Bidirectional Symbolic Verification Architecture (BSVA) v1.0

From Generation to Audit: Structuring AI Safety in High-Risk Medical Domains

The Bidirectional Symbolic Verification Architecture (BSVA) was developed in response to the growing use of large language models (LLMs) in clinical settings—especially where patient safety depends not just on fluent language, but on symbolic precision. BSVA defines a structured architecture to prevent protocol drift, eliminate hallucinated outputs, and preserve clinical integrity during AI-assisted documentation, decision support, and training simulation.

Unlike surface-level validation techniques, BSVA separates language generation from structural verification. It employs a two-phase system: a bottom-up generation phase governed by Symbolic Containment Layers (SCLs), followed by a top-down audit that scores each output’s logic, term fidelity, and protocol alignment using a Symbolic Fidelity Score (SFS). Outputs are routed based on thresholds—delivered, rejected, or escalated for human review.

BSVA is not a clinical model. It is a symbolic safety scaffold.
It enables LLMs to operate within clearly defined containment boundaries and requires each output to justify its clinical reasoning structure before reaching an end user. This makes BSVA particularly suited for integration into EMS education, EMR systems, SDKs, and regulatory-compliant clinical AI tools.

While other frameworks on this site address ethics, identity, or symbolic governance, BSVA is unapologetically operational. It is designed for developers, clinical directors, and regulatory bodies who require verifiable reasoning—not just plausible language—from their AI systems.