Beneficial is built for organizations that can't afford black boxes.
The evaluation runs on declared information only. No documents, datasets, or source code are ever transmitted or stored. During Early Access, project descriptions are accessible only to authorized Beneficial team members under strict confidentiality. Submitted information is used solely for evaluation and protocol improvement. Never to train third-party models.
See the method →The engine is rules-based. No probabilistic model, no drift between runs. Same context, same result. That's what makes a verdict defensible.
See the method →Regulatory sources, evaluated dimensions, and scores are fully documented. The verdict can be presented to a board, a regulator, or an auditor. It's dated, sourced against named standards, and archivable.
Submissions are reviewed before evaluation to prioritize projects genuinely at the decision stage. Human oversight covers the declared context. Never the verdict computation.
The engine scores against 15 international standards: AI Act, GDPR, ISO/IEC 42001, NIST AI RMF, OECD AI Principles, and sector-specific frameworks. The regulatory corpus is updated as norms evolve.
See the frameworks →Beneficial doesn't sell implementation solutions. The verdict is independent of any vendor, integrator, or cloud provider. Zero conflict of interest between evaluation and execution.
Our engine only scores projects with a real decision at stake.
Beneficial is currently in Early Access, open to a limited number of organizations.
Submit your AI project →Proprietary method. Same inputs, same verdict.