decision.
Consent-based
No introduction should be opened without a relevant reason and appropriate participant consent.
Bias-aware
Matching outcomes and data coverage are reviewed for blind spots, imbalance and over-reliance on historical patterns.
Secure by design
Access to sensitive programme information is restricted, recorded and proportionate to the decision being made.
Outcome-aware
Models improve from documented programme outcomes—not from unverified attention signals alone.
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